Adaptive direct transaction for network client group

Abstract
Internet-based software and associated database provide group analysis overlay to monitor client-server web traffic and provide direct marketing to client group. Client car, patient, office or school sensor and interface provides overlay attribute for database comparison to classify usage pattern, location, timing, or family for targeted messaging for enhanced service from server source. Database group registry tracks client classification and provides adaptive context mapping according to set attribute relative to targeted on-line transaction.
Description
FIELD OF INVENTION

Invention relates to networked computer applications, particularly to distributed client-server software for adaptive direct group transaction.


BACKGROUND OF INVENTION

With the explosive growth of the Internet and its associated World-Wide Web, various computer programs have been developed for distributed applications between client and server processors interconnected through local and/or wide area networks. In particular, web-based software are provided variously for promoting, managing or otherwise transacting business on-line. Thus, such electronic commerce applications are provided to facilitate more efficient marketing and distribution of goods and services. However, prior-art approaches at facilitating on-line commerce are limited, particularly with respect to enabling direct marketing, especially for multiple targets or client groups.


SUMMARY OF INVENTION

Invention resides in software for directing on-line messages to classified client set adaptively according to monitored set characteristics. Memory stores set data associated with historically stored, currently measured, or preferred network configuration, on-line traffic, location, schedule, or affiliation. Clients are classified into sets per criteria for contextual mapping of particular sets to corresponding targeted on-line messages. Client sensor interface provides mobile location, medical condition, or other attribute for adaptive classification of client into sets by comparing attribute to set groupings. Updated client classification provides adaptive context mapping of sets to directed transactions.





BRIEF DESCRIPTION OF DRAWINGS


FIG. 1 is general block diagram for network system implementing present invention.



FIG. 2 is logic flow diagram of operational methodology for implementing present invention.



FIG. 3 is database diagram according to present invention.



FIG. 4 is block diagram of client interface according to present invention.



FIG. 5 is flow chart of operational steps for group analysis overlay according to present invention.



FIG. 6 is flow chart of operational steps for network download dynamic display according to present invention.



FIG. 7 is flow chart of operational steps for directed offering transaction according to present invention.





DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS


FIG. 1 block diagram shows network system 4 having one or more server processors or nodes 2 and one or more client processors or nodes 10, 20, 30, coupled thereto preferably according to standard Internet Protocol or other conventional digital networking and data communications scheme, which publicly available specifications are hereby referenced, as appropriate.


Preferably, client 10 represents network interface for vehicular or other mobile processing application, client 20 represents network interface for medical or other personal processing application, and client 30 represents network interface for appliance or other embedded processing application.


It is contemplated herein that network 4 may be embodied in conventional and/or proprietary, wired and/or wireless, hardware and/or software, integrated and/or modular means for sending and receiving digital data and/or electronic signals between processors, nodes or other addressable network sites coupled thereto. Moreover, it is contemplated that server or client processing functionality may be embodied in one or more processing machines or devices, and a single processing machine or device may perform functionality of multiple server and/or client processors.



FIG. 2 flow chart shows process for network configuration and resource control 40, client interface and secure access 50, operational processing and sensing 60, network download and dynamic display 70, group analysis overlay 80, directed offering and transaction 90, and database access 100.


In accordance with present invention, network 4, including server(s) 2 and client(s) 10, 20, 30 employ software and/or other functionally equivalent firmware, hardware, or electronics for directing or targeting on-line messages or electronic signals to selected or classified client set or group adaptively or dynamically according to monitored or specified set characteristics or attributes. Preferably, such software functionality is implemented using embedded or real-time operating (RTOS) code convention, JAVA, C/C++, Windows/CE, or other equivalent digital signal processing instruction scheme, according to operational definition described herein.


Such software or functionality may use or cooperate for read/write operations with one or more digital memory or functionally equivalent network-accessible electronic storage to store data or attribute signals about one or more client 10, 20, 30 associated with previously stored, currently measured, or preferred network or node configuration, on-line network traffic, actual location, schedule events, or subscribed or qualified affiliation.


Preferably, clients 10, 20, 30 are classified into or otherwise associated with sets, super-sets, sub-sets, groups, super-groups, sub-groups, or other hierarchical category according to pre-specified or dynamically defined criteria for qualification therein. Particular set or sets may be logically mapped, assigned contextually or otherwise related to one or more corresponding targeted on-line message or electronic network signals, as described herein. In particular, client sensor interface may provide various monitored still images, live video, audio, states, data or attribute signals representative thereof, such as mobile location, medical condition, or other detectable attribute for adaptive or responsive classification of subject client into set(s) by comparing attribute and classifying appropriately into set groupings. For example, sensor may include one or more keyboard, screen or mouse entry, microphone, digital imaging or video camera, or position locator or navigational electronics, such as Global Positioning Satellite system (GPS) receiver functionality to provide certain dimensional and temporal (i.e., time and place) signals and values.


Additionally, client interface user interface is preferably implemented as dial-up or dedicated network connection web browser software, which provides secured access according to authenticated and/or encrypted user identification or messages. Optionally, user identification may be achieved by client interface determination of unique user physical or biological characteristic, such as sensor-sampled or input-verified personal genetic sequence.


Moreover, updated or modified client classifications effectively provide adaptive or dynamic context mapping of sets to directed transactions, messages, or signals representative thereof. For example, directed message, transaction or network signal may include commercial offering, application program, still image, or video stream.


Hence, during software operation of preferred implementation, one or more client attribute or signal is determined or generated initially, so that subject client may be classified in a set according to subject attribute (i.e., currently monitored or generated attribute signal); then, a message or transaction signal representative thereof is sent to clients classified in that set. Generally, subject attribute or generated signal may represent one or more monitored signals, data, or values, such as client location, elapsed or actual time, client or user entry selection, physical, mechanical, medical or other objective condition, as well as any affiliation or subscription associated with subject client.


More particularly, subject attribute value or signal may be provided by one or more client sensor, wherein such attribute is provided in digital memory or functionally equivalent electronic storage. Client may be classified by comparing the attribute with another attribute stored in memory to determine equivalence or non-equivalence, such that client is classified or not classified in the set, for example, according to pre-determined substantial similarity determined therebetween.


Additionally, a second attribute of the client may be determined, wherein the client then may be classified in another or same set according to the second attribute. Another or same message or transaction signal may be sent to one or more clients classified in the second set. Moreover, a second attribute may be determined for another client, wherein such other client is classified in the second set according to the second attribute, and a second message or transaction signal is thereby sent to clients classified in the second set.



FIG. 3 diagram represents database 100 of base server(s) 102, user client(s) 104, traffic operations 106, and group registry 108, which are one or more separately or collectively stored or accessible object-oriented and/or relational information modules or other networking or processing system cache or repositories, value or signals representative of functional activity associated respectively with one or more servers 2, client interfaces 10, 2030, network 4 communications and configurations, and client set groupings, as described herein.


In particular, base server data module 102 includes electronically-accessible expert, service catalog, knowledge library, or other on-line or user self-service resource pool; and network-downloadable text, audio, still images, video clips or streams; or any update or revision thereof. User client or sensor site module 104 includes network client or server connection and configuration; client and/or group identifier or reference indicator; network usage or transaction history or pattern; monitored or sensed client attributes (e.g., time, location, temperature, available resources, etc.); client sensor configuration, status and condition, or client specified or inferred preferences.


Traffic operations or network manager module 106 includes client or sensor sites set-up sequence, configuration or log; security or authentication sequence, configuration or log; data transfer or signal transmission download or communication sequence, configuration or log; offering transaction sequence, configuration or log; and network operation or performance monitor or log. Client or user group or set registry module 108 includes group or set search interface sequence, configuration or log; user or client attribute tracking or monitoring; group or set classifications or criteria; or context mapping or other directed message association.



FIG. 4 diagram shows client or site interface 10, 20, 30, including interface; coupling or application, controller or embedded processor; storage, cache or memory; and one or more network-accessible sensors. Such included client functionality may be provided in one or more integrated, programmable, reconfigurable, electronic devices, circuit, firmware, software and/or other equivalent implementation. Preferably controller 14 is implemented as programmed embedded digital signal processor, microprocessor, or reduced instruction set computing (RISC) microcontroller, such as commercial parts: 43001 from NEC Electronics (Santa Clara, Calif.), 4640/4650 from Integrated Device Technology (Santa Clara, Calif.), R5000/R8000/10000 from MIPS Technology (Mountain View, Calif.), PPC603/604 from IBM Microelectronics (Hopewell Junction, N.Y.) and Motorola (Austin, Tex.), 486DX4/486DX5 from Advanced Micro Devices (Austin, Tex.), PentiumPro/PentiumII from Intel (Chandler, Ariz.), UltraSPARC II/III from Sun Microsystems (Mountain View, Calif.), or Alpha 21164/21264 from Digital Equipment (Maynard, Mass.).


Generally, present embodiment may be implemented and/or performed using any digital local or wide-area network 4 wherein one or more addressable nodes (i.e., client and/or server) are coupled thereto for communication or transmission of packets, cells, frames, signals, or other electronic messages therebetween. Preferred network uses so-called Internet convention and World-Wide Web networking protocol for sending files, for example, according to specified formats, such as hypertext file transfer protocol (HTTP), universal resource locator (URL), hypertext markup language (HTML), extensible markup language (XML), transmission control protocol/Internet protocol (TCP/IP), etc. Thus, in this network arrangement, one or more servers and/or clients may remotely or locally access one or more servers coupled directly or indirectly thereto.


Initially, for functional operation of present embodiment, one or more client interface 10, 20, 30 is coupled to network 4, and such network is configured 40 wherein one or more informational expertise or data signal resources, such as provided centrally or distributedly by one or more modules 102, 104, 106, 108 in database 100.


For example, during or after initial set-up, resource pool in base server 102 may specify one or more expertise repositories or catalogs which may provide client-requested or downloadable text, audio, video, or other digital data. Moreover, during or after initial set-up, user client database 104 may be updated to indicate network connectivity and configuration between any servers and/or clients coupled thereto, as well as connectivity and configuration of any sensor or equivalent devices associated with one or more such clients. Furthermore, during or after initial set-up, user client database 104 may indicate one or more user-preferred network configuration, transaction selection, or sensor-related attribute. Additionally, during or after initial set-up, traffic operations module 106 may indicate client setup, network configuration, and security access parameters. In addition, during or after initial set-up, group registry module 108 may indicate client tracking state and client classification or grouping.


Preferably, one or more client interfaces 10, 20, 30 are configured and coupled in accordance with secure access channel and protocol 50 to network 4 to provide selectable access to one or more sensor 18 associated with particular client. Depending on client interface type, application or specific embodiment, for example, client interface 10 may serve as network interface for non-fixed pedestrian, vehicular or other moving processing site; client interface 20 may serve as network interface for personal, patient, medical or other tele-medicine computing or communications environment; or client interface 30 may serve as network interface for multimedia equipment, residential appliance, office processing equipment, or other embedded controller or local processing application.


Hence, when client-server network is configured 40 for controlling expert resource or database access, and various client interface and sensors are coupled and accessible securely 50 thereto, then one or more applications programs may execute, preferably according to client and corresponding sensor implementation type, according to present invention to enable effectively adaptive direct transaction or messaging for one or more networked client group.


Sensor input signals from one or more client sites may be received continuously, scheduled at regular times, triggered by specified alarms or conditions, selectably activated by client or server, or adaptively or proportionately increased or decreased in sensing activity according to pre-specified or associated attributes, current related activity, or specified or monitored client group or set conditions or monitored activity.


In embodiment case of vehicle client interface 10, operational processing and sensing uses one or more microprocessor or embedded controller 14 electronically to monitor, diagnose and/or control data signals, alarm or out-of-specified range condition, pre-specified states, or other objectively detectable or attributes. Preferably, such sensed signal monitoring process is achieved using one or more local or embedded processing programs or applications provided in storage 16 executable by controller 14 for real-time access of one or more sensors or other signal feedback detector coupled thereto, such as temperature, pressure, accelerometer or movement sensors, (such as commercial integrated silicon or micromachined parts: AD741X and AD781X temperature sensors from Analog Devices (Norwood, Mass.), LM80, LM56, LM75 thermal sensors from National Semiconductor (Santa Clara, Calif.), XTR106 pressure sensors from Burr-Brown (Tucson, Ariz.), MPX10/50/100/2010/210d0/2700/5010/5006/5100/5700 pressure sensors from Motorola (Phoenix, Ariz.), or 7257AT accelerometer sensor from Endevco (San Juan Capistrano, Calif.), 40PC/4000PC pressure sensor from Honeywell (Freeport, Ill.), 19(C,U)005G pressure sensor from Sensym (Milpitas, Calif.), Titan pressure sensor from Lucas Control Systems (Hampton, Va.), DMU Turbo accelerometer sensor from Crossbow Technology (San Jose, Calif.), or MAP1452/XKP1260 pressure transducers from Integrated Sensor Solutions (San Jose, Calif.)).


It is contemplated that such client sensors 18 may be implemented in automotive, trucking or other terrestrial, airborne and/or marine transport systems or subsystems, such as mechanical (e.g., internal combustion engine timing, mechanical linkage stress or strain, transmission, and related drive train monitor, vehicle braking or brake anti-locking, fuel delivery and storage, passenger restraint, emergency condition, seatbelt securement or airbag deployment, or impact detection, diagnosis and/or control thereof), and/or electrical (e.g., engine ignition, lighting, thermal cooling/heating, entertainment, communication, dispatching, or navigational appliance or device, and/or other electronic module monitor, diagnosis and/or control thereof), etc.


In embodiment case of personal or patient client interface 20, operational processing and sensing uses one or more microprocessor or embedded controller 14 electronically to monitor, diagnose and/or control data signals, alarm or out-of-specified range condition, pre-specified states, or other objectively detectable or attributes through one or more sensors or other signal feedback detector, as described herein. Preferably, such sensed signal monitoring process is achieved using one or more local or embedded processing programs or applications provided in storage 16 and executable by controller 14 for real-time access of one or more sensors or other signal feedback detector coupled thereto.


It is contemplated that such client sensors 18 may be implemented in remote clinical, biometric, ambulatory medical, consultation, monitoring or communications systems or subsystems, particularly record-forwarding, patient-communication and observation, patient vital measurements, radiograph and other diagnostic image-transmission, for various specialties, such as radiology, dental, cardiorespiratory, constitutional, dermatology, ear-nose-throat, gastrointestinal, genitourinary, gynecological, musculoskeletal, neuropsychiatric, etc.


Optionally, sensors 18 may serve to detect or identify client-provided or specified organic material, particularly by obtaining probed or receiving analyzed input of one or more genetic sequence data of deoxyribonucleic acid (DNA) or protein of subject client, for example, for subsequent database alignment and/or comparison for similarity or matching against known identifiable sequences.


In embodiment case of office, home or school appliance client interface 30, operational processing and sensing uses one or more microprocessor or embedded controller 14 electronically to monitor, diagnose and/or control data signals, alarm or out-of-specified range condition, pre-specified states, or other objectively detectable or attributes through one or more sensors or other signal feedback detector, as described herein. Preferably, such sensed signal monitoring process is achieved using one or more local or embedded processing programs or applications provided in storage 16 and executable by controller 14 for real-time access of one or more sensors or other signal feedback detector coupled thereto.


It is contemplated that such client sensors 18 may be implemented for accessing, communicating with, monitoring, and controlling operations in multimedia entertainment, home or small office automation equipment, residential appliance devices, systems or subsystems, such as digital video disk players or recorders, personal computers, printers, copiers, fax machines, digital television, set-top boxes, security monitoring and alarm, etc.


Preferably, such electronic sensor-implementing components employ controller 14 processing code to interface to network 4 for sensor and interface access, signaling and control according to communication or signaling protocol, such as universal serial bus (USB), IEEE 1394 (i.e., FireWire), or other similar comparable interface specification. For example, such preferred interface for client appliance interface 30 complies with home audio/video interoperability (HAVI) architecture, which published specification is hereby incorporated by reference.


According to application program execution during operational processing and sensing 60, as described herein, client or user input and/or output (I/O) interface is provided, particularly to deliver signal or data download from network using dynamic display mechanism 70. Informational download, such as text (e.g., ASCII or Word processor format), audio (e.g., Real Audio format), still image (e.g., joint picture experts group (JPEG), 2 or 3 dimensional format), video (e.g., moving picture experts group (MPEG), or other catalog, expertise data pool, resource files or electronic digital material, are accessed from database 100 modules 102, 104, 106, 108. Optionally, such network client interface includes web browser software, such as available commercially from Microsoft (e.g., Internet Explorer) or Netscape (e.g., Communicator/Navigator).



FIG. 6 flow chart shows group download display embodiment, wherein one or more servers initially setup to determine one or more clients associated with or belonging to specified sets or groups, thereby updating database client grouping 104, database registry client tracking 108, as well as any database traffic operation client setup and network configuration 106.


In particular, such determining server(s) may create and maintain current group or task manager, preferably as data table or system process to identify and monitor communications with or other network download to specified group members. Thus, based on initial client-server parameter setup, as well as subsequent updates thereto, accessing such task manager may provide effectively real-time organization of multi-member grouping data, and facilitates relatively fast informative response to authorized client or server query to determine current group definitions and members actively categorized therein. Additionally, such task manager program may serve to balance processing between group members, for example, such that directed messages or other transaction offerings are delivered more frequently or earlier to less-busy or higher-processing capacity client sites, as indicated in current database 100.


Further, display downloading scheme 70 includes faster-memory caching 74 of relatively larger data files, such as still image (e.g., .GIF, .JPG) and compressed video (e.g., MPG) files from database module download library 102. In addition, display downloading may include feedback signaling or equivalent communication 76 from one or more subject clients, which belong to common group client members, to provide accelerated current group membership indication to like group members. In this feedback-loop manner, group members may relatively quickly be alerted and display appropriate membership or non-membership status.


Preferably, network download dynamic display operations 70 provide subject server or client relatively high-resolution, flat-panel screen output with interactive multi-media capability (i.e., text, audio, still image, video, 3-D graphic or virtual media format, etc.), for example, using personal computer equipment or engineering workstation with processing encoded and compressed media signals, or interactive digital television having network-ready Internet or equivalent communications interface and applications protocol. Optionally, particular client may select to screen, block, filter or exclude from receiving one or more classes or attributes of incoming directed messages, such as undesirable commercial or immoral content.



FIG. 5 flow chart shows operational steps for group analysis or system overlay thereof, according to important aspect of present invention, generally wherein Internet-based client interface 10, 20, 30 and associated database 100 effectively provide group analysis processing to monitor client-server web traffic and deliver direct marketing services to client group. As per alternative instances described herein, client car, patient, office or school sensors and interfaces provide attribute processing system overlay for database comparison to classify usage pattern, location, timing, or family for targeted messaging for enhanced service from server source. Database 100 group registry tracks client classification and provides adaptive context mapping according to set attribute relative to targeted on-line transaction.


Generally, group analysis 80 may be invoked automatically upon schedule or per directed request, thereby operating to determine groupings by comparing sensed 60 operational values with associated values stored in database 100. When group analysis 80 and subsequent directed offering transaction operations 90 are so invoked, for example, by network client or server with proper requesting authorization, preferably, one or more candidate client sites 10, 20, 30 are identified accordingly for classification. For example, in case of vehicle client interface 10, one or more clients having certain sensed or specified characteristics or other attributes, such as having certain serial or model numbers, tracked geographic location, etc., may be designated as candidate sites when considered for possible vehicle or product defect, repair, upgrade, or recall.


Initially, to perform proper group analysis, subject server 2 (or other network processor with access to database 100 and one or more candidate clients for present comparison) examines database 100, which may be implemented in one or more network-accessible data repositories, to determine 82 existence of any specified supergroups, groups, subgroups, in present network, and particularly search database modules 104, 108 recognize any such grouping which includes client to be evaluated for membership. Moreover, such subject server 2 may further search such database modules 104, 108 to determine and monitor existence of any or each sensor and characteristics thereof associated with each subject client for evaluation.


Then, database compare and set classify operations 84 are performed by subject server 2, whereby representative attributes or other sensed characteristics of candidate client(s) are logically compared to equivalent data field representations of other pre-registered or tracked clients in database 100 to determine matching or recognize substantial qualification for set groupings or non-groupings. Group registry 108 provides functional or graphical interface for searching fields for client and sensor attributes.


For example, in case of patient client interface 20, candidate patient sensed or specified attributes, such as geographical location, demographic family, race or ethnicity, medical insurance coverage, age, sex, etc. may be compared against other clients to generate certain groupings for subsequent targeted messaging or commercial offerings. Similarly, in case of appliance client interface 30, candidate appliance sensed or specified attributes, such as appliance model number, multimedia play-back capacity, entertainment preferences, usage pattern, budget allowance, schedule availability, etc. may be compared against other client to generate certain groupings. Upon candidate grouping classification, database 100 modules 104, 108 may be updated to reflect client membership accordingly.


Optionally, to provide network system client grouping scalability, when candidate client is determined not to be classifiable as analyzed, subject server 2 may modify group registry 108 to define set changes and create new super-group, group, or sub-group, as required by subject server.


Preferably, database registry 108 provides group classification with corresponding context mapping or topic relevance matching, thereby enabling directed matching for adaptive messages 86. Although such context mapping may be applied in case-specific manner, wherein specific rules or requirements for defining groups or clients having certain specified or sensed attributes are designated to receive targeted message broadcast, preferably, such context mapping may be achieved using less precise qualification scheme, such as fuzzy or statistical logical or topical association to generate list of possible candidates for targeted messaging. Upon completion of such context mapping, group registry 108 is updated. Additionally, context mapping scheme may be adapted to focus target candidates or reduce such directed client list for more precise marketing effect, preferably in response to real-time specified or sensed group or client attributes.



FIG. 7 flow chart shows directed offering transaction operation 90, wherein subject server 2 (or alternate network processor) generates and/or sources one or more directed or targeted message, which may include commercial, promotional, or marketing symbol, audio, text, still image, video, or other media content or signal for context-mapped or other designated clients within specified grouping(s). In particular, such directed messages may be downloaded from module 102, or other network source, and transmitted 92 through network 4 to designated client sites according to database 100 user client and grouping configurations and network connections specified in module 104, whereupon database 100 traffic operations module 106 is appropriately updated or reconfigured to reflect completed messaging.


Optionally, such directed messaging may be invoked by subject server 2 in response to one or more network searches or queries 92, for example, from other authorized server or client, or network search agent software application or process thereof, accessing group registry module 108 search interface to locate or identify one or more target groupings or clients therein, which qualify under certain specified or sensed attributes. Directed transactional messages 70 may be sent to targeted grouping(s), as well as client members therein, for prompt network download and display 70.


Furthermore, in auction style or similar bidding procedure, one or more such searching or querying network nodes or sources, or client members in particular grouping, may be designated or qualified to participate in on-line bidding or auction transaction, whereby highest price or other parameter bidder is provided specified merit rights or transaction.


In addition, when one or more such searching or querying network node or sources, or client members in particular grouping, is so designated or qualified, customized commercial terms, for example, for transacting so-called micro-sale or comparable limited per-use service billing 96 may be charged to such on-line customer according to actual network distribution or execution of transacted application service. In such micro-sale transaction, subject server 2 may prioritize access or directed messaging resources to targeted clients to achieve group balancing, whereby network computing performance, database resource access, and/or application or other service delivery are optimized.


Foregoing described embodiments of the invention are provided as illustrations and descriptions. They are not intended to limit the invention to precise form described. In particular, Applicants contemplate that functional implementation of invention described herein may be implemented equivalently in hardware, software, firmware, and/or other available functional components or building blocks. Other variations and embodiments are possible in light of above teachings, and it is thus intended that the scope of invention not be limited by this Detailed Description, but rather by Claims following.

Claims
  • 1. Adaptive direct transaction telemedicine system for network client group comprising: a server coupled to a vehicle client interface, a patient client interface and an appliance client interface;wherein at least one such vehicle, patient and appliance client comprises an interactive digital television controller, a storage and a sensor sampling a personal genetic sequence of DNA or protein, the server adaptively causing an expert knowledge library to be accessed electronically via network-ready communications interface for one or more interactive digital television associated with one or more client interface by enabling local or remote network transmission of one or more telemedicine video stream including clinical, biometric, ambulatory, medical, consultation, or monitoring diagnosis provided to one or more such interactive digital televisions from a database pool of expert videos modified automatically by the server to diagnose one or more client according to unique personal DNA sequence, such client being enabled to access telemedicine video stream comprising expert clinical, biometric, ambulatory, medical, consultation, or monitoring diagnosis of said unique personal DNA sequence and thereby enable automated medical or patient remote or local contextually-mapped telemedicine services including genetically personalized health care video streaming automated to adapt particularly to client unique personal DNA sequence by customizing client diagnostic telemedicine video stream services comprising personalized client record-forwarding, patient-communication and observation, patient vital measurements, or radiograph and diagnostic image-transmission, such adaptively modified telemedicine video stream being automatically customized for radiology, dental, cardiorespiratory, constitutional, dermatology, ear-nose-throat, gastrointestinal, genitourinary, gynecological, musculoskeletal or neuropsychiatric diagnosis via interactive digital television telemedicine video streaming adaptively modified according to unique personal DNA sequence.
  • 2. System of claim 1 wherein the server enables network configuration and resource control, client interface and secure access, operational processing and sensing, group analysis overlay, direct offering transaction, and network download and dynamic display.
  • 3. System of claim 1 wherein the server accesses a database comprising base server including resource pool and download library for video streams, still images and catalog update; user clients including network connect, ID/grouping, usage pattern, time/location, sensor configuration and preferences; traffic operations including client setup, network configuration, security access, downloads, transactions and performance monitor; and group registry including search interface, client tracking, classifications, set changes and context mapping.
  • 4. Adaptive direct transaction telemedicine method for network client group comprising step: coupling a server to a vehicle client interface, a patient client interface and an appliance client interface;wherein at least one such vehicle, patient and appliance client comprises an interactive digital television controller, a storage and a sensor sampling a personal genetic sequence of DNA or protein, the server adaptively causing an expert knowledge library to be accessed electronically via network-ready communications interface for one or more interactive digital television associated with one or more client interface by enabling local or remote network transmission of one or more telemedicine video stream including clinical, biometric, ambulatory, medical, consultation, or monitoring diagnosis provided to one or more such interactive digital televisions from a database pool of expert videos modified automatically by the server to diagnose one or more client according to unique personal DNA sequence, such client being enabled to access telemedicine video stream comprising expert clinical, biometric, ambulatory, medical, consultation, or monitoring diagnosis of said unique personal DNA sequence and thereby enable automated medical or patient remote or local contextually-mapped telemedicine services including genetically personalized health care video streaming automated to adapt particularly to client unique personal DNA sequence by customizing client diagnostic telemedicine video stream services comprising personalized client record-forwarding, patient-communication and observation, patient vital measurements, or radiograph and diagnostic image-transmission, such adaptively modified telemedicine video stream being automatically customized for radiology, dental, cardiorespiratory, constitutional, dermatology, ear-nose-throat, gastrointestinal, genitourinary, gynecological, musculoskeletal or neuropsychiatric diagnosis via interactive digital television telemedicine video streaming adaptively modified according to unique personal DNA sequence.
  • 5. Method of claim 4 wherein the server enables network configuration and resource control, client interface and secure access, operational processing and sensing, group analysis overlay, direct offering transaction, and network download and dynamic display.
  • 6. Method of claim 4 wherein the server accesses a database comprising base server including resource pool and download library for video streams, still images and catalog update; user clients including network connect, ID/grouping, usage pattern, time/location, sensor configuration and preferences; traffic operations including client setup, network configuration, security access, downloads, transactions and performance monitor; and group registry including search interface, client tracking, classifications, set changes and context mapping.
CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation application of U.S. patent application Ser. No. 12/239,593 originally filed on Sep. 26, 2008, which is a continuation application of U.S. patent application Ser. No. 09/145,167 originally filed on Sep. 1, 1998.

US Referenced Citations (264)
Number Name Date Kind
3568161 Knickel Mar 1971 A
3683114 Eqan et al. Aug 1972 A
3828306 Angeloni Aug 1974 A
3914692 Seaborn, Jr. Oct 1975 A
3980948 Olive Sep 1976 A
3986119 Hemmer, Jr. et al. Oct 1976 A
4002983 Kavlir et al. Jan 1977 A
4067411 Conley et al. Jan 1978 A
4084241 Tsumura Apr 1978 A
4139889 Ingels Feb 1979 A
4162377 Mearns Jul 1979 A
4229620 Schaible Oct 1980 A
4369426 Merkel Jan 1983 A
4616214 Naito Oct 1986 A
4687732 Ward et al. Aug 1987 A
4707926 Decker, Jr. Nov 1987 A
4710955 Kauffman Dec 1987 A
4755872 Bestler et al. Jul 1988 A
4757267 Riskin Jul 1988 A
4763418 Decker, Jr. Aug 1988 A
4833477 Tendler May 1989 A
4891650 Sheffer Jan 1990 A
4965821 Bishop et al. Oct 1990 A
4982346 Girouard et al. Jan 1991 A
5003584 Benyacar et al. Mar 1991 A
5043736 Darnell et al. Aug 1991 A
5119102 Barnard Jun 1992 A
5131020 Liebesny et al. Jul 1992 A
5159315 Schultz et al. Oct 1992 A
5196846 Brockelsby et al. Mar 1993 A
5208706 Lemelson May 1993 A
5208756 Song May 1993 A
5218367 Sheffer et al. Jun 1993 A
5223844 Mansell et al. Jun 1993 A
5225842 Brown et al. Jul 1993 A
5272483 Kato Dec 1993 A
5278568 Enqe et al. Jan 1994 A
5283829 Anderson Feb 1994 A
5296963 Murakami et al. Mar 1994 A
5319363 Welch et al. Jun 1994 A
5323322 Mueller et al. Jun 1994 A
5327144 Stilp et al. Jul 1994 A
5334974 Simms et al. Aug 1994 A
5335140 Kamino et al. Aug 1994 A
5341140 Perry Aug 1994 A
5343493 Karimullah Aug 1994 A
5365451 Wang et al. Nov 1994 A
5388147 Grimes Feb 1995 A
5390238 Kirk et al. Feb 1995 A
5396227 Carroll et al. Mar 1995 A
5398190 Wortham Mar 1995 A
5400018 Scholl et al. Mar 1995 A
5416695 Stutman et al. May 1995 A
5418526 Crawford May 1995 A
5418538 Lau May 1995 A
5422624 Smith Jun 1995 A
5422816 Sprague et al. Jun 1995 A
5432542 Thibadeau et al. Jul 1995 A
5432841 Rimer Jul 1995 A
5441047 David et al. Aug 1995 A
5442553 Parillo Aug 1995 A
5444450 Olds et al. Aug 1995 A
5458123 Unger Oct 1995 A
5459660 Berra Oct 1995 A
5465079 Bouchard Nov 1995 A
5477228 Tiwari et al. Dec 1995 A
5479479 Braitberg et al. Dec 1995 A
5479482 Grimes Dec 1995 A
5481542 Langston et al. Jan 1996 A
5504482 Schreder Apr 1996 A
5506897 Moore et al. Apr 1996 A
5510798 Bauer Apr 1996 A
5512908 Herrick Apr 1996 A
5515043 Berard et al. May 1996 A
5515285 Garrett, Sr. et al. May 1996 A
5515419 Sheffer May 1996 A
5519760 Borkowski et al. May 1996 A
5539395 Buss et al. Jul 1996 A
5543789 Behr et al. Aug 1996 A
5544661 Davis et al. Aug 1996 A
5555286 Tendler Sep 1996 A
5556749 Mitsuhashi et al. Sep 1996 A
5557254 Johnson et al. Sep 1996 A
5561704 Salimando Oct 1996 A
5572204 Timm et al. Nov 1996 A
5576716 Sadler Nov 1996 A
5576952 Stutman et al. Nov 1996 A
5579013 Hershey et al. Nov 1996 A
5579285 Hubert Nov 1996 A
5583776 Levi et al. Dec 1996 A
5588148 Landis et al. Dec 1996 A
5598456 Feinberg Jan 1997 A
5598460 Tendler Jan 1997 A
5610815 Gudat et al. Mar 1997 A
5615116 Gudat et al. Mar 1997 A
5625668 Loomis et al. Apr 1997 A
5630206 Urban et al. May 1997 A
5632041 Peterson et al. May 1997 A
5640323 Kleimenhagen et al. Jun 1997 A
5646843 Gudat et al. Jul 1997 A
5652570 Lepkofker Jul 1997 A
5669061 Schipper Sep 1997 A
5673305 Ross Sep 1997 A
5686910 Timm et al. Nov 1997 A
5687215 Timm et al. Nov 1997 A
5696503 Nasburg et al. Dec 1997 A
5701419 McConnell Dec 1997 A
5706498 Fuiimiya et al. Jan 1998 A
5708780 Levergood et al. Jan 1998 A
5712899 Pace, II Jan 1998 A
5724070 Denninghoff et al. Mar 1998 A
5726893 Schuchman et al. Mar 1998 A
5727057 Emery et al. Mar 1998 A
5732074 Spaur et al. Mar 1998 A
5732125 Oyama Mar 1998 A
5737700 Cox et al. Apr 1998 A
5740549 Reilly et al. Apr 1998 A
5745681 Levine et al. Apr 1998 A
5764923 Tallman et al. Jun 1998 A
5774357 Hoffberg et al. Jun 1998 A
5806018 Smith et al. Sep 1998 A
5808197 Dao Sep 1998 A
5808564 Simms et al. Sep 1998 A
5808907 Shetty et al. Sep 1998 A
5826195 Westerlage et al. Oct 1998 A
5829782 Breed et al. Nov 1998 A
5840020 Heinonen et al. Nov 1998 A
5848373 Delorme et al. Dec 1998 A
5848396 Gerace Dec 1998 A
5857155 Hill et al. Jan 1999 A
5867799 Lang et al. Feb 1999 A
5867821 Ballantyne et al. Feb 1999 A
5869244 Martin et al. Feb 1999 A
5875108 Hoffberg et al. Feb 1999 A
5878141 Daly et al. Mar 1999 A
5878417 Baldwin et al. Mar 1999 A
5893111 Sharon et al. Apr 1999 A
5895371 Levitas et al. Apr 1999 A
5901978 Breed et al. May 1999 A
5917405 Joao Jun 1999 A
5933080 Nojima Aug 1999 A
5933827 Cole et al. Aug 1999 A
5940004 Fulton Aug 1999 A
5940821 Wical Aug 1999 A
5959580 Maloney et al. Sep 1999 A
5987381 Oshizawa Nov 1999 A
5987519 Peifer et al. Nov 1999 A
5991735 Gerace Nov 1999 A
6014090 Rosen et al. Jan 2000 A
6016509 Dedrick Jan 2000 A
6018292 Penny, Jr. Jan 2000 A
6023729 Samuel et al. Feb 2000 A
6025788 Diduck Feb 2000 A
6028537 Suman et al. Feb 2000 A
6032054 Schwinke Feb 2000 A
6047327 Tso et al. Apr 2000 A
6061561 Alanara et al. May 2000 A
6064970 McMillan et al. May 2000 A
6067500 Morimoto et al. May 2000 A
6081780 Lumelsky Jun 2000 A
6083248 Thompson Jul 2000 A
6104338 Krasner Aug 2000 A
6122520 Want et al. Sep 2000 A
6128482 Nixon et al. Oct 2000 A
6131067 Girerd et al. Oct 2000 A
6141010 Hoyle Oct 2000 A
6150927 Nesbitt Nov 2000 A
6150961 Alewine et al. Nov 2000 A
6151551 Geier et al. Nov 2000 A
6161125 Traversat et al. Dec 2000 A
6177931 Alexander et al. Jan 2001 B1
6195654 Wachtel Feb 2001 B1
6211777 Greenwood et al. Apr 2001 B1
6219696 Wynblatt et al. Apr 2001 B1
6246672 Lumelsky Jun 2001 B1
6250148 Lynam Jun 2001 B1
6252544 Hoffberg Jun 2001 B1
6263268 Nathanson Jul 2001 B1
6263384 Yanase Jul 2001 B1
6269394 Kenner et al. Jul 2001 B1
6275231 Obradovich Aug 2001 B1
6295449 Westerlage et al. Sep 2001 B1
6308175 Lang et al. Oct 2001 B1
6314420 Lang et al. Nov 2001 B1
6314422 Barker et al. Nov 2001 B1
6317090 Nagy et al. Nov 2001 B1
6324393 Doshay Nov 2001 B1
6332086 Avis Dec 2001 B2
6333703 Alewine et al. Dec 2001 B1
6339842 Fernandez et al. Jan 2002 B1
6341523 Lynam Jan 2002 B2
6363421 Barker et al. Mar 2002 B2
6374290 Scharber et al. Apr 2002 B1
6400690 Liu et al. Jun 2002 B1
6405132 Breed et al. Jun 2002 B1
6415188 Fernandez et al. Jul 2002 B1
6429812 Hoffberg Aug 2002 B1
6430488 Goldman et al. Aug 2002 B1
6434400 Villeville et al. Aug 2002 B1
6484080 Breed Nov 2002 B2
6493637 Steeg Dec 2002 B1
6516664 Lynam Feb 2003 B2
6535743 Kennedy, III et al. Mar 2003 B1
6539336 Vock et al. Mar 2003 B1
6542076 Joao Apr 2003 B1
6542794 Obradovich Apr 2003 B2
6549130 Joao Apr 2003 B1
6580390 Hay Jun 2003 B1
6580904 Cox et al. Jun 2003 B2
6587046 Joao Jul 2003 B2
6590602 Fernandez et al. Jul 2003 B1
6647328 Walker Nov 2003 B2
6678612 Khawam Jan 2004 B1
6697103 Fernandez et al. Feb 2004 B1
6720920 Breed et al. Apr 2004 B2
6735506 Breed et al. May 2004 B2
6754485 Obradovich et al. Jun 2004 B1
6768944 Breed et al. Jul 2004 B2
6791472 Hoffberg Sep 2004 B1
6792263 Kite Sep 2004 B1
6807558 Hassett et al. Oct 2004 B1
6813777 Weinberger et al. Nov 2004 B1
6816727 Cox et al. Nov 2004 B2
6823244 Breed Nov 2004 B2
6826775 Howe et al. Nov 2004 B1
6832178 Fernandez et al. Dec 2004 B1
6853907 Peterson et al. Feb 2005 B2
6868389 Wilkins et al. Mar 2005 B1
6871139 Liu et al. Mar 2005 B2
6882837 Fernandez et al. Apr 2005 B2
6882905 Hall et al. Apr 2005 B2
6922664 Fernandez et al. Jul 2005 B1
6950638 Videtich et al. Sep 2005 B2
6963899 Fernandez et al. Nov 2005 B1
6965816 Walker Nov 2005 B2
6968736 Lynam Nov 2005 B2
6987964 Obradovich et al. Jan 2006 B2
6988026 Breed et al. Jan 2006 B2
7039393 Kite May 2006 B1
7042363 Katrak et al. May 2006 B2
7062379 Videtich Jun 2006 B2
7082359 Breed Jul 2006 B2
7084859 Pryor Aug 2006 B1
7085637 Breed et al. Aug 2006 B2
7103460 Breed Sep 2006 B1
7113860 Wang Sep 2006 B2
7124004 Obradovich Oct 2006 B2
7142099 Ross et al. Nov 2006 B2
7142844 Obradovich et al. Nov 2006 B2
7147246 Breed et al. Dec 2006 B2
7155335 Rennels Dec 2006 B2
7164177 Chang et al. Jan 2007 B2
7165040 Ehrman et al. Jan 2007 B2
7171381 Ehrman et al. Jan 2007 B2
7203300 Shaffer et al. Apr 2007 B2
7231357 Shanman et al. Jun 2007 B1
7548961 Fernandez et al. Jun 2009 B1
20010007086 Rogers et al. Jul 2001 A1
20010056544 Walker Dec 2001 A1
20020001317 Herring Jan 2002 A1
20020034757 Cubicciotti Mar 2002 A1
20020049389 Abreu Apr 2002 A1
20040215931 Ellis Oct 2004 A1
20050125117 Breed Jun 2005 A1
Foreign Referenced Citations (10)
Number Date Country
0718614 Jun 1996 EP
0748727 Dec 1996 EP
0921411 Sep 1999 EP
2261977 Feb 1993 GB
2320973 Jul 1998 GB
8076706 Mar 1996 JP
WO 9515658 Jun 1995 WO
WO 9522131 Aug 1995 WO
WO 9726061 Jul 1997 WO
WO 9729373 Jul 1997 WO
Non-Patent Literature Citations (39)
Entry
U.S. Appl. No. 09/145,167, filed Sep. 1, 1998, Fernandez, et al.
U.S. Appl. No. 09/952,329, filed Sep. 14, 2001, Fernandez, et al.
U.S. Appl. No. 11/585,468, filed Oct. 23, 2006, Fernandez, et al.
U.S. Appl. No. 11/852,848, filed Sep. 10, 2007, Fernandez, et al.
U.S. Appl. No. 12/113,042, filed Apr. 30, 2008, Fernandez, et al.
U.S. Appl. No. 12/239,593, filed Sep. 26, 2008, Fernandez, et al.
U.S. Appl. No. 90/010,397, filed Feb. 10, 2009, Fernandez, et al.
Carstensen, Todd. OnStar—First With Remote Diagnostics. OnStar Press Release from GM/Onstar Website [online], Sep. 4, 1997 [retrieved on Jan. 17, 2008]. Retrieved from the Internet: <URL: http://209.235.195.221/releases—detail.php?ItemID=89>.
Caskey et al. Diagnosis of Human Heritable Defects by Recombinant DNA Methods. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences, vol. 319, No. 1194, The Prevention and Avoidance of Genetic Disease [online], Jun. 15, 1988 [retr. on Feb. 27, 2007]. Retrieved from the Internet: <www.jstor.org/stable/2396686>.
Sassa, S. & K. Furuyama. “How Genetic Defects Are Identified”, Clinics in Dermatology, vol. 16, Issue 2 (Mar. 4, 1998), pp. 235-243.
Charatan, Fred. US unveils new DNA database. British Medical Journal, vol. 317, No. 7168 [online], Nov. 7, 1998 [retrieved on Feb. 3, 2007]. Retrieved from the Internet: <URL: www.bmj.com/cgi/content/full/317/7168/1274/c?maxtoshow=&H...ence+patient=database&searchid=1&FIRSTINDEX=0&resourcetype=HWCIT>.
Cameron, M. & Brown, A. “Intelligent Transportation System Mayday Becomes a Reality”, Proc. of IEEE 1995 Nat'l Aerospace and Electronics Conf., (May 22-26, 1995), pp. 340-347.
Brown, A. & R. Silva. “TIDGET Mayday System for Motorists”, Position Location and Navigation Symposium, 1994., IEEE, (Apr. 11-15, 1994), pp. 480-485.
Karimi,H.A & Lockhart,J.T. “GPS-Based Tracking System for Taxi Cab Fleet Operations”, Proc. IEEE-IEE Vehicle Navigation and Information Sys. Conf.(Oct. 12-15, 1993) pp. 679-682.
Steed, Julian. “The Management of Dangerous Goods Transport: The European Approach”, Proc. IEEE-IEE Vehicle Navigation and Information Sys. Conf. (Oct. 12-15, 1993), pp. 674-678.
Vieveen et al. “Telematics and Dangerous Goods in the Netherlands, telematics for road transport; the TGS project”, Proceedings of the IEEE-IEE Vehicle Navigation & Information Systems Conference, 1993, (Oct. 12-15, 1993), pp. 653-656.
US Department of Transportation, National Highway Traffic Safety Administration. “Technology Alternatives for an Automated Collision Notification System: Final Report.” National Technical Information Service, Springfield, VA, Aug. 1994.
“Transportation Electronics: Proceedings of the International Congress on Transportation Electronics”, Society of Automotive Engineers, Inc., Warrendale, PA, Oct. 1986, pp. 261-263.
Jameel, A. & Fuchs, E. “White Paper: Internet Multimedia on Wheels”, Media Briefing, Daimler-Benz Research and Technology North America, Apr. 30, 1997.
Jameel, A. & Fuchs, E. “Daimler-Benz Research and Technology Previews First ‘Internet Multimedia on Wheels’ Technology; Future Mercedes-Benz drivers and passengers to access Cyberspace from their seats”, Media Information, Daimler-Benz Research and Technology North America, Apr. 30, 1997.
Shows, Winnie. “Video Clips List.” Daimler-Benz [fax], May 13, 1997 [retrieved on May 13, 1997].
Markoff, John. “Daimler-Benz to Exhibit an Early-Stage Internet Car”, The New York Times, Section D (Apr. 29, 1997), p. 2.
Karmouch, A. “Multimedia Distributed Cooperative System,” Computer Communications, vol. 16, No. 9 (Sep. 1993), pp. 568-580.
Grundig et al. “The HAVi Architecture, Specification of the Home Audio/Video Interoperability (HAVi) Architecture, Version 0.8 Draft.” May 11, 1998.
Grigsby, J. & Sanders, J.H. Telemedicine: Where It Is and Where It's Going. Annals of Internal Medicine, vol. 129, Issue 2 [online], Jul. 15, 1998, [retrieved on Feb. 20, 2009]. Retrieved from the Internet: <URL: http://www.annals.org/cgi/content/full/129/2/123>pp. 123-127.
Engage Technologies. Engage announces Accipiter AdManager 4.0 for precision online marketing. Press Release, Jupiter Online Advertising Show [online], Aug. 10, 1998 [retrieved on Oct. 28, 1998]. Retrieved from the Internet: <URL:http://www.engage.com/press/realeases/081198pradm40.htm>.
Engage Technologies. Accipiter announces Accipiter AdManager, a breakthrough in Internet advertising and marketing. Press Release, Seybold San Francisco [online], Sep. 9, 1996 [retrieved on Oct. 28, 1998]. Retrieved from the Internet <URL: http://www.engage.com/press/releases/pr—adman10.htm>.
Evaluation Manager, Argonne National Lab. The Advanced Project: Formal Evaluation of the Targeted Deployment, vol. 1. U.S. Department of Transportation [online], Jan. 1997 [retrieved on Jul. 2, 2009]. Retrieved from the Internet <URL: http://ntl.bts.gov/lib/2000/2700/2763/m97007401.pdf>.
Evaluation Manager, Argonne National Lab. The Advanced Project: Formal Evaluation of the Targeted Deployment, vol. 2. U.S. Department of Transportation [online], Jan. 1997 [retrieved on Jul. 2, 2009]. Retrieved from the Internet <URL: http://www.itsdocs.fhwa.dot.gov/JPODOCS/REPTS—TE/3324.pdf>.
Evaluation Manager, Argonne National Lab. The Advanced Project: Formal Evaluation of the Targeted Deployment, vol. 3. U.S. Department of Transportation [online], Jan. 1997 [retrieved on Jul. 2, 2009]. Retrieved from the Internet <URL: http://www.itsdocs.fhwa.dot.gov//JPODOCS/REPTS—TE//3213.pdf>.
General Motors Corp., Corrected Request for Ex Parte Reexamination, from U.S. Patent Reexamination Control No. 90/010,397 (filed Feb. 10, 2009).
Fernandez Innovative Technologies, L.L.C., Plaintiff's Opening Claim Construction Brief, Fernandez Innovative Tech., L.L.C. v. General Motors Corp., No. 07-cv-01397, 2008 WL 2168843 (N.D. III. 2008). Brief filed Dec. 18, 2007.
Fernandez Innovative Technologies, L.L.C., Plaintiff's Reply Brief in Support of its Claim Construction Argument, Fernandez Innovative Tech., L.L.C. v. General Motors Corp., No. 07-cv-01397, 2008 WL 2168843 (N.D. III. 2008). Brief filed Feb. 8, 2008.
Fernandez Innovative Technologies, L.L.C., Brief of Plaintiff-Appellant, Fernandez Innovative Tech., L.L.C. v. General Motors Corp., 2008-1533 (Fed. Cir. Oct. 23, 2008).
USPTO, Final Rejection, from U.S. Appl. No. 09/952,285 (action mailed Nov. 24, 2004).
Fernandez, D., Appeal Brief, from U.S. Appl. No. 09/952,285 (brief filed Feb. 10, 2005).
General Motors Corp., Exhibits M-R (Claim Charts), from U.S. Patent Reexamination Control No. 90/010,397 (filed Jan. 27, 2009).
“SNET Announces Major Entry Into Health Care Market: SNET LifeNet Solutions”, PR Newswire, Dec. 3, 1996.
Fano, Andrew, “Shopper's Eye: Using Location-Based Filtering for a Shopping Agent in the Physicial World”, Agents '98 2nd International Conference on Autonomous Agents, Minneapolis, MN, May 1998.
Continuations (1)
Number Date Country
Parent 12239593 Sep 2008 US
Child 12541065 US