Variable bus stops across a bus route in a regional transportation network

Information

  • Patent Grant
  • 9441981
  • Patent Number
    9,441,981
  • Date Filed
    Friday, June 20, 2014
    10 years ago
  • Date Issued
    Tuesday, September 13, 2016
    8 years ago
Abstract
Disclosed are a method and a system of variable bus stops across a bus route in a regional transportation network, according to one embodiment. A method of a bus server includes analyzing a current geospatial location of a mobile device responsive to a pick up request of a prospective bus passenger, associating a closest street intersection with the current geospatial location of the mobile device, and determining if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. A message may be communicated to the mobile device based on the determination of whether the bus route traverses the closest street intersection. A bus associated with the bus route may be instructed to pick up the prospective bus passenger when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device.
Description
FIELD OF TECHNOLOGY

This disclosure relates generally to the technical fields of communications and, in one example embodiment, to a method, apparatus, and system of variable bus stops across a bus route in a regional transportation network.


BACKGROUND

Individuals may rely on buses in order to accomplish daily tasks (e.g., to get to and/or from work and/or to run errands). Bus stops may not be properly located in order to address changing demands of bus passengers and/or may make it difficult for individuals to effectively use the bus. It may be inefficient for buses and/or bus passengers to use set bus stops along a route as effective pick up locations and/or drop off locations may vary drastically on an hourly, daily, and/or yearly basis.


SUMMARY

A method, device and system of variable bus stops across a bus route in a regional transportation network. In one aspect, a method of a bus server includes analyzing a current geospatial location of a mobile device responsive to a pick up request of a prospective bus passenger, associating a closest street intersection with the current geospatial location of the mobile device, and determining if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. A message may be communicated to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device.


A bus associated with the bus route may be instructed to pick up the prospective bus passenger at the closest street intersection on the bus route when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. An estimated time of arrival of the bus may be communicated to the prospective bus passenger through the message. The bus may only traverse the bus route in a unidirectional looping fashion (such that a particular bus on the bus route for which the closest street intersection is in a forward path of the particular bus is closest is preferred, as compared to other buses on the bus route that have already departed from the closest street intersection in forward journey on the bus route). The particular bus may be an autonomously navigating vehicle and/or a semiautonomously navigating vehicle.


Walking directions may be provided to the prospective bus passenger to the closest street intersection on the bus route. The mobile device may be periodically pinged to provide pickup updates to the prospective bus passenger based on a request of the prospective bus passenger. Multiple ones of the prospective bus passengers in a neighborhood of a current geospatial vicinity of the prospective bus passenger may be routed to a common intersection point that is within a threshold distance from each of the prospective bus passengers of the neighborhood to minimize delays of the particular bus on the bus route. The closest street intersection may be associated with an address that provides for safe navigation of the particular bus on the bus route, such that the particular bus is able to make a pit stop at a safe stopping location when picking up the prospective bus passenger.


A bus fare associated with a route of the bus may be settled directly on the mobile device of the prospective bus passenger prior to the prospective bus passenger boarding the bus. The bus fare may be dependent upon a distance desired to be travelled by the prospective bus passenger. The prospective bus passenger may select a drop off location using the mobile device. The drop off location may be a scheduled bus stop, a custom bus stop, and/or a shared ad-hoc bus stop with other current and prospective bus passengers on the bus route. The prospective bus passenger may pay a premium when the prospective bus passenger selects the custom bus stop on the bus route. The particular bus may be routed to the closest street intersection only when the bus fare is paid on the mobile device. The particular bus may open a door of the bus when the prospective bus passenger swipes the mobile device on a reader of the particular bus when the bus fare has been paid with the mobile device by the prospective bus passenger.


In another aspect, a method of a bus sever includes analyzing a current geospatial location of a mobile device responsive to a pick up request of a prospective bus passenger, associating a closest street intersection with the current geospatial location of the mobile device, and determining if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. The method also includes instructing a bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. A message may be communicated to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device.


In yet another aspect, a system includes a mobile device having a current geospatial location, a network, and a bus server. The bus server is configured to analyze the current geospatial location of the mobile device responsive to a pick up request of a prospective bus passenger, associate a closest street intersection with the current geospatial location of the mobile device, determine if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device, and communicate, through the network, a message to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device.


A pick-up algorithm may instruct a bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device. A time-of-arrival algorithm may communicate an estimated time of arrival of the bus to the prospective bus passenger through the message. The bus may only traverse the bus route in a unidirectional looping fashion (such that a particular bus on the bus route for which the closest street intersection is in a forward path of the particular bus is closest is preferred, as compared to other buses on the bus route that have already departed from the closest street intersection in forward journey on the bus route). The particular bus may be an autonomously navigating vehicle, and/or a semiautonomously navigating vehicle.


A direction algorithm may provide walking directions to the prospective bus passenger to the closest street intersection on the bus route. An update algorithm may periodically ping the mobile device to provide pickup updates to the prospective bus passenger based on a request of the prospective bus passenger. A rally algorithm may route multiple ones of the prospective bus passengers in a neighborhood of a current geospatial vicinity of the prospective bus passenger to a common intersection point that is within a threshold distance from each of the prospective bus passengers of the neighborhood to minimize delays of the particular bus on the bus route.


The closest street intersection may be associated with an address that provides for safe navigation of the particular bus on the bus route (such that the particular bus is able to make a pit stop at a safe stopping location when picking up the prospective bus passenger). A payment algorithm may directly settle a bus fare associated with a route of the bus on the mobile device of the prospective bus passenger prior to the prospective bus passenger boarding the bus. The bus fare may be dependent upon a distance desired to be travelled by the prospective bus passenger.


The prospective bus passenger may select a drop off location using the mobile device. The drop off location may be a scheduled bus stop, a custom bus stop, and/or a shared ad-hoc bus stop with other current and prospective bus passengers on the bus route. The prospective bus passenger may pay a premium when the prospective bus passenger selects the custom bus stop on the bus route. The particular bus may be routed to the closest street intersection only when the bus fare is paid on the mobile device. The particular bus may open a door of the bus when the prospective bus passenger swipes the mobile device on a reader of the particular bus when the bus fare has been paid with the mobile device by the prospective bus passenger.


The methods, systems, and apparatuses disclosed herein may be implemented in any means for achieving various aspects, and may be executed in a form of a machine-readable medium embodying a set of instructions that, when executed by a machine, cause the machine to perform any of the operations disclosed herein. Other features will be apparent from the accompanying drawings and from the detailed description that follows.





BRIEF DESCRIPTION OF THE DRAWINGS

Example embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which:



FIG. 1 is a regional transportation network view of a bus server receiving a pick-up request sent by a mobile device of a prospective bus passenger and communicating a message based on the pick-up request to the mobile device of the prospective bus passenger, according to one embodiment.



FIG. 2 is an exploded view of the bus server of FIG. 1, according to one embodiment.



FIG. 3 is a table view illustrating data relationships between the prospective bus passenger, the pick-up request, and the message of FIG. 1, according to one embodiment.



FIG. 4 is a critical path view illustrating a flow based on time where the prospective bus passenger with the mobile device sends pick-up request to the bus server of FIG. 1 and a message is communicated to the mobile device, according to one embodiment.



FIG. 5 is a schematic view of a unidirectional looping fashion of a bus route illustrating a forward path of a particular bus, according to one embodiment.



FIG. 6A is a user interface view displaying the pick-up request sent by the mobile device associated with the prospective bus passenger to the bus server of FIG. 1, according to one embodiment.



FIG. 6B is a user interface view displaying a message sent by the bus server to the mobile device associated with the prospective bus passenger of FIG. 1, according to one embodiment.



FIG. 7 is a graphical process flow of variable bus stops across the bus route in a regional transportation network, according to one embodiment.



FIG. 8 is a process flow detailing the operations involving variable bus stops across the bus route in a regional transportation network of FIG. 1, according to one embodiment.





Other features of the present embodiments will be apparent from the accompanying drawings and from the detailed description that follows.


DETAILED DESCRIPTION

Disclosed are a method and system of variable bus stops across the bus route in a regional transportation network. FIG. 1 is a regional transportation network view 150 of a bus server receiving a pick-up request sent by a mobile device of a prospective bus passenger and communicating a message based on the pick-up request to the mobile device of the prospective bus passenger, according t6 one embodiment. In particular, FIG. 1 shows a bus server 100, a network 101, a memory 102, a processor 104, a database 106, a prospective bus passenger 108, a mobile device 110, a closest street intersection 112, a pick-up request 114, a current geo-spatial location 116, a message 118, a bus 120, a bus route 122, a geo-spatial vicinity 124, and a threshold distance 126.



FIG. 1 illustrates a number of operations between the bus server 100, the prospective bus passenger 108, and the bus 120. Particularly, circle ‘1’ of FIG. 1 illustrates the pick-up request 114 being communicated from the mobile device 110 associated with the prospective bus passenger 108 to the bus server 100 through the network 101 (e.g., an Internet protocol network and/or a wide area network). The pick-up request 114 may include the current geo-spatial location 116 of the mobile device 110, a desired pick up time, a distance 308 desired to be traveled, a drop off location 306, and/or a desired bus fare 310. The mobile device 110 (e.g., a smartphone, a tablet, a laptop, a location service enabled portable device, and/or a personal planner) may communicate the pick-up request 114 through a network (e.g., the network 101 and/or a cellular network) using a browser application of the mobile device 110 (e.g., Google®, Chrome) and/or through a client-side application downloaded to the mobile device 110 (e.g., a Nextdoor.com mobile application, a Fatdoor.com mobile application). The prospective bus passenger 108 may be able to communicate the pick-up request 114 from any location (e.g., by indicating a future desired pick up location 302).


Circle ‘2’ shows the message 118 being communicated by the bus server 100 to the mobile device 110 associated with the prospective bus passenger 108. The message 118 may be generated, using the processor 104 and the memory 102, based on the pick-up request 114 communicated by the prospective bus passenger 108. The bus server 100 may analyze the current location of the mobile device 110, associate the current geo-spatial location 116 of the mobile device 110 with the closest street intersection 112, determine if a bus route 122 traverses the closest street intersection 112, and/or instruct a bus 120 that traverses the bus route 122 to pick up the prospective passenger at the closest street intersection 112.


The message 118 may be communicated to the mobile device 110 through the network 101. In one embodiment, the message 118 may include the closest street intersection 112 (e.g., an address associated with the closest street intersection 112), the bus fare 310, the estimated time of arrival 304, walking direction from the current geo-spatial location 116 to the closest street intersection 112, and/or a unique identifier of the bus 120 that will pick up the prospective bus passenger 108 (e.g., a bus number). The bus server 100 may simultaneously communicate a set of instructions through the network 101 to the bus 120 (e.g., the bus associated with the bus route 122 that traverses the closest street intersection 112). The set of instructions may route the bus 120 to a safe stopping location 706 to make a pit stop 704 to pick up the prospective bus passenger 108. The bus 120 may be an autonomous vehicle and/or a semiautonomous vehicle.


In one embodiment, the bus server 100 may create shared ad-hoc bus stops by routing multiple prospective bus passengers 108 in the geo-spatial vicinity 124 (e.g., a current geo-spatial vicinity 124) of the prospective bus passenger 108 to a common intersection point (e.g., the closest street intersection 112) that is in the threshold distance 126 from each of the prospective bus passengers 108. The bus server 100 may determine if a threshold number of prospective bus passengers 108 are and/or will be at the shared ad-hoc bus stop before creating the shared ad-hoc bus stop and/or instructing the bus 120 to pick up passengers at the shared ad-hoc bus stop. Prospective bus passengers 108 may be able to request, through the pick-up request 114, a custom bus stop (e.g., the bus 120 will pick them up and/or drop them off at a requested location (e.g., the current geo-spatial location 116). In one embodiment, the prospective bus passenger 108 may be required to pay a premium 602 for a custom bus stop (e.g., a fee in addition to a bus fare 310 and/or a higher bus fare 310).



FIG. 2 is an exploded view 250 of the bus server of FIG. 1, according to one embodiment. FIG. 2 shows a pick-up algorithm 202, a time-of-arrival algorithm 204, a direction algorithm 206, an update algorithm 208, a rally algorithm 210, and a payment algorithm 212.


The pick-up algorithm 202 may generate the set of instructions to route the bus 120 to the closest street intersection 112 and/or may instruct the bus 120 associated with the bus route 122 that traverses the closest street intersection 112 to pick up the prospective bus passenger(s) 108. In one embodiment, the pick-up algorithm 202 may instruct the bus 120 to only pick up (e.g., the doors only open for) certain prospective bus passengers 108 (e.g., prospective bus passengers 108 for whom the shared ad-hoc bus stop was created and/or prospective bus passengers 108 that sent the pick-up request 114 from which the set of instructions was generated).


The time-of-arrival algorithm 204 may communicate an estimated time of arrival 304 of the bus 120 to the mobile device 110 of the perspective bus 120 passenger through the message 118. In one embodiment, the time-of-arrival algorithm 204 may communicate a time until arrival to the prospective bus passenger 108 instead of or in addition to the time of arrival of the bus 120. The direction algorithm 206 may provide walking directions 604 to the prospective bus passenger 108. The walking directions 604 may be communicated as part of the message 118 and/or may direct the prospective bus passenger 108 from the current location of the mobile device 110 to the closest street intersection 112.


The update algorithm 208 may periodically ping the mobile device 110, providing updates to the prospective bus passenger 108 based on a request of the bus 120 passenger. The pickup updates may include progress of the bus 120 (e.g., a map through which the bus 120′ progress may be viewed) and/or time remaining until the bus 120 arrives. In one embodiment, the pickup updates may be sent as text messages 118 and/or push notifications and/or may be communicated at predetermined intervals (e.g., intervals specified by the bus server 100 and/or the prospective passenger). The intervals may include time intervals, progress points of the bus 120 (e.g., when the bus 120 is a specified distance 308 and/or time away), and/or when the prospective bus passenger 108 requests the pickup update.


The rally algorithm 210 may route multiple prospective bus passengers 108 to a common intersection point (e.g., the shared ad-hoc bus stop and/or the closest street intersection 112). The common intersection point may be required to be in the threshold distance 126 from each of the multiple prospective bus passengers 108. The rally algorithm 210 may determine the common intersection point based on a threshold number of prospective bus passengers 108 that may be routed to the common intersection point, a most efficient location of the common intersection point, and/or a most efficient manner of establishing common intersection points (e.g., the manner that minimizes delays of a particular bus route 122).


The payment algorithm 212 may enable a payment (e.g., payment of the bus fare 310 and/or the premium 702) of the prospective bus passenger 108 to be processed. The prospective bus passenger 108 may make payment using the mobile device 110. The payment may be made in the pick-up request 114, in response to the message 118, and/or before the bus 120 is routed to pick up the prospective bus passenger 108. The bus fare 310 and/or premium 602 may be dependent upon the distance 308 desired to be traveled by the prospective bus passenger 108, the number of prospective bus passengers 108 to be picked up and/or dropped off at the pick-up location and/or drop-off location of the prospective bus passenger 108, and/or a size of the current and/or predicted demand placed on the bus server 100.



FIG. 3 is a table view 350 illustrating data relationships between the prospective bus passenger, the pick-up request, and the message of FIG. 1, according to one embodiment. FIG. 3 shows a pick up location 302, an estimated time of arrival 304, a drop off location 306, a distance 308, and a bus fare 310. In one embodiment, the pick-up request 114 may include the current geo-spatial location 116 (e.g., a set of geo-spatial coordinates). The pick-up request 114 may be associated with the mobile device 110 and/or the prospective bus passenger 108 associated with the mobile device 110 (e.g., the name of the prospective bus passenger 108, a profile of the prospective bus passenger 108, and/or the payment information of the prospective bus passenger 108).


The pick up location 302 may be an address (e.g., an address of a building located at the closest street intersection 112), a location name (e.g., the name of a building and/or a landmark at the closest street intersection 112 and/or a name of the closest street intersection 112 (e.g., 1st and Main street)), and/or a set of geo-spatial coordinates. The estimated time of arrival 304 may be an estimated time of arrival 304. The estimated time of arrival 304 may be the time at which the bus 120 will arrive at the pick up location 302 provided the bus route 122 remains the same (e.g., no pit stops 704 are added) and/or the bus 120 continues at its current, scheduled, and/or predicted pace.


The estimated time of arrival 304 may be updated based on the addition of other pick up locations 302 and/or other pick-up requests 114 between the current location of the bus 120 and the pick up location 302. The updated estimated time of arrival 304 may be communicated to the prospective bus passenger 108 through pickup updates. In one embodiment, the bus server 100 may prioritize fidelity to estimated times of arrival 304 and/or pick up locations 302 that have already been communicated to prospective bus passengers 108. Additional pick-up requests 114 and/or additional pit stops 704 may not be accommodated if the bus server 100 determines that accommodation of the additional pick-up requests 114 and/or additional pit stops 704 would alter a threshold number of estimated times of arrival 304 and/or create a delay over a threshold amount. The prospective bus passenger 108 may be able to “prioritize” their pick up and/or estimated time of arrival 304, paying a premium 602 to have the bus 120 go directly to their pick up location 302 and/or to prevent the bus server 100 from delaying the estimated time of arrival 304 (e.g., preventing the bus server 100 from accommodating additional pick-up requests 114 between the current location of the bus 120 and the pick up location 302 of the prospective bus passenger 108 paying the premium 602).


The drop off location 306 may be a set of geo-spatial coordinates, a location name, and/or an address to which the prospective bus passenger 108 has requested to be taken. The distance 308 may be the distance 308 between the pick up location 302 and the drop off location 306 and/or the distance 308 the bus 120 will travel between the pick up location 302 and the drop off location 306. The bas fare may depend upon the distance 308, the nature of the pick up and/or drop off (e.g., whether the pick up location 302 and/or the drop off location 306 are custom bus stops, shared ad-hoc bus stops and/or scheduled bus stops), whether the pick up and/or drop off has been prioritized (e.g., by the prospective bus passenger 108 that requested the pick up and/or drop off), and/or a demand placed on the bus server 100 (e.g., whether the pick up and/or drop off associated with the bus fare 310 occurs at peak business hours).



FIG. 4 is a critical path view 450 illustrating a flow based on time where the prospective bus passenger with the mobile device sends pick-up request to the bus server of FIG. 1 and a message is communicated to the mobile device, according to one embodiment.


In step 402, a prospective bus passenger 108 may send a pick-up request 114 through a network 101 to a bus server 100 using the mobile device 110. The bus server 100 may then analyze a current geo-spatial location 116 of the mobile device 110 (e.g., the current geo-spatial location 116 communicated in the pick-up request 114) in step 404. The bus server 100 may associate the current geo-spatial location 116 of the mobile device 110 with a closest street intersection 112 in step 406.


In step 408, the bus server 100 may determine whether a bus route 122 traverses the closest street intersection 112. In step 410, the bus server 100 may instruct a bus 120 (e.g., by communicating a set of instructions through the network 101) to pick up the prospective bus passenger 108 at the closest street intersection 112 when the bus route 122 associated with the bus 120 is determined to traverse the closest street intersection 112. The bus server 100 may only instruct the bus 120 to pick up the prospective bus passenger 108 when the prospective bus passenger 108 has made payment of the bus fare 310 and/or premium 602 associated with the pick-up request 114. In step 412, the bus 120 may pick up the prospective bus passenger 108 at the closest street intersection 112.



FIG. 5 is a schematic view 550 of a unidirectional looping fashion of a bus route illustrating a forward path of a particular bus, according to one embodiment. FIG. 5 shows a particular bus 502, a forward path 504, and unidirectional looping fashion 506ing fashion 506. In one embodiment, buses 120 may only travel in the unidirectional looping fashion 506 such that buses 120 may only make pickups and/or drop offs at locations (e.g., pit stops 704, safe parking locations, and/or closest street intersections 112) that are in the forward path 504.


In one embodiment, the bus server 100 may prefer the nearest bus 120 to which the closest street intersection 112 is in the forward path 504 as compared to other buses 120 that have departed from the closest street intersection 112. In the example embodiment of FIG. 5, the particular bus 502 may be preferred to pick up the prospective bus passenger 108 from the closest street intersection 112 over the bus 120. While the bus 120 may be physically closer to the closest street intersection 112, the bus 120 is shown to have departed from the closest street intersection 112 such that the closest street intersection 112 is no longer in the forward path 504 of the bus 120 (or such that the closest street intersection 112 is further away from the closest street intersection 112 along the forward path 504 than is the particular bus 502).



FIG. 6A is a user interface view 650 displaying the pick-up request 114 sent by the mobile device 110 associated with the prospective bus passenger 108 to the bus server 100 of FIG. 1, according to one embodiment. In user interface A, the prospective bus passenger 108 may be able to set their pick up location 302 (e.g., a custom bus stop and/or the current geo-spatial location 116 of the mobile device 110). The user may be able to enter an intersection, an address, and/or place a pin on a map view to indicate the requested pick up location 302. The prospective bus passenger 108 may be able to select the desired drop off location 306 through similar means.


The bus server 100 may automatically determine whether a bus 120 traverses the closes street intersection and/or requested pick up location 302 and/or the prospective bus passenger 108 may query the server after inputting information on the mobile device 110. The pick-up request 114 may include a desired bus fare 310 range, a desired bus fare 310, a desired time of pick up, a desired time of drop off, and/or a desired ride duration time. In one embodiment, the prospective bus passenger 108 may be required to sign onto their profile (e.g., on Fatdoor.com) in order to submit the pick-up request 114.



FIG. 6B is a user interface view 651 displaying a message sent by the bus server to the mobile device associated with the prospective bus passenger of FIG. 1, according to one embodiment. In user interface B, the prospective bus passenger 108 may be able to view whether a bus 120 traverses the closes street intersection and/or requested pick up location 302. The mobile device 110 may display the unique identifier of the bus 120 (e.g., the bus number), the associated closest street intersection 112, the estimated time of arrival 304, the bus fare 310, the premium 602 (if applicable), and/or the walking directions 604. The prospective bus passenger 108 may be able to pay the bus fare 310 and/or premium 602 and/or contact an operator through the user interface B.


User interface C may enable the prospective user to select a payment method and/or complete the payment using the mobile device 110. The prospective user may be able to select and/or enter a credit card (e.g., a credit card for which the user has previously provided information (e.g., card number, expiration date, and/or security code), a debit card, and/or an e-banking method (e.g., account transfer, PayPal®, and/or Venmo®). User interface D may enable the prospective user to view and/or use walking directions 604 from the current geo-spatial location 116 of the mobile device 110 to the requested pick up location 302 (e.g., the closest street intersection 112). The bus 120 may be instructed to pick the prospective bus passenger 108 up at the pick up location 302 once payment has been made and/or the prospective bus passenger 108 has confirmed the ride.



FIG. 7 is a graphical process flow 750 of variable bus stops across the bus route in a regional transportation network, according to one embodiment. Particularly, FIG. 7 shows a reader 702, a pit stop 704, and a safe stopping location 706. In circle ‘1,’ the prospective bus passenger 108 may communicate the pick-up request 114 to the bus server 100. In one embodiment, the pick-up request 114 may include a comment from the prospective bus passenger 108 (e.g., that the prospective bus passenger 108 has a bicycle with them and/or requires a seat due to age and/or disability).


The bus server 100 may generate the message 118 based on the pick-up request 114 and/or communicate the message 118 to the mobile device 110 in circle ‘2.’ The prospective bus passenger 108 may indicate the desired drop off location 306 using the mobile device 110 in circle ‘3.’ In one embodiment, the prospective bus passenger 108 may indicate the desired drop off location 306 in the pick-up request 114.


In circle ‘4,’ the prospective bus passenger 108 may pay the bus fare 310 and/or premium 702 using the mobile device 110. The bus 120 may be routed to the closest street intersection 112 and/or the pick up location 302 to pick up the prospective bus passenger 108 in circle ‘5.’ In circle ‘6,’ the bus 120 may continue along the forward path 504 on the unidirectional looping fashion 506 to the closest street intersection 112.


The bus 120 may make a pit stop 704 at the safe stopping location 706 to pick up the prospective bus passenger 108. The prospective bus passenger 108 may swipe the mobile device 110 on the reader 702 of the bus 120 (e.g., the particular bus 502) in circle ‘7.’ In circle ‘8,’ the doors of the bus 120 may open in response to the mobile device 110 being swiped on the reader 702. In one embodiment, the reader 702 may sense a signal sent from the mobile device 110 and/or a code (e.g., a QR code and/or a bar code) sent to the mobile device 110 from the bus server 100. The bus 120 door may only open for prospective bus passengers 108 whom have paid the bus fare 310 and/or premium 702. The safe stopping location 706 may be a designated area (e.g., a bus stop) and/or may be a sensed location that the bus 120 has determined to be a safe stopping location 706 (e.g., using an optical sensor, a laser sensor, a radar sensor, and/or an ultrasound sensor).



FIG. 8 is a process flow 850 detailing the operations involving variable bus stops across the bus route in a regional transportation network of FIG. 1, according to one embodiment. Operation 802 may analyze a current geo-spatial location 116 of a mobile device 110 responsive to a pick-up request 114 of a prospective bus passenger 108. Operation 804 may associate a closest street intersection 112 with the current geo-spatial location 116 of the mobile device 110. Operation 806 may determine if a bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. Operation 808 may communicate a message 118 to the mobile device 110 based on the determination of whether the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110.


Disclosed are a method and system of variable bus stops across a bus route in a regional transportation network, according to one embodiment. In one embodiment, a method of a bus server 100 includes analyzing a current geo-spatial location 116 of a mobile device 110 responsive to a pick-up request 114 of a prospective bus passenger 108, associating a closest street intersection 112 with the current geo-spatial location 116 of the mobile device 110, and determining if a bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. A message 118 may be communicated to the mobile device 110 based on the determination of whether the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110.


A bus 120 associated with the bus route 122 may be instructed to pick up the prospective bus passenger 108 at the closest street intersection 112 on the bus route 122 when the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. An estimated time of arrival 304 of the bus 120 may be communicated to the prospective bus passenger 108 through the message 118. The bus 120 may only traverse the bus route 122 in a unidirectional looping fashion 506ing fashion 506 (such that a particular bus 502 on the bus route 122 for which the closest street intersection 112 is in a forward path 504 of the particular bus 502 is closest is preferred, as compared to other buses 120 on the bus route 122 that have already departed from the closest street intersection 112 in forward journey on the bus route 122). The particular bus 502 may be an autonomously navigating vehicle and/or a semiautonomously navigating vehicle.


Walking directions 604 may be provided to the prospective bus passenger 108 to the closest street intersection 112 on the bus route 122. The mobile device 110 may be periodically pinged to provide pickup updates to the prospective bus passenger 108 based on a request of the prospective bus passenger 108. Multiple ones of the prospective bus passengers 108 in a neighborhood of a current geo-spatial vicinity 124 of the prospective bus passenger 108 may be routed to a common intersection point that is within a threshold distance 126 from each of the prospective bus passengers 108 of the neighborhood to minimize delays of the particular bus 502 on the bus route 122. The closest street intersection 112 may be associated with an address that provides for safe navigation of the particular bus 502 on the bus route 122, such that the particular bus 502 is able to make a pit stop 704 at a safe stopping location 706 when picking up the prospective bus passenger 108.


A bus fare 310 associated with a route of the bus 120 may be settled directly on the mobile device 110 of the prospective bus passenger 108 prior to the prospective bus passenger 108 boarding the bus 120. The bus fare 310 may be dependent upon a distance 308 desired to be travelled by the prospective bus passenger 108. The prospective bus passenger 108 may select a drop off location 306 using the mobile device 110. The drop off location 306 may be a scheduled bus stop, a custom bus stop, and/or a shared ad-hoc bus stop with other current and prospective bus passengers 108 on the bus route 122. The prospective bus passenger 108 may pay a premium 702 when the prospective bus passenger 108 selects the custom bus stop on the bus route 122. The particular bus 502 may be routed to the closest street intersection 112 only when the bus fare 310 is paid on the mobile device 110. The particular bus 502 may open a door of the bus 120 when the prospective bus passenger 108 swipes the mobile device 110 on a reader 702 of the particular bus 502 when the bus fare 310 has been paid with the mobile device 110 by the prospective bus passenger 108.


In another embodiment, a method of a bus 120 sever includes analyzing a current geo-spatial location 116 of a mobile device 110 responsive to a pick-up request 114 of a prospective bus passenger 108, associating a closest street intersection 112 with the current geo-spatial location 116 of the mobile device 110, and determining if a bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. The method also includes instructing a bus 120 associated with the bus route 122 to pick up the prospective bus passenger 108 at the closest street intersection 112 on the bus route 122 when the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. A message 118 may be communicated to the mobile device 110 based on the determination of whether the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110.


In yet another embodiment, a system includes a mobile device 110 having a current geo-spatial location 116, a network 101, and a bus server 100. The bus server 100 is configured to analyze the current geo-spatial location 116 of the mobile device 110 responsive to a pick-up request 114 of a prospective bus passenger 108, associate a closest street intersection 112 with the current geo-spatial location 116 of the mobile device 110, determine if a bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110, and communicate, through the network 101, a message 118 to the mobile device 110 based on the determination of whether the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110.


A pick-up algorithm 202 may instruct a bus 120 associated with the bus route 122 to pick up the prospective bus passenger 108 at the closest street intersection 112 on the bus route 122 when the bus route 122 traverses the closest street intersection 112 associated with the current geo-spatial location 116 of the mobile device 110. A time-of-arrival algorithm 204 may communicate an estimated time of arrival 304 of the bus 120 to the prospective bus passenger 108 through the message 118. The bus 120 may only traverse the bus route 122 in a unidirectional looping fashion 506ing fashion 506 (such that a particular bus 502 on the bus route 122 for which the closest street intersection 112 is in a forward path 504 of the particular bus 502 is closest is preferred, as compared to other buses 120 on the bus route 122 that have already departed from the closest street intersection 112 in forward journey on the bus route 122). The particular bus 502 may be an autonomously navigating vehicle, and/or a semiautonomously navigating vehicle.


A direction algorithm 206 may provide walking directions 604 to the prospective bus passenger 108 to the closest street intersection 112 on the bus route 122. An update algorithm 208 may periodically ping the mobile device 110 to provide pickup updates to the prospective bus passenger 108 based on a request of the prospective bus passenger 108. A rally algorithm 210 may route multiple ones of the prospective bus passengers 108 in a neighborhood of a current geo-spatial vicinity 124 of the prospective bus passenger 108 to a common intersection point that is within a threshold distance 126 from each of the prospective bus passengers 108 of the neighborhood to minimize delays of the particular bus 502 on the bus route 122.


The closest street intersection 112 may be associated with an address that provides for safe navigation of the particular bus 502 on the bus route 122 (such that the particular bus 502 is able to make a pit stop 704 at a safe stopping location 706 when picking up the prospective bus passenger 108). A payment algorithm 212 may directly settle a bus fare 310 associated with a route of the bus 120 on the mobile device 110 of the prospective bus passenger 108 prior to the prospective bus passenger 108 boarding the bus 120. The bus fare 310 may be dependent upon a distance 308 desired to be travelled by the prospective bus passenger 108.


The prospective bus passenger 108 may select a drop off location 306 using the mobile device 110. The drop off location 306 may be a scheduled bus stop, a custom bus stop, and/or a shared ad-hoc bus stop with other current and prospective bus passengers 108 on the bus route 122. The prospective bus passenger 108 may pay a premium 702 when the prospective bus passenger 108 selects the custom bus stop on the bus route 122. The particular bus 502 may be routed to the closest street intersection 112 only when the bus fare 310 is paid on the mobile device 110. The particular bus 502 may open a door of the bus 120 when the prospective bus passenger 108 swipes the mobile device 110 on a reader 702 of the particular bus 502 when the bus fare 310 has been paid with the mobile device 110 by the prospective bus passenger 108.


An example embodiment will now be described. In one example embodiment, Jane may not have access to a car and/or may live in an area that makes use of a personal vehicle unnecessary (e.g., a metropolitan city center). She may rely on public transportation to get to and/or from work. Jane may live a long distance away from a standard bus stop and/or may not have time to wait at a location for a bus 120 that is often delayed and/or full.


Jane may be able to use her smart phone to request a pick up. She may receive a message 118 informing her that bus 2 is able to pick her up at the corner one block from her apartment in 10 minutes. Jane may be able to pay the bus fare 310 using her smart phone and/or quickly and easily get to work using the bus 120. In one embodiment, Jane may be in a hurry and/or request the bus 120 drop her off right outside of her office. Jane may be able to pay a premium 702 for the custom bus stop and/or get to work on time.


In another example embodiment, Jon may be visiting a new city. He may not want to take a taxi in order to save money. He may not know the bus 120 lines in the city and/or may not want to spend time studying bus 120 loops and/or determining which bus 120 and/or bus stop he should use. Jon may send a pick-up request 114 using his mobile device 110. He may request to be taken from a popular tourist attraction to a museum.


There may be several other prospective bus passengers 108 requesting pickups around Jon's location (e.g., other people leaving the popular tourist attraction). Jon may be directed to a shared ad-hoc bus stop along with other perspective bus 120 passengers. He may be picked up very close to the tourist attraction. Several passengers on the bus 120 may be going to the same museum as Jon and/or the bus 120 may drop Jon (along with the other passengers) off right outside of the museum. By using the regional transportation network, Jon may be able to get convenient bus 120 rides in a new city without having to travel long distances to find bus stops and/or become knowledgeable of the city's bus system.


Although the present embodiments have been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the various embodiments. For example, the various devices, algorithms, analyzers, generators, etc. described herein may be enabled and operated using hardware circuitry (e.g., CMOS based logic circuitry), firmware, software and/or any combination of hardware, firmware, and/or software (e.g., embodied in a machine readable medium). For example, the various electrical structure and methods may be embodied using transistors, logic gates, and electrical circuits (e.g., application specific integrated ASIC circuitry and/or in Digital Signal; Processor DSP circuitry).


In addition, it will be appreciated that the various operations, processes, and methods disclosed herein may be embodied in a machine-readable medium and/or a machine accessible medium compatible with a data processing system (e.g., a computer system), and may be performed in any order. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.

Claims
  • 1. A method of a bus server, comprising: analyzing a current geospatial location of a mobile device responsive to a pick up request of a prospective bus passenger;associating a closest street intersection with the current geospatial location of the mobile device;determining if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device;communicating a message to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device,wherein a bus fare associated with a route of the bus is settled directly on the mobile device of the prospective bus passenger prior to the prospective bus passenger boardinga bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route,wherein the bus fare is dependent upon a distance desired to be travelled by the prospective bus passenger,wherein the prospective bus passenger to select a drop off location using the mobile device,wherein the drop off location is at least one of a scheduled bus stop, a custom bus stop, and a shared ad-hoc bus stop with other current and prospective bus passengers on the bus route,wherein the prospective bus passenger to pay a premium when the prospective bus passenger selects the custom bus stop on the bus route,wherein a particular bus to be routed to the closest street intersection only when the bus fare is paid on the mobile device, andwherein the particular bus to open a door of the bus when the prospective bus passenger swipes the mobile device on a reader of the particular bus when the bus fare has been paid with the mobile device by the prospective bus passenger.
  • 2. The method of the bus server of claim 1, further comprising: instructing the bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route,wherein the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device; andcommunicating an estimated time of arrival of the bus to the prospective bus passenger through the message.
  • 3. The method of the bus server of claim 2: wherein the bus only traverses the bus route in a unidirectional looping fashion such that the particular bus on the bus route for which the closest street intersection is in a forward path of the particular bus is closest is preferred, as compared to other buses on the bus route that have already departed from the closest street intersection in forward journey on the bus route, andwherein the particular bus is at least one of an autonomously navigating vehicle, and a semiautonomously navigating vehicle.
  • 4. The method of the bus server of claim 3 further comprising: providing walking directions to the prospective bus passenger to the closest street intersection on the bus route.
  • 5. The method of the bus server of claim 4, further comprising: periodically pinging the mobile device to provide pickup updates to the prospective bus passenger based on a request of the prospective bus passenger; androuting multiple ones of the prospective bus passengers in a neighborhood of a current geospatial vicinity of the prospective bus passenger to a common intersection point that is within a threshold distance from each of the prospective bus passengers of the neighborhood to minimize delays of the particular bus on the bus route.
  • 6. The method of the bus server of claim 5: wherein the closest street intersection is associated with an address that provides for safe navigation of the particular bus on the bus route, such that the particular bus is able to make a pit stop at a safe stopping location when picking up the prospective bus passenger.
  • 7. A method of a bus sever, comprising: analyzing a current geospatial location of a mobile device responsive to a pick up request of a prospective bus passenger;associating a closest street intersection with the current geospatial location of the mobile device;determining if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device;instructing a bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route,wherein when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device,wherein a bus fare associated with the bus route is settled directly on the mobile device of the prospective bus passenger prior to the prospective bus passenger boarding the bus,wherein the bus fare is dependent upon a distance desired to be travelled by the prospective bus passenger,wherein the prospective bus passenger to select a drop off location using the mobile device,wherein the drop off location is at least one of a scheduled bus stop, a custom bus stop, and a shared ad-hoc bus stop with other current and prospective bus passengers on the bus route,wherein the prospective bus passenger to pay a premium when the prospective bus passenger selects the custom bus stop on the bus route,wherein a particular bus to be routed to the closest street intersection only when the bus fare is paid on the mobile device, andwherein the particular bus to open a door of the bus when the prospective bus passenger swipes the mobile device on a reader of the particular bus when the bus fare has been paid with the mobile device by the prospective bus passenger.
  • 8. The method of the bus server of claim 7 further comprising: communicating a message to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device; andcommunicating an estimated time of arrival of the bus to the prospective bus passenger through the message.
  • 9. The method of the bus server of claim 8: wherein the bus only traverses the bus route in a unidirectional looping fashion such that the particular bus on the bus route for which the closest street intersection is in a forward path of the particular bus is closest is preferred, as compared to other buses on the bus route that have already departed from the closest street intersection in forward journey on the bus route, andwherein the particular bus is at least one of an autonomously navigating vehicle, and a semiautonomously navigating vehicle.
  • 10. The method of the bus server of claim 9 further comprising: providing walking directions to the prospective bus passenger to the closest street intersection on the bus route.
  • 11. The method of the bus server of claim 10 further comprising: periodically pinging the mobile device to provide pickup updates to the prospective bus passenger based on a request of the prospective bus passenger; androuting multiple ones of the prospective bus passengers in a neighborhood of a current geospatial vicinity of the prospective bus passenger to a common intersection point that is within a threshold distance from each of the prospective bus passengers of the neighborhood to minimize delays of the particular bus on the bus route.
  • 12. The method of the bus server of claim 11: wherein the closest street intersection is associated with an address that provides for safe navigation of the particular bus on the bus route, such that the particular bus is able to make a pit stop at a safe stopping location when picking up the prospective bus passenger.
  • 13. A system comprising: a mobile device having a current geospatial location;a network; anda bus server configured to:analyze the current geospatial location of the mobile device responsive to a pick up request of a prospective bus passenger,associate a closest street intersection with the current geospatial location of the mobile device,determine if a bus route traverses the closest street intersection associated with the current geospatial location of the mobile device,communicate, through the network, a message to the mobile device based on the determination of whether the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device,a payment algorithm to directly settle a bus fare associated with the bus route on the mobile device of the prospective bus passenger prior to the prospective bus passenger boardinga bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route,wherein the bus fare is dependent upon a distance desired to be travelled by the prospective bus passenger,wherein the prospective bus passenger to select a drop off location using the mobile device,wherein the drop off location is at least one of a scheduled bus stop, a custom bus stop, and a shared ad-hoc bus stop with other current and prospective bus passengers on the bus route,wherein the prospective bus passenger to pay a premium when the prospective bus passenger selects the custom bus stop on the bus route,wherein a particular bus to be routed to the closest street intersection only when the bus fare is paid on the mobile device, andwherein the particular bus to open a door of the bus when the prospective bus passenger swipes the mobile device on a reader of the particular bus when the bus fare has been paid with the mobile device by the prospective bus passenger.
  • 14. The system of claim 13, further comprising: a pick-up algorithm to instruct the bus associated with the bus route to pick up the prospective bus passenger at the closest street intersection on the bus route,wherein when the bus route traverses the closest street intersection associated with the current geospatial location of the mobile device; anda time-of-arrival algorithm to communicate an estimated time of arrival of the bus to the prospective bus passenger through the message.
  • 15. The system of claim 14: wherein the bus only traverses the bus route in a unidirectional looping fashion such that the particular bus on the bus route for which the closest street intersection is in a forward path of the particular bus is closest is preferred, as compared to other buses on the bus route that have already departed from the closest street intersection in forward journey on the bus route, andwherein the particular bus is at least one of an autonomously navigating vehicle, and a semiautonomously navigating vehicle.
  • 16. The system of claim 15 further comprising: a direction algorithm to provide walking directions to the prospective bus passenger to the closest street intersection on the bus route;an update algorithm to periodically ping the mobile device to provide pickup updates to the prospective bus passenger based on a request of the prospective bus passenger; anda rally algorithm to route multiple ones of the prospective bus passengers in a neighborhood of a current geospatial vicinity of the prospective bus passenger to a common intersection point that is within a threshold distance from each of the prospective bus passengers of the neighborhood to minimize delays of the particular bus on the bus route.
  • 17. The system of claim 16: wherein the closest street intersection is associated with an address that provides for safe navigation of the particular bus on the bus route, such that the particular bus is able to make a pit stop at a safe stopping location when picking up the prospective bus passenger.
US Referenced Citations (1019)
Number Name Date Kind
2035218 Bloom Mar 1936 A
3253806 Eickmann May 1966 A
3556438 Meditz Jan 1971 A
3762669 Curci Oct 1973 A
4119163 Ball Oct 1978 A
4161843 Hui Jul 1979 A
4375354 Henriksson Mar 1983 A
4556198 Tominaga Dec 1985 A
4779203 McClure et al. Oct 1988 A
4914605 Loughmiller, Jr. et al. Apr 1990 A
4996468 Field et al. Feb 1991 A
5050844 Hawk Sep 1991 A
5199686 Fletcher Apr 1993 A
5208750 Kurami et al. May 1993 A
5325294 Keene Jun 1994 A
5372211 Wilcox et al. Dec 1994 A
5521817 Burdoin et al. May 1996 A
5577567 Johnson et al. Nov 1996 A
5581630 Bonneau, Jr. Dec 1996 A
5590062 Nagamitsu et al. Dec 1996 A
5617319 Arakawa et al. Apr 1997 A
5630103 Smith et al. May 1997 A
5671342 Millier et al. Sep 1997 A
5720363 Kipp Feb 1998 A
5751245 Janky et al. May 1998 A
5774133 Neave et al. Jun 1998 A
5794207 Walker et al. Aug 1998 A
5799263 Culbertson Aug 1998 A
5805810 Maxwell Sep 1998 A
5819269 Uomini Oct 1998 A
5826244 Huberman Oct 1998 A
5831664 Wharton et al. Nov 1998 A
5835896 Fisher et al. Nov 1998 A
5852810 Sotiroff et al. Dec 1998 A
5904214 Lin May 1999 A
5905499 McDowall et al. May 1999 A
5907322 Kelly et al. May 1999 A
5926765 Sasaki Jul 1999 A
5930474 Dunworth et al. Jul 1999 A
5937413 Hyun et al. Aug 1999 A
5940806 Danial Aug 1999 A
5991737 Chen Nov 1999 A
6024288 Gottlich et al. Feb 2000 A
6029141 Bezos et al. Feb 2000 A
6029195 Herz Feb 2000 A
6034618 Tatebayashi et al. Mar 2000 A
6036601 Heckel Mar 2000 A
6047194 Andersson Apr 2000 A
6047236 Hancock et al. Apr 2000 A
6049778 Walker et al. Apr 2000 A
6059263 Otema et al. May 2000 A
6073138 de l'Etraz et al. Jun 2000 A
6078906 Huberman Jun 2000 A
6088702 Plantz et al. Jul 2000 A
6092076 McDonough et al. Jul 2000 A
6092105 Goldman Jul 2000 A
6101484 Halbert et al. Aug 2000 A
6108639 Walker et al. Aug 2000 A
6122592 Arakawa et al. Sep 2000 A
6134486 Kanayama Oct 2000 A
6148260 Musk et al. Nov 2000 A
6148289 Virdy Nov 2000 A
6175831 Weinreich et al. Jan 2001 B1
6199076 Logan et al. Mar 2001 B1
6229533 Farmer et al. May 2001 B1
6236990 Geller et al. May 2001 B1
6269369 Robertson Jul 2001 B1
6308177 Israni et al. Oct 2001 B1
6317718 Fano Nov 2001 B1
6336111 Ashby et al. Jan 2002 B1
6339745 Novik Jan 2002 B1
6356834 Hancock et al. Mar 2002 B2
6381537 Chenault et al. Apr 2002 B1
6401085 Gershman et al. Jun 2002 B1
6405123 Rennard et al. Jun 2002 B1
6408307 Semple et al. Jun 2002 B1
6445983 Dickson et al. Sep 2002 B1
6453339 Schultz et al. Sep 2002 B1
6470268 Ashcraft et al. Oct 2002 B1
6480885 Olivier Nov 2002 B1
6487583 Harvey et al. Nov 2002 B1
6498982 Bellesfield et al. Dec 2002 B2
6507776 Fox, III Jan 2003 B1
6513069 Abato et al. Jan 2003 B1
6519629 Harvey et al. Feb 2003 B2
6532007 Matsuda Mar 2003 B1
6542813 Kovacs Apr 2003 B1
6542817 Miyaki Apr 2003 B2
6542936 Mayle et al. Apr 2003 B1
6557013 Ziff et al. Apr 2003 B1
6587787 Yokota Jul 2003 B1
6600418 Francis et al. Jul 2003 B2
6611751 Warren Aug 2003 B2
6615039 Eldering Sep 2003 B1
6622086 Polidi Sep 2003 B2
6633311 Douvikas et al. Oct 2003 B1
6636803 Hartz, Jr. et al. Oct 2003 B1
6640187 Chenault et al. Oct 2003 B1
6643663 Dabney et al. Nov 2003 B1
6646568 MacPhail et al. Nov 2003 B2
6647383 August et al. Nov 2003 B1
6658410 Sakamaki et al. Dec 2003 B1
6662016 Buckham et al. Dec 2003 B1
6672601 Hofheins et al. Jan 2004 B1
6677894 Sheynblat et al. Jan 2004 B2
6687878 Eintracht et al. Feb 2004 B1
6691105 Virdy Feb 2004 B1
6691114 Nakamura Feb 2004 B1
6711414 Lightman et al. Mar 2004 B1
6716101 Meadows et al. Apr 2004 B1
6719570 Tsuchioka Apr 2004 B2
6721748 Knight et al. Apr 2004 B1
6728635 Hamada et al. Apr 2004 B2
6745196 Colyer et al. Jun 2004 B1
6750881 Appelman Jun 2004 B1
6798407 Benman Sep 2004 B1
6816850 Culliss Nov 2004 B2
6819267 Edmark et al. Nov 2004 B1
6834229 Rafiah et al. Dec 2004 B2
6847823 Lehikoinen et al. Jan 2005 B2
6871140 Florance et al. Mar 2005 B1
6882307 Gifford Apr 2005 B1
6883748 Yoeli Apr 2005 B2
6889213 Douvikas et al. May 2005 B1
6907405 Brett Jun 2005 B2
6918576 Finkbeiner Jul 2005 B2
6926233 Corcoran, III Aug 2005 B1
6931419 Lindquist Aug 2005 B1
6950791 Bray et al. Sep 2005 B1
6963879 Colver et al. Nov 2005 B2
6968179 De Vries Nov 2005 B1
6968513 Rinebold et al. Nov 2005 B1
6974123 Latvys Dec 2005 B2
6976031 Toupal et al. Dec 2005 B1
6978284 McBrearty et al. Dec 2005 B2
6983139 Dowling et al. Jan 2006 B2
6987976 Kohar et al. Jan 2006 B2
7006881 Hoffberg et al. Feb 2006 B1
7013292 Hsu et al. Mar 2006 B1
7024397 Donahue Apr 2006 B1
7024455 Yokobori et al. Apr 2006 B2
7038681 Scott et al. May 2006 B2
7047202 Jaipuria et al. May 2006 B2
7050909 Nichols et al. May 2006 B2
7068309 Toyama et al. Jun 2006 B2
7069308 Abrams Jun 2006 B2
7072849 Filepp et al. Jul 2006 B1
7079943 Flann et al. Jul 2006 B2
7080019 Hurzeler Jul 2006 B1
7080096 Imamura Jul 2006 B1
7099745 Ebert Aug 2006 B2
7099862 Fitzpatrick et al. Aug 2006 B2
7117254 Lunt et al. Oct 2006 B2
7130702 Morrell Oct 2006 B2
7136915 Rieger, III Nov 2006 B2
7155336 Dorfman et al. Dec 2006 B2
7158878 Rasmussen et al. Jan 2007 B2
7177872 Schwesig et al. Feb 2007 B2
7178720 Strubbe et al. Feb 2007 B1
7184990 Walker et al. Feb 2007 B2
7188056 Kagarlis Mar 2007 B2
7188080 Walker et al. Mar 2007 B1
7188153 Lunt et al. Mar 2007 B2
7209803 Okamoto et al. Apr 2007 B2
7218993 Yasukawa et al. May 2007 B2
7228232 Bodin et al. Jun 2007 B2
7233942 Nye Jun 2007 B2
7249123 Elder et al. Jul 2007 B2
7249732 Sanders, Jr. et al. Jul 2007 B2
7251647 Hoblit Jul 2007 B2
7254559 Florance et al. Aug 2007 B2
7269590 Hull et al. Sep 2007 B2
7293019 Dumais et al. Nov 2007 B2
7296026 Patrick et al. Nov 2007 B2
7306186 Kusic Dec 2007 B2
7324810 Nave et al. Jan 2008 B2
7343564 Othmer Mar 2008 B2
7353034 Haney Apr 2008 B2
7353114 Rohlf et al. Apr 2008 B1
7353199 DiStefano, III Apr 2008 B1
7359871 Paasche et al. Apr 2008 B1
7359894 Liebman et al. Apr 2008 B1
7373244 Kreft May 2008 B2
7375618 Quintos May 2008 B2
7383251 Might Jun 2008 B2
7386542 Maybury et al. Jun 2008 B2
7389210 Kagarlis Jun 2008 B2
7424438 Vianello Sep 2008 B2
7424541 Bourne Sep 2008 B2
7426970 Olsen Sep 2008 B2
7433832 Bezos et al. Oct 2008 B1
7433868 Satomi et al. Oct 2008 B1
7437368 Kolluri et al. Oct 2008 B1
7441031 Shrinivasan et al. Oct 2008 B2
7444241 Grimm Oct 2008 B2
7447509 Cossins et al. Nov 2008 B2
7447685 Nye Nov 2008 B2
7447771 Taylor Nov 2008 B1
7454524 Jeong Nov 2008 B2
7475953 Osborn et al. Jan 2009 B2
7477285 Johnson Jan 2009 B1
7478324 Ohtsu Jan 2009 B1
7480867 Racine et al. Jan 2009 B1
7483960 Kyusojin Jan 2009 B2
7487114 Florance et al. Feb 2009 B2
7496603 Deguchi et al. Feb 2009 B2
7500258 Eldering Mar 2009 B1
7505919 Richardson Mar 2009 B2
7505929 Angert et al. Mar 2009 B2
7520466 Bostan Apr 2009 B2
7525276 Eaton Apr 2009 B2
7561169 Carroll Jul 2009 B2
7562023 Yamamoto Jul 2009 B2
7580862 Montelo et al. Aug 2009 B1
7581702 Olson et al. Sep 2009 B2
7587276 Gold et al. Sep 2009 B2
7596511 Hall et al. Sep 2009 B2
7599795 Blumberg et al. Oct 2009 B1
7599935 La Rotonda et al. Oct 2009 B2
7617048 Simon et al. Nov 2009 B2
7636687 Foster et al. Dec 2009 B2
7640204 Florance et al. Dec 2009 B2
7658346 Goossen Feb 2010 B2
7668405 Gallagher Feb 2010 B2
7669123 Zuckerberg et al. Feb 2010 B2
7680673 Wheeler Mar 2010 B2
7680859 Schiller Mar 2010 B2
7693953 Middleton et al. Apr 2010 B2
7702545 Compton et al. Apr 2010 B1
7725492 Sittig et al. May 2010 B2
7734254 Frost et al. Jun 2010 B2
7761789 Erol et al. Jul 2010 B2
7792815 Aravamudan et al. Sep 2010 B2
7797256 Zuckerberg et al. Sep 2010 B2
7801542 Stewart Sep 2010 B1
7802290 Bansal et al. Sep 2010 B1
7808378 Hayden Oct 2010 B2
7809709 Harrison, Jr. Oct 2010 B1
7809805 Stremel et al. Oct 2010 B2
7810037 Edwards et al. Oct 2010 B1
7812717 Cona et al. Oct 2010 B1
7823073 Holmes et al. Oct 2010 B2
7827052 Scott et al. Nov 2010 B2
7827120 Evans et al. Nov 2010 B1
7827208 Bosworth et al. Nov 2010 B2
7827265 Cheever et al. Nov 2010 B2
7831917 Karam Nov 2010 B1
7840224 Vengroff et al. Nov 2010 B2
7840319 Zhong Nov 2010 B2
7840558 Wiseman et al. Nov 2010 B2
7853518 Cagan Dec 2010 B2
7853563 Alvarado et al. Dec 2010 B2
7860889 Martino et al. Dec 2010 B1
7870199 Galli et al. Jan 2011 B2
7873471 Gieseke Jan 2011 B2
7881864 Smith Feb 2011 B2
7886024 Kelly et al. Feb 2011 B2
7894933 Mountz et al. Feb 2011 B2
7894939 Zini et al. Feb 2011 B2
7894981 Yamane et al. Feb 2011 B2
7904366 Pogust Mar 2011 B2
7933808 Garcia Apr 2011 B2
7933810 Morgenstern Apr 2011 B2
7945653 Zuckerberg et al. May 2011 B2
7949714 Burnim May 2011 B1
7958011 Cretney et al. Jun 2011 B1
7961986 Jing et al. Jun 2011 B1
7962281 Rasmussen et al. Jun 2011 B2
7966567 Abhyanker Jun 2011 B2
7969606 Chu Jun 2011 B2
7970657 Morgenstern Jun 2011 B2
7980808 Chilson et al. Jul 2011 B2
7991703 Watkins Aug 2011 B1
7996109 Zini et al. Aug 2011 B2
8010230 Zini et al. Aug 2011 B2
8027943 Juan et al. Sep 2011 B2
8046309 Evans et al. Oct 2011 B2
8051089 Gargi et al. Nov 2011 B2
8060389 Johnson Nov 2011 B2
8060555 Grayson et al. Nov 2011 B2
8064590 Abhyanker Nov 2011 B2
8065291 Knorr Nov 2011 B2
8103734 Galli et al. Jan 2012 B2
8107879 Pering et al. Jan 2012 B2
8112419 Hancock et al. Feb 2012 B2
8117486 Handley Feb 2012 B2
8136145 Fetterman et al. Mar 2012 B2
8139514 Weber et al. Mar 2012 B2
8145703 Frishert et al. Mar 2012 B2
8149113 Diem Apr 2012 B2
8167234 Moore May 2012 B1
8171128 Zuckerberg et al. May 2012 B2
8190476 Urbanski et al. May 2012 B2
8195601 Law et al. Jun 2012 B2
8195744 Julia et al. Jun 2012 B2
8204624 Zini et al. Jun 2012 B2
8204776 Abhyanker Jun 2012 B2
8204952 Stremel et al. Jun 2012 B2
8223012 Diem Jul 2012 B1
8225376 Zuckerberg et al. Jul 2012 B2
8229470 Ranjan et al. Jul 2012 B1
8249943 Zuckerberg et al. Aug 2012 B2
8271057 Levine et al. Sep 2012 B2
8275546 Xiao et al. Sep 2012 B2
8290943 Carbone et al. Oct 2012 B2
8292215 Olm et al. Oct 2012 B2
8296373 Bosworth et al. Oct 2012 B2
8301743 Curran et al. Oct 2012 B2
8315389 Qiu et al. Nov 2012 B2
8326091 Jing et al. Dec 2012 B1
8326315 Phillips et al. Dec 2012 B2
8328130 Goossen Dec 2012 B2
8352183 Thota et al. Jan 2013 B2
8364757 Scott et al. Jan 2013 B2
8370003 So et al. Feb 2013 B2
8380382 Sung et al. Feb 2013 B2
8380638 Watkins Feb 2013 B1
8391789 Palin et al. Mar 2013 B2
8391909 Stewart Mar 2013 B2
8401771 Krumm et al. Mar 2013 B2
8402094 Bosworth et al. Mar 2013 B2
8402372 Gillespie et al. Mar 2013 B2
8412576 Urbanski Apr 2013 B2
8412675 Alvarado et al. Apr 2013 B2
8427308 Baron, Sr. et al. Apr 2013 B1
8428565 Middleton et al. Apr 2013 B2
8433650 Thomas Apr 2013 B1
8438156 Redstone et al. May 2013 B2
8442923 Gross May 2013 B2
8443107 Burdette et al. May 2013 B2
8447810 Roumeliotis et al. May 2013 B2
8463764 Fujioka et al. Jun 2013 B2
8473199 Blumberg et al. Jun 2013 B2
8493849 Fuste Vilella et al. Jul 2013 B2
8498947 Haake Jul 2013 B1
8504284 Brülle-Drews et al. Aug 2013 B2
8504512 Herzog et al. Aug 2013 B2
8510268 Laforge et al. Aug 2013 B1
8521656 Zimberoff et al. Aug 2013 B2
8538458 Haney Sep 2013 B2
8543143 Chandra et al. Sep 2013 B2
8543323 Gold et al. Sep 2013 B1
8548493 Rieger, III Oct 2013 B2
8554770 Purdy Oct 2013 B2
8554852 Burnim Oct 2013 B2
8584091 Champion et al. Nov 2013 B2
8589330 Petersen et al. Nov 2013 B2
8594715 Stewart Nov 2013 B1
8595292 Grayson et al. Nov 2013 B2
8600602 McAndrew et al. Dec 2013 B1
8615565 Randall Dec 2013 B2
8620532 Curtis et al. Dec 2013 B2
8620827 Watkins, III Dec 2013 B1
8626699 Xie et al. Jan 2014 B2
8627506 Vera et al. Jan 2014 B2
8649976 Kreft Feb 2014 B2
8650103 Wilf et al. Feb 2014 B2
8655873 Mitchell et al. Feb 2014 B2
8660541 Beresniewicz et al. Feb 2014 B1
8666660 Sartipi et al. Mar 2014 B2
8671095 Gross Mar 2014 B2
8671106 Lee et al. Mar 2014 B1
8688594 Thomas et al. Apr 2014 B2
8694605 Burrell et al. Apr 2014 B1
8695919 Shachor et al. Apr 2014 B2
8712441 Haney Apr 2014 B2
8713055 Callahan et al. Apr 2014 B2
8713143 Centola et al. Apr 2014 B2
8718910 Guéziec May 2014 B2
8723679 Whisenant May 2014 B2
8732155 Vegnaduzzo et al. May 2014 B2
8732219 Ferries et al. May 2014 B1
8732846 D'Angelo et al. May 2014 B2
8738292 Faaborg May 2014 B1
8775405 Gross Jul 2014 B2
D710454 Barajas et al. Aug 2014 S
8794566 Hutson Aug 2014 B2
8799253 Valliani et al. Aug 2014 B2
8825226 Worley, III et al. Sep 2014 B1
8832556 Steinberg Sep 2014 B2
20010016795 Bellinger Aug 2001 A1
20010020955 Nakagawa et al. Sep 2001 A1
20010029426 Hancock et al. Oct 2001 A1
20010036833 Koshima et al. Nov 2001 A1
20010037721 Hasegawa et al. Nov 2001 A1
20010042087 Kephart et al. Nov 2001 A1
20010049616 Khuzadi et al. Dec 2001 A1
20010049636 Hudda et al. Dec 2001 A1
20020019739 Juneau et al. Feb 2002 A1
20020023018 Kleinbaum Feb 2002 A1
20020026388 Roebuck Feb 2002 A1
20020029350 Cooper et al. Mar 2002 A1
20020030689 Eichel et al. Mar 2002 A1
20020038225 Klasky et al. Mar 2002 A1
20020046131 Boone et al. Apr 2002 A1
20020046243 Morris et al. Apr 2002 A1
20020049617 Lencki et al. Apr 2002 A1
20020059201 Work May 2002 A1
20020059379 Harvey et al. May 2002 A1
20020065691 Twig et al. May 2002 A1
20020065739 Florance et al. May 2002 A1
20020070967 Tanner et al. Jun 2002 A1
20020072848 Hamada et al. Jun 2002 A1
20020077060 Lehikoinen et al. Jun 2002 A1
20020077901 Katz Jun 2002 A1
20020078171 Schneider Jun 2002 A1
20020087260 Hancock et al. Jul 2002 A1
20020087506 Reddy Jul 2002 A1
20020090996 Maehiro Jul 2002 A1
20020091556 Fiala et al. Jul 2002 A1
20020097267 Dinan et al. Jul 2002 A1
20020099693 Kofsky Jul 2002 A1
20020103813 Frigon Aug 2002 A1
20020103892 Rieger Aug 2002 A1
20020124009 Hoblit Sep 2002 A1
20020124053 Adams et al. Sep 2002 A1
20020130906 Miyaki Sep 2002 A1
20020133292 Miyaki Sep 2002 A1
20020143462 Warren Oct 2002 A1
20020147638 Banerjee et al. Oct 2002 A1
20020156782 Rubert Oct 2002 A1
20020156917 Nye Oct 2002 A1
20020160762 Nave et al. Oct 2002 A1
20020161666 Fraki et al. Oct 2002 A1
20020169662 Claiborne Nov 2002 A1
20020184496 Mitchell et al. Dec 2002 A1
20020188522 McCall et al. Dec 2002 A1
20030004802 Callegari Jan 2003 A1
20030005035 Rodgers Jan 2003 A1
20030018521 Kraft et al. Jan 2003 A1
20030023489 McGuire et al. Jan 2003 A1
20030023586 Knorr Jan 2003 A1
20030036958 Warmus et al. Feb 2003 A1
20030036963 Jacobson et al. Feb 2003 A1
20030055983 Callegari Mar 2003 A1
20030061503 Katz et al. Mar 2003 A1
20030063072 Brandenberg et al. Apr 2003 A1
20030064705 Desiderio Apr 2003 A1
20030065716 Kyusojin Apr 2003 A1
20030069002 Hunter et al. Apr 2003 A1
20030069693 Snapp et al. Apr 2003 A1
20030078897 Florance et al. Apr 2003 A1
20030088520 Bohrer et al. May 2003 A1
20030145093 Oren et al. Jul 2003 A1
20030154020 Polidi Aug 2003 A1
20030154213 Ahn Aug 2003 A1
20030158668 Anderson Aug 2003 A1
20030177019 Santos et al. Sep 2003 A1
20030177192 Umeki et al. Sep 2003 A1
20030182222 Rotman et al. Sep 2003 A1
20030200192 Bell et al. Oct 2003 A1
20030218253 Avanzino et al. Nov 2003 A1
20030222918 Coulthard Dec 2003 A1
20030225632 Tong et al. Dec 2003 A1
20030225833 Pilat et al. Dec 2003 A1
20040003283 Goodman et al. Jan 2004 A1
20040021584 Hartz et al. Feb 2004 A1
20040024846 Randall et al. Feb 2004 A1
20040030525 Robinson et al. Feb 2004 A1
20040030741 Wolton et al. Feb 2004 A1
20040054428 Sheha et al. Mar 2004 A1
20040056762 Rogers Mar 2004 A1
20040088177 Travis et al. May 2004 A1
20040109012 Kraus et al. Jun 2004 A1
20040111302 Falk et al. Jun 2004 A1
20040122570 Sonoyama et al. Jun 2004 A1
20040122693 Hatscher et al. Jun 2004 A1
20040128215 Florance et al. Jul 2004 A1
20040135805 Gottsacker et al. Jul 2004 A1
20040139034 Farmer Jul 2004 A1
20040139049 Hancock et al. Jul 2004 A1
20040145593 Berkner et al. Jul 2004 A1
20040146199 Berkner et al. Jul 2004 A1
20040148275 Achlioptas Jul 2004 A1
20040153466 Ziff et al. Aug 2004 A1
20040157648 Lightman Aug 2004 A1
20040158488 Johnson Aug 2004 A1
20040162064 Himmelstein Aug 2004 A1
20040166878 Erskine et al. Aug 2004 A1
20040167787 Lynch et al. Aug 2004 A1
20040172280 Fraki et al. Sep 2004 A1
20040186766 Fellenstein et al. Sep 2004 A1
20040210661 Thompson Oct 2004 A1
20040215517 Chen et al. Oct 2004 A1
20040215559 Rebenack et al. Oct 2004 A1
20040217884 Samadani et al. Nov 2004 A1
20040217980 Radburn et al. Nov 2004 A1
20040220903 Shah et al. Nov 2004 A1
20040220906 Gargi et al. Nov 2004 A1
20040230562 Wysoczanski et al. Nov 2004 A1
20040236771 Colver et al. Nov 2004 A1
20040243478 Walker et al. Dec 2004 A1
20040257340 Jawerth Dec 2004 A1
20040260604 Bedingfield Dec 2004 A1
20040260677 Malpani et al. Dec 2004 A1
20040267625 Feng et al. Dec 2004 A1
20050015488 Bayyapu Jan 2005 A1
20050018177 Rosenberg et al. Jan 2005 A1
20050021750 Abrams Jan 2005 A1
20050027723 Jones et al. Feb 2005 A1
20050034075 Riegelman et al. Feb 2005 A1
20050044061 Klemow Feb 2005 A1
20050049971 Bettinger Mar 2005 A1
20050055353 Marx et al. Mar 2005 A1
20050086309 Galli et al. Apr 2005 A1
20050091027 Zaher et al. Apr 2005 A1
20050091175 Farmer Apr 2005 A9
20050091209 Frank et al. Apr 2005 A1
20050094851 Bodin et al. May 2005 A1
20050096977 Rossides May 2005 A1
20050097319 Zhu et al. May 2005 A1
20050108520 Yamamoto et al. May 2005 A1
20050114527 Hankey et al. May 2005 A1
20050114759 Williams et al. May 2005 A1
20050114783 Szeto May 2005 A1
20050120084 Hu et al. Jun 2005 A1
20050131761 Trika et al. Jun 2005 A1
20050137015 Rogers et al. Jun 2005 A1
20050143174 Goldman et al. Jun 2005 A1
20050144065 Calabria et al. Jun 2005 A1
20050154639 Zetmeir Jul 2005 A1
20050159970 Buyukkokten et al. Jul 2005 A1
20050171799 Hull et al. Aug 2005 A1
20050171832 Hull et al. Aug 2005 A1
20050171954 Hull et al. Aug 2005 A1
20050171955 Hull et al. Aug 2005 A1
20050177385 Hull et al. Aug 2005 A1
20050187823 Howes Aug 2005 A1
20050192859 Mertins et al. Sep 2005 A1
20050192912 Bator et al. Sep 2005 A1
20050192999 Cook et al. Sep 2005 A1
20050193410 Eldering Sep 2005 A1
20050197775 Smith Sep 2005 A1
20050197846 Pezaris et al. Sep 2005 A1
20050197950 Moya et al. Sep 2005 A1
20050198020 Garland et al. Sep 2005 A1
20050198031 Pezaris et al. Sep 2005 A1
20050198305 Pezaris et al. Sep 2005 A1
20050203768 Florance et al. Sep 2005 A1
20050203769 Weild Sep 2005 A1
20050203807 Bezos et al. Sep 2005 A1
20050209776 Ogino et al. Sep 2005 A1
20050209781 Anderson Sep 2005 A1
20050216186 Dorfman et al. Sep 2005 A1
20050216300 Appelman et al. Sep 2005 A1
20050216550 Paseman et al. Sep 2005 A1
20050219044 Douglass et al. Oct 2005 A1
20050235062 Lunt et al. Oct 2005 A1
20050240580 Zamir et al. Oct 2005 A1
20050251331 Kreft Nov 2005 A1
20050256756 Lam et al. Nov 2005 A1
20050259648 Kodialam et al. Nov 2005 A1
20050270299 Rasmussen et al. Dec 2005 A1
20050273346 Frost Dec 2005 A1
20050283497 Nurminen et al. Dec 2005 A1
20050288957 Eraker et al. Dec 2005 A1
20050288958 Eraker et al. Dec 2005 A1
20050289650 Kalogridis Dec 2005 A1
20060004680 Robarts et al. Jan 2006 A1
20060004703 Spivack et al. Jan 2006 A1
20060004734 Malkin et al. Jan 2006 A1
20060022048 Johnson Feb 2006 A1
20060023881 Akiyama et al. Feb 2006 A1
20060025883 Reeves Feb 2006 A1
20060026147 Cone et al. Feb 2006 A1
20060036588 Frank et al. Feb 2006 A1
20060036748 Nusbaum et al. Feb 2006 A1
20060041543 Achlioptas Feb 2006 A1
20060042483 Work et al. Mar 2006 A1
20060047825 Steenstra et al. Mar 2006 A1
20060048059 Etkin Mar 2006 A1
20060052091 Onyon et al. Mar 2006 A1
20060058921 Okamoto Mar 2006 A1
20060059023 Mashinsky Mar 2006 A1
20060064431 Kishore et al. Mar 2006 A1
20060074780 Taylor et al. Apr 2006 A1
20060075335 Gloor Apr 2006 A1
20060080613 Savant Apr 2006 A1
20060085419 Rosen Apr 2006 A1
20060088145 Reed et al. Apr 2006 A1
20060089882 Shimansky Apr 2006 A1
20060100892 Ellanti May 2006 A1
20060113425 Rader Jun 2006 A1
20060123053 Scannell Jun 2006 A1
20060125616 Song Jun 2006 A1
20060136127 Coch et al. Jun 2006 A1
20060136419 Brydon et al. Jun 2006 A1
20060143066 Calabria Jun 2006 A1
20060143067 Calabria Jun 2006 A1
20060143083 Wedeen Jun 2006 A1
20060143183 Goldberg et al. Jun 2006 A1
20060149624 Baluja et al. Jul 2006 A1
20060161599 Rosen Jul 2006 A1
20060178972 Jung et al. Aug 2006 A1
20060184578 La Rotonda et al. Aug 2006 A1
20060184617 Nicholas et al. Aug 2006 A1
20060184997 La Rotonda et al. Aug 2006 A1
20060190279 Heflin Aug 2006 A1
20060190281 Kott et al. Aug 2006 A1
20060194186 Nanda Aug 2006 A1
20060200384 Arutunian et al. Sep 2006 A1
20060212407 Lyon Sep 2006 A1
20060217885 Crady et al. Sep 2006 A1
20060218225 Hee Voon et al. Sep 2006 A1
20060218226 Johnson et al. Sep 2006 A1
20060223518 Haney Oct 2006 A1
20060226281 Walton Oct 2006 A1
20060229063 Koch Oct 2006 A1
20060230061 Sample et al. Oct 2006 A1
20060238383 Kimchi et al. Oct 2006 A1
20060242139 Butterfield et al. Oct 2006 A1
20060242178 Butterfield et al. Oct 2006 A1
20060242581 Manion et al. Oct 2006 A1
20060247940 Zhu et al. Nov 2006 A1
20060248573 Pannu et al. Nov 2006 A1
20060251292 Gokturk et al. Nov 2006 A1
20060253491 Gokturk et al. Nov 2006 A1
20060256008 Rosenberg Nov 2006 A1
20060264209 Atkinson et al. Nov 2006 A1
20060265277 Yasinovsky et al. Nov 2006 A1
20060265417 Amato et al. Nov 2006 A1
20060270419 Crowley et al. Nov 2006 A1
20060270421 Phillips et al. Nov 2006 A1
20060271287 Gold et al. Nov 2006 A1
20060271472 Cagan Nov 2006 A1
20060293976 Nam Dec 2006 A1
20060294011 Smith Dec 2006 A1
20070002057 Danzig et al. Jan 2007 A1
20070003182 Hunn Jan 2007 A1
20070005683 Omidyar Jan 2007 A1
20070005750 Lunt et al. Jan 2007 A1
20070011148 Burkey et al. Jan 2007 A1
20070011617 Akagawa et al. Jan 2007 A1
20070016689 Birch Jan 2007 A1
20070027920 Alvarado et al. Feb 2007 A1
20070032942 Thota Feb 2007 A1
20070033064 Abrahamsohn Feb 2007 A1
20070033182 Knorr Feb 2007 A1
20070038646 Thota Feb 2007 A1
20070043947 Mizikovsky et al. Feb 2007 A1
20070050360 Hull et al. Mar 2007 A1
20070061128 Odom et al. Mar 2007 A1
20070061405 Keohane et al. Mar 2007 A1
20070067219 Altberg et al. Mar 2007 A1
20070078747 Baack Apr 2007 A1
20070078772 Dadd Apr 2007 A1
20070099609 Cai May 2007 A1
20070105536 Tingo May 2007 A1
20070106627 Srivastava et al. May 2007 A1
20070112461 Zini et al. May 2007 A1
20070112645 Traynor et al. May 2007 A1
20070112729 Wiseman et al. May 2007 A1
20070118430 Wiseman et al. May 2007 A1
20070118525 Svendsen May 2007 A1
20070150375 Yang Jun 2007 A1
20070150603 Crull et al. Jun 2007 A1
20070156429 Godar Jul 2007 A1
20070159651 Disario et al. Jul 2007 A1
20070162432 Armstrong et al. Jul 2007 A1
20070162458 Fasciano Jul 2007 A1
20070162547 Ross Jul 2007 A1
20070162942 Hamynen et al. Jul 2007 A1
20070167204 Lyle et al. Jul 2007 A1
20070168852 Erol et al. Jul 2007 A1
20070168888 Jawerth Jul 2007 A1
20070174389 Armstrong et al. Jul 2007 A1
20070179905 Buch et al. Aug 2007 A1
20070185906 Humphries et al. Aug 2007 A1
20070192299 Zuckerberg et al. Aug 2007 A1
20070203644 Thota et al. Aug 2007 A1
20070203820 Rashid Aug 2007 A1
20070207755 Julia et al. Sep 2007 A1
20070208613 Backer Sep 2007 A1
20070208802 Barman et al. Sep 2007 A1
20070208916 Tomita Sep 2007 A1
20070214141 Sittig et al. Sep 2007 A1
20070218900 Abhyanker Sep 2007 A1
20070219712 Abhyanker Sep 2007 A1
20070226314 Eick et al. Sep 2007 A1
20070233291 Herde et al. Oct 2007 A1
20070233367 Chen et al. Oct 2007 A1
20070233375 Garg et al. Oct 2007 A1
20070239352 Thota et al. Oct 2007 A1
20070239552 Sundaresan Oct 2007 A1
20070239648 Thota Oct 2007 A1
20070245002 Nguyen et al. Oct 2007 A1
20070250321 Balusu Oct 2007 A1
20070250511 Endler et al. Oct 2007 A1
20070255785 Hayashi et al. Nov 2007 A1
20070255831 Hayashi et al. Nov 2007 A1
20070258642 Thota Nov 2007 A1
20070259654 Oijer Nov 2007 A1
20070260599 McGuire et al. Nov 2007 A1
20070261071 Lunt et al. Nov 2007 A1
20070266003 Wong et al. Nov 2007 A1
20070266097 Harik et al. Nov 2007 A1
20070266118 Wilkins Nov 2007 A1
20070268310 Dolph et al. Nov 2007 A1
20070270163 Anupam et al. Nov 2007 A1
20070271367 Yardeni et al. Nov 2007 A1
20070273558 Smith et al. Nov 2007 A1
20070281689 Altman et al. Dec 2007 A1
20070281690 Altman et al. Dec 2007 A1
20070281716 Altman et al. Dec 2007 A1
20070282621 Altman et al. Dec 2007 A1
20070282987 Fischer et al. Dec 2007 A1
20070288164 Gordon et al. Dec 2007 A1
20070288311 Underhill Dec 2007 A1
20070288621 Gundu et al. Dec 2007 A1
20070294357 Antoine Dec 2007 A1
20080005076 Payne et al. Jan 2008 A1
20080005231 Kelley et al. Jan 2008 A1
20080010343 Escaffi et al. Jan 2008 A1
20080010365 Schneider Jan 2008 A1
20080016051 Schiller Jan 2008 A1
20080020814 Kernene Jan 2008 A1
20080027772 Gernega et al. Jan 2008 A1
20080032666 Hughes et al. Feb 2008 A1
20080032703 Krumm et al. Feb 2008 A1
20080033641 Medalia Feb 2008 A1
20080033652 Hensley et al. Feb 2008 A1
20080033739 Zuckerberg et al. Feb 2008 A1
20080033776 Marchese Feb 2008 A1
20080040370 Bosworth et al. Feb 2008 A1
20080040428 Wei et al. Feb 2008 A1
20080040474 Zuckerberg et al. Feb 2008 A1
20080040475 Bosworth et al. Feb 2008 A1
20080040673 Zuckerberg et al. Feb 2008 A1
20080043020 Snow et al. Feb 2008 A1
20080043037 Carroll Feb 2008 A1
20080046976 Zuckerberg Feb 2008 A1
20080048065 Kuntz Feb 2008 A1
20080051932 Jermyn et al. Feb 2008 A1
20080059992 Amidon et al. Mar 2008 A1
20080065321 DaCosta Mar 2008 A1
20080065611 Hepworth et al. Mar 2008 A1
20080070593 Altman et al. Mar 2008 A1
20080070697 Robinson et al. Mar 2008 A1
20080071929 Motte et al. Mar 2008 A1
20080077464 Gottlieb et al. Mar 2008 A1
20080077581 Drayer et al. Mar 2008 A1
20080077642 Carbone et al. Mar 2008 A1
20080077708 Scott et al. Mar 2008 A1
20080086368 Bauman et al. Apr 2008 A1
20080086458 Robinson et al. Apr 2008 A1
20080091461 Evans et al. Apr 2008 A1
20080091723 Zuckerberg et al. Apr 2008 A1
20080091786 Jhanji Apr 2008 A1
20080097999 Horan Apr 2008 A1
20080098090 Geraci et al. Apr 2008 A1
20080098313 Pollack Apr 2008 A1
20080103959 Carroll et al. May 2008 A1
20080104227 Birnie et al. May 2008 A1
20080109718 Narayanaswami May 2008 A1
20080115082 Simmons et al. May 2008 A1
20080115226 Welingkar et al. May 2008 A1
20080117928 Abhyanker May 2008 A1
20080125969 Chen et al. May 2008 A1
20080126355 Rowley May 2008 A1
20080126411 Zhuang et al. May 2008 A1
20080126476 Nicholas et al. May 2008 A1
20080126478 Ferguson et al. May 2008 A1
20080133495 Fischer Jun 2008 A1
20080133649 Pennington Jun 2008 A1
20080134035 Pennington et al. Jun 2008 A1
20080148156 Brewer et al. Jun 2008 A1
20080154733 Wolfe Jun 2008 A1
20080155019 Wallace et al. Jun 2008 A1
20080162027 Murphy et al. Jul 2008 A1
20080162211 Addington Jul 2008 A1
20080162260 Rohan et al. Jul 2008 A1
20080167771 Whittaker et al. Jul 2008 A1
20080168068 Hutheesing Jul 2008 A1
20080168175 Tran Jul 2008 A1
20080172173 Chang et al. Jul 2008 A1
20080172244 Coupal et al. Jul 2008 A1
20080172288 Pilskalns et al. Jul 2008 A1
20080189292 Stremel et al. Aug 2008 A1
20080189380 Bosworth et al. Aug 2008 A1
20080189768 Callahan et al. Aug 2008 A1
20080195428 O'Sullivan Aug 2008 A1
20080195483 Moore Aug 2008 A1
20080208956 Spiridellis et al. Aug 2008 A1
20080215994 Harrison et al. Sep 2008 A1
20080221846 Aggarwal et al. Sep 2008 A1
20080222140 Lagad et al. Sep 2008 A1
20080229424 Harris et al. Sep 2008 A1
20080231630 Shenkar et al. Sep 2008 A1
20080238941 Kinnan et al. Oct 2008 A1
20080243378 Zavoli Oct 2008 A1
20080243667 Lecomte Oct 2008 A1
20080243830 Abhyanker Oct 2008 A1
20080255759 Abhyanker Oct 2008 A1
20080256230 Handley Oct 2008 A1
20080263460 Altberg et al. Oct 2008 A1
20080269992 Kawasaki Oct 2008 A1
20080270158 Abhyanker Oct 2008 A1
20080270366 Frank Oct 2008 A1
20080270615 Centola et al. Oct 2008 A1
20080270945 Abhyanker Oct 2008 A1
20080281854 Abhyanker Nov 2008 A1
20080288277 Fasciano Nov 2008 A1
20080288612 Kwon Nov 2008 A1
20080294678 Gorman et al. Nov 2008 A1
20080294747 Abhyanker Nov 2008 A1
20080300979 Abhyanker Dec 2008 A1
20080301565 Abhyanker Dec 2008 A1
20080306754 Abhyanker Dec 2008 A1
20080307053 Mitnick et al. Dec 2008 A1
20080307066 Amidon et al. Dec 2008 A1
20080307320 Payne et al. Dec 2008 A1
20080316021 Manz et al. Dec 2008 A1
20080319806 Abhyanker Dec 2008 A1
20090003265 Agarwal et al. Jan 2009 A1
20090006177 Beaver et al. Jan 2009 A1
20090006473 Elliott et al. Jan 2009 A1
20090007195 Beyabani Jan 2009 A1
20090018925 Abhyanker Jan 2009 A1
20090019004 Abhyanker Jan 2009 A1
20090019085 Abhyanker Jan 2009 A1
20090019122 Abhyanker Jan 2009 A1
20090019366 Abhyanker Jan 2009 A1
20090019373 Abhyanker Jan 2009 A1
20090029672 Manz Jan 2009 A1
20090030927 Cases et al. Jan 2009 A1
20090031006 Johnson Jan 2009 A1
20090031245 Brezina et al. Jan 2009 A1
20090031301 D'Angelo et al. Jan 2009 A1
20090043650 Abhyanker et al. Feb 2009 A1
20090044254 Tian Feb 2009 A1
20090048922 Morgenstern et al. Feb 2009 A1
20090049018 Gross Feb 2009 A1
20090049037 Gross Feb 2009 A1
20090049070 Steinberg Feb 2009 A1
20090049127 Juan et al. Feb 2009 A1
20090061883 Abhyanker Mar 2009 A1
20090063252 Abhyanker Mar 2009 A1
20090063467 Abhyanker Mar 2009 A1
20090063500 Zhai et al. Mar 2009 A1
20090064011 Abhyanker Mar 2009 A1
20090064144 Abhyanker Mar 2009 A1
20090069034 Abhyanker Mar 2009 A1
20090070334 Callahan et al. Mar 2009 A1
20090070435 Abhyanker Mar 2009 A1
20090077100 Hancock et al. Mar 2009 A1
20090102644 Hayden Apr 2009 A1
20090119275 Chen et al. May 2009 A1
20090132504 Vegnaduzzo et al. May 2009 A1
20090132644 Frishert et al. May 2009 A1
20090171950 Lunenfeld Jul 2009 A1
20090177577 Garcia Jul 2009 A1
20090177628 Yanagisawa et al. Jul 2009 A1
20090228305 Gustafsson et al. Sep 2009 A1
20090254971 Herz et al. Oct 2009 A1
20090271417 Toebes et al. Oct 2009 A1
20090271524 Davi et al. Oct 2009 A1
20090284530 Lester et al. Nov 2009 A1
20090287682 Fujioka et al. Nov 2009 A1
20090299551 So et al. Dec 2009 A1
20100011081 Crowley et al. Jan 2010 A1
20100017275 Carlson Jan 2010 A1
20100023388 Blumberg et al. Jan 2010 A1
20100024045 Sastry et al. Jan 2010 A1
20100051740 Yoeli Mar 2010 A1
20100057555 Butterfield et al. Mar 2010 A1
20100064007 Randall Mar 2010 A1
20100070075 Chirnomas Mar 2010 A1
20100076966 Strutton et al. Mar 2010 A1
20100077316 Omansky et al. Mar 2010 A1
20100079338 Wooden et al. Apr 2010 A1
20100082683 Law et al. Apr 2010 A1
20100083125 Zafar et al. Apr 2010 A1
20100088015 Lee Apr 2010 A1
20100094548 Tadman et al. Apr 2010 A1
20100100937 Tran Apr 2010 A1
20100106731 Cartmell et al. Apr 2010 A1
20100108801 Olm et al. May 2010 A1
20100118025 Smith et al. May 2010 A1
20100120422 Cheung et al. May 2010 A1
20100138259 Delk Jun 2010 A1
20100138318 Chun Jun 2010 A1
20100153279 Zahn Jun 2010 A1
20100191798 Seefeld et al. Jul 2010 A1
20100198684 Eraker et al. Aug 2010 A1
20100214250 Gillespie et al. Aug 2010 A1
20100231383 Levine et al. Sep 2010 A1
20100243794 Jermyn Sep 2010 A1
20100255899 Paulsen Oct 2010 A1
20100265034 Cap Oct 2010 A1
20100275033 Gillespie et al. Oct 2010 A1
20100299177 Buczkowski et al. Nov 2010 A1
20100306016 Solaro et al. Dec 2010 A1
20110001020 Forgac Jan 2011 A1
20110015954 Ward Jan 2011 A1
20110022540 Stern et al. Jan 2011 A1
20110040681 Ahroon Feb 2011 A1
20110040692 Ahroon Feb 2011 A1
20110041084 Karam Feb 2011 A1
20110061018 Piratla et al. Mar 2011 A1
20110066588 Xie et al. Mar 2011 A1
20110066648 Abhyanker et al. Mar 2011 A1
20110078012 Adamec Mar 2011 A1
20110078270 Galli et al. Mar 2011 A1
20110082747 Khan et al. Apr 2011 A1
20110087667 Hutheesing Apr 2011 A1
20110093340 Kramer et al. Apr 2011 A1
20110093498 Lunt et al. Apr 2011 A1
20110099142 Karjalainen et al. Apr 2011 A1
20110106658 Britt May 2011 A1
20110112976 Ryan et al. May 2011 A1
20110128144 Baron, Sr. et al. Jun 2011 A1
20110131172 Herzog et al. Jun 2011 A1
20110151898 Chandra et al. Jun 2011 A1
20110163160 Zini et al. Jul 2011 A1
20110174920 Yoeli Jul 2011 A1
20110181470 Qiu et al. Jul 2011 A1
20110184773 Forstall Jul 2011 A1
20110202426 Cretney et al. Aug 2011 A1
20110219318 Abhyanker Sep 2011 A1
20110231268 Ungos Sep 2011 A1
20110246258 Cragun et al. Oct 2011 A1
20110256895 Palin et al. Oct 2011 A1
20110258028 Satyavolu et al. Oct 2011 A1
20110264692 Kardell Oct 2011 A1
20110291851 Whisenant Dec 2011 A1
20120023196 Grayson et al. Jan 2012 A1
20120047102 Petersen et al. Feb 2012 A1
20120047448 Amidon et al. Feb 2012 A1
20120077523 Roumeliotis et al. Mar 2012 A1
20120084289 Hutheesing Apr 2012 A1
20120096098 Balassanian Apr 2012 A1
20120123667 Guéziec May 2012 A1
20120126974 Phillips et al. May 2012 A1
20120138732 Olm et al. Jun 2012 A1
20120166935 Abhyanker Jun 2012 A1
20120191606 Milne Jul 2012 A1
20120191797 Masonis et al. Jul 2012 A1
20120209775 Milne Aug 2012 A1
20120221470 Lyon Aug 2012 A1
20120224076 Niedermeyer et al. Sep 2012 A1
20120232958 Silbert Sep 2012 A1
20120239483 Yankovich et al. Sep 2012 A1
20120239520 Lee Sep 2012 A1
20120246024 Thomas et al. Sep 2012 A1
20120254774 Patton Oct 2012 A1
20120259688 Kim Oct 2012 A1
20120264447 Rieger, III Oct 2012 A1
20120270567 Johnson Oct 2012 A1
20120278743 Heckman et al. Nov 2012 A1
20120331002 Carrington Dec 2012 A1
20130024108 Grün Jan 2013 A1
20130024114 Oriet Jan 2013 A1
20130041761 Voda Feb 2013 A1
20130041862 Yang et al. Feb 2013 A1
20130054317 Abhyanker Feb 2013 A1
20130055163 Matas et al. Feb 2013 A1
20130068876 Radu Mar 2013 A1
20130072114 Abhyanker Mar 2013 A1
20130073375 Abhyanker Mar 2013 A1
20130073474 Young et al. Mar 2013 A1
20130103437 Nelson Apr 2013 A1
20130105635 Alzu'bi et al. May 2013 A1
20130110396 Choudhury May 2013 A1
20130110631 Mitchell et al. May 2013 A1
20130129075 Whitaker May 2013 A1
20130151455 Odom et al. Jun 2013 A1
20130159127 Myslinski Jun 2013 A1
20130204437 Koselka et al. Aug 2013 A1
20130218455 Clark Aug 2013 A1
20130254670 Eraker et al. Sep 2013 A1
20130282842 Blecon et al. Oct 2013 A1
20130297589 Work et al. Nov 2013 A1
20130301405 Fuste Vilella et al. Nov 2013 A1
20130303197 Chandra et al. Nov 2013 A1
20130317999 Zimberoff et al. Nov 2013 A1
20130334307 Kwong Dec 2013 A1
20140032034 Raptopoulos et al. Jan 2014 A1
20140040079 Smirin Feb 2014 A1
20140040179 Shai Herzog et al. Feb 2014 A1
20140067167 Levien et al. Mar 2014 A1
20140067491 James Mar 2014 A1
20140067704 Abhyanker Mar 2014 A1
20140074736 Carrington Mar 2014 A1
20140081450 Kuehnrich et al. Mar 2014 A1
20140095293 Abhyanker Apr 2014 A1
20140108540 Crawford Apr 2014 A1
20140108613 Randall Apr 2014 A1
20140114866 Abhyanker Apr 2014 A1
20140115671 Abhyanker Apr 2014 A1
20140123246 Abhyanker May 2014 A1
20140129302 Amin May 2014 A1
20140129951 Amin May 2014 A1
20140130140 Abhyanker May 2014 A1
20140135039 Sartipi et al. May 2014 A1
20140136328 Abhyanker May 2014 A1
20140136624 Abhyanker May 2014 A1
20140142848 Chen et al. May 2014 A1
20140143061 Abhyanker May 2014 A1
20140149244 Abhyanker May 2014 A1
20140149508 Middleton et al. May 2014 A1
20140164126 Nicholas et al. Jun 2014 A1
20140165091 Abhyanker Jun 2014 A1
20140172727 Abhyanker Jun 2014 A1
20140204360 Dowski, Jr. et al. Jul 2014 A1
20140207375 Lerenc Jul 2014 A1
20140222908 Park et al. Aug 2014 A1
20140254896 Zhou et al. Sep 2014 A1
20140277834 Levien et al. Sep 2014 A1
20140316243 Niedermeyer Oct 2014 A1
20140365250 Ikeda Dec 2014 A1
20150012320 Juckett Jan 2015 A1
20150142497 Osumi May 2015 A1
20150154810 Tew Jun 2015 A1
20150161533 Kawamoto Jun 2015 A1
20150227871 Zeile Aug 2015 A1
20150294298 Michishita Oct 2015 A1
20150324708 Skipp Nov 2015 A1
20150324945 Lord Nov 2015 A1
20150371157 Jaffe Dec 2015 A1
Foreign Referenced Citations (13)
Number Date Country
1426876 Jun 2004 EP
101069834 Oct 2010 KR
1020120121376 Jul 2012 KR
0219236 Mar 2002 WO
0241115 May 2002 WO
2006020471 Feb 2006 WO
2007113844 Oct 2007 WO
2008105766 Sep 2008 WO
2008108772 Sep 2008 WO
2008118119 Oct 2008 WO
2008111929 Nov 2008 WO
2010103163 Sep 2010 WO
2014121145 Aug 2014 WO
Non-Patent Literature Citations (54)
Entry
“Crowdsourcing: Those that are willing to test & learn will be those that will win”, Newsline, Mar. 1, 2011 by Neil Perkin http://mediatel.co.uk/newsline/2011/03/01/crowdsourcing-those-that-are-willing-to-test-learn-will-be-those-that-will-win/.
Benchmark-Backed Nextdoor Launches As a Private Social Network for Neighborhoods, Techcrunch Article, Oct. 26, 2011 by Leena Rao (6 Pages) http://techcrunch.com/2011/10/26/benchmark-backed-nextdoor-launches-as-a-private-social-network-for-neighborhoods/.
Fatdoor Founder Sues Benchmark Capital, Saying It Stole His Idea for Nextdoor, All Things Digital Article, Nov. 11, 2011, by Liz Gannes (7 Pages) http://allthingsd.com/20111111/fatdoor-founder-sues-benchmark-capital-saying-it-stole-his-idea-for-nextdoor/.
Fatdoor CEO Talks About Balancing Security with Community, Wired Magazine, May 31, 2007, by Terrence Russell (2 Pages) http://www.wired.com/2007/05/fatdoor—ceo—tal/.
Fatdoor Launches Social Network for Your Neighborhood, Mashable Article, May 28, 2007, by Kristen Nicole (3 Pages) http://mashable.com/2007/05/28/fatdoor/.
Screenshots of Nextdoor website and its features—as submitted in Case5:14-cv-02335-BLF on Jul. 15, 2014 (pp. 19) http://www.nextdoor.com/.
Fatdoor turns neighborhoods into online social networks, VentureBeat News Article, May 28, 2007, by Dan Kaplan (pp. 4) http://venturebeat.com/2007/05/28/fatdoor-turns-neighborhoods-into-online-social-networks/.
Halloween Just Got Easier: Nextdoor Debuts Halloween Treat Map, Nextdoor Blog, Oct. 17, 2013, by Anne Dreshfield (pp. 6) http://blog.nextdoor.com/2013/10/17/halloween-just-got-easier-nextdoor-debuts-halloween-treat-map/.
Helping Neighbors Connect, Screenshot from FrontPorchForum website—screenshots of Aug. 21, 2014 (3 Pages) http://frontporchforum.com/.
Advocacy Strategy for the Age of Connectivity, Netcentric Advocacy: fatdoor.com (alpha), Jun. 23, 2007 (p. 1) http://www.nework-centricadvocacy.net/2007/06/fatdoorcom-alph.html.
Silicon Valley venture capital and legal globalization Blog, WayBack Machine Blogs Apr. 8, 2008, by Raj V. Abhyanker (pp. 2) https://web.archive.org/web/20080706001509/http:/abhyanker.blogspot.com/.
Frontporchforum. screenshots. Jul. 19, 2006 webarchive.org 1-15 (herein FrontPorch) (pp. 15).
Fatdoor where 2.0 Launch Coverage Report, Jun. 21, 2007, by Sterling Communications (pp. 24).
Screenshot of Fatdoor on Wikipedia, Apr. 12, 2007 (p. 1).
Case No. 5-14-cv-02335-BLF Complaint Fatdoor v. Nextdoor, Northern District of California, with Exhibits A, B and C {Part 1 (pp. 258)} and Exhibits D, E, F, G and H {Part 2 (pp. 222)}, Jul. 15, 2014.
Expert Report—Forensics of Jon Berryhill, Report, Nextdoor v. Abhyanker, Aug. 8, 2014, by Berryhill Computer forensics Inc. (pp. 23).
Case No. 3:12-cv-05667-EMC Complaint Nextdoor v. Abhyanker, Northern District of California, Nov. 5, 2012 (pp. 46).
Expert Report—Patent of Jeffrey G. Sheldon, Nextdoor v. Abhyanker, Aug. 8, 2014 (pp. 7).
Exhibits of Expert Report—Patent of Jeffrey G. Sheldon, Nextdoor v. Abhyanker, with Attachments A, B, C, D and E (1/2) {Part 1 (pp. 46)} and Attachments E (2/2) and F {Part 2 (pp. 41)}.
Case No. 111-CV-212924 Abhyanker v. Benchmark Capital Partners L.P., Superior Court of California, County of Santa Clara, Nov. 10, 2011 (pp. 78) http://www.scribd.com/doc/72441873/Stamped-COMPLAINT-Abhyanker-v-Benchmark-Capital-Et-Al-FILED-PUBLIC.
Neighbors Stop Diaper and Formula Thief in his Tracks, Nextdoor Blog, Aug. 15, 2014, by Anne Dreshfield (pp. 12) http://blog.nextdoor.com/.
Screenshot of Fatdoor website with its features—Aug. 21, 2014 (pp. 6) http://www.fatdoor.com/.
Screenshot of AirBnB website with its features—Aug. 21, 2014 (pp. 4) http://www.airbnb.com/.
Wikipedia entry AirBnB website—Aug. 21, 2014 (pp. 16) http://en.wikipedia.org/wiki/Airbnb.
AirBed&Breakfast for Connecting '07—Oct. 10, 2007 (1 Page) http://www.core77.com/blog/events/airbed—breakfast—for—connecting—07—7715.asp.
Case No. 5:14-cv-03844-PSG, Complaint Fatdoor, Inc. v. IP Analytics LLC and Google Inc.,Northern District of California, Aug. 25, 2014, (pp. 16).
Screenshot of Meetey on CrunchBase, Aug. 27, 2014, (pp. 3) http://www.crunchbase.com/organization/meetey.
Wikipedia entry Patch Media website—Aug. 27, 2014 (pp. 2) http://en.wikipedia.org/wiki/Patch—Media.
Wikipedia entry Yahoo! Groups website—Aug. 27, 2014 (pp. 7) http://en.wikipedia.org/wiki/Yahoo—groups.
Palo Alto News on Topix, Aug. 27, 2014, (pp. 3) http://www.topix.com/palo-alto.
Screenshot of My Neighbourhoods on CrunchBase, Aug. 27, 2014 (pp. 2) http://www.crunchbase.com/organization/my-neighbourhoods.
Screenshot of Dehood website, Aug. 27, 2014, (p. 1) http://www.dehood.com/home.
Wikipedia entry The Freecycle Network website—Aug. 27, 2014 (pp. 3) http://en.wikipedia.org/wiki/The—Freecycle—Network.
eDirectree Brings Group Wiki Twist to Social Networking, Techcrunch Article, Feb. 1, 2008 by Mark Hendrickson, (pp. 2) http://techcrunch.com/2008/02/01/edirectree-brings-group-wiki-twist-to-social-networking/.
Wikipedia entry Meetup website—Aug. 27, 2014 (p. 1) http://en.wikipedia.org/wiki/Meetup—(website).
Wikipedia entry Google Maps website—Aug. 27, 2014 (p. 18) http://en.wikipedia.org/wiki/Google—Maps.
Screenshot of Facebook website for groups, Aug. 27, 2014, (p. 1) https://www.facebook.com/about/groups.
Facebook Engineers bring Google+ Circles to Facebook, Article on ZDNet by Emil Protalinski, Jul. 3, 2011, (pp. 2) http://www.zdnet.com/blog/facebook/facebook-engineers-bring-google-circles-to-facebook/1885.
Screenshot of Uber website, Aug. 27, 2014, (pp. 5) https://www.uber.com/.
Screenshot of Lyft website, Aug. 27, 2014, (pp. 5) https://www.lyft.com/.
Wikipedia entry Google driverless car—Aug. 27, 2014 (pp. 4) http://en.wikipedia.org/wiki/Google—driverless—car.
Wikipedia entry Uber (company)—Aug. 27, 2014 (pp. 7) http://en.wikipedia.org/wiki/Uber—(company).
Wikipedia entry Autonomous car—Aug. 27, 2014 (pp. 15) http://en.wikipedia.org/wiki/Autonomous—car.
Screenshot of sidecar website, Aug. 27, 2014 (p. 1) http://www.sidecar.com/.
Screenshot of patch media website, Aug. 27, 2014 (pp. 6) http://patch.com/.
Screenshot of i-neighbors website, Aug. 27, 2014 (pp. 3) https://www.i-neighbors.org/howitworks.php.
“Friends and Neighbors on the Web”, 2001 by Lada A. Adamic et al. (pp. 9) http://www.hpl.hp.com/research/idl/papers/web10/fnn2.pdf.
“A social influence model of consumer participation in network- and small-group-based virtual communities”, International Journal of Research in Marketing, 2004 by Utpal M, Dholakia et al. (pp. 23) http://www-bcf.usc.edu/˜douglast/620/bettina1.pdf.
“BuzzMaps: a prototype social proxy for predictive utility”, ACM Digital Library, 2003 by Azzari Caillier Jarrett et al. (Pages) http://dl.acm.org/citation.cfm?id=948547&dl=ACM&coll=DL&CFID=456946313&CFTOKEN=50139062.
“Direct Annotation: A Drag-and-Drop Strategy for Labeling Photos”, University of Maryland, 2000 by Ben Shneiderman et al. (pp. 8) http://hcil2.cs.umd.edu/trs/2000-06/2000-06.pdf.
“Notification for Shared Annotation of Digital Documents”, Technical Report MSR—TR-2001-87, Sep. 19, 2001 by A. J. Bernheim Brush et al. (pp. 9) http://research.microsoft.com/pubs/69880/tr-2001-87.pdf.
“HT06, Tagging Paper, Taxonomy, Flickr, Academic Article, ToRead”, Yahoo Research Berkeley, CA, 2006 by Cameron Marlow et al. (pp. 9) http://www.danah.org/papers/Hypertext2006.pdf.
“Computer Systems and the Design of Organizational Interaction”, by Fernando Flores et al. (pp. 20) http://cpe.njit.edu/dlnotes/CIS/CIS735/ComputerSystemsandDesign.pdf.
“ChipIn—the easy way to collect money”, Louis' Really Useful Finds, Mar. 12. (p. 1) http://reallyusefulthings.tumblr.com/post/28688782/chipin-the-easy-way-to-collect-money.
Related Publications (1)
Number Date Country
20150369621 A1 Dec 2015 US