Some embodiments relate to systems and methods associated with mobile user devices. More specifically, some embodiments are directed to systems and methods to provide location based support request messages responsive to alert recommendations.
A user of a user device (e.g., a smartphone) may find that he or she suddenly and unexpectedly needs support from one or more other individuals. For example, a user might experience a medical event (e.g., a heart attack, stroke, etc.) and require immediate medical assistance. Similarly, user might be attacked and need the help of the police department. Typically, a user would use his or her smartphone to call for help from emergency services (e.g., by contacting the police, fire department, ambulance, etc.). In some cases, however, a user might be unable to use a smartphone (e.g., if he or she is unconscious or otherwise unable to speak or use the smartphone). Moreover, emergency service individuals might be located a substantial distance away from the user, and, as a result, the amount of time it would take them to respond to his or her request could be substantial.
Accordingly, methods and mechanisms to efficiently, accurately, and/or automatically facilitate location based support request messages responsive to alert recommendations may be provided in accordance with some embodiments described herein.
In some situations, a user of a user device, such as a smartphone, may find that he or she needs support from one or more other individuals. For example, a user might experience a medical event or be attacked and need rapid help from an ambulance, the police department, etc. Note that in some cases a user may be unable to use a smartphone or similar device (e.g., if he or she is unconscious). Moreover, the nearest emergency service individuals might be far away, the amount of time it would take them to respond to such a request could be substantial. To address such problems,
The alert signal may be received by a notification platform 150 via a recommendation communication port 152. The notification platform 150 may also receive or otherwise determine a user's current location. Based on this information, the notification platform 150 may transmit one or more support request messages to nearby individuals who are using communication devices. In this way, the nearby individuals may be able to provide support and/or assistance to the user in a timely fashion.
According to some embodiments, the notification platform 150 may directly communicate with one or more remote communication device via Bluetooth or the Internet. According to other embodiments, a gateway may be provided between the notification platform 150 and other remote devices. The other devices may include, according to some embodiments, one or more processors to receive electronic files and/or to execute applications and/or components (e.g., a plug-in that is integrated to a smartphone or tablet).
Note that
Any of the devices illustrated in
All systems and processes discussed herein may be embodied in program code stored on one or more computer-readable media. Such media may include, for example, a floppy disk, a CD-ROM, a DVD-ROM, magnetic tape, OR solid state Random Access Memory (“RAM”) or Read Only Memory (“ROM”) storage units. Embodiments are therefore not limited to any specific combination of hardware and software.
According to some embodiments, the system may receive or determine a current location (e.g., based on Global Positioning System (“GPS”) satellite information, cell phone tower information, etc.) and use that information, along with the alert signal from the alert recommendation engine, to output support request messages to nearby individuals.
At S210, an alert recommendation platform may receive data associated with current local condition signals from a set of condition monitoring sensors. Each condition monitoring sensor may be, for example, adapted to provide a signal indicative of a current condition local at a user device. As used herein, the phrase “user device” may refer to, for example, a smartphone, an activity or fitness tracker, a smartwatch, a wearable computing device, a game or entertainment device, a music player, and/or a vehicle computer. Moreover, as used herein the phrase “condition monitoring sensor” might refer to devices associated with, for example, a smartphone, an activity or fitness tracker, a smartwatch, a wearable computing device, a vehicle computer (e.g., including device that transmit telematics data), a motion sensor, an accelerometer, a heart rate monitor, a blood pressure monitor, a glucose level monitor, skin resistance, a body temperature thermometer, a microphone (e.g., to detect an automobile crash, gunshot, etc.), a game or entertainment device, a music device, a location device (e.g., a navigation assistance apparatus), and/or any other diagnostic device or tool.
At S220, the system may automatically analyze the received data and decision logic to generate an alert recommendation. According to some embodiments, the decision logic is based on historic information associated with other user devices. For example, the system may learn over time which sets of sensor input conditions are typically associated with emergencies (and which are not). In other embodiments, the decision logic may be based on past interactions with the user device (e.g., and/or a user associated with the user device). For example, a system might learn information about a user over a period of time (e.g., as the system becomes familiar with the user's health conditions, his or her typical reactions to various situations, etc.). In this way, the determination of when an emergency is occurring and/or how notifications should be handled may improve over time. According to some embodiments, the decision logic includes a user confirmation action (e.g., where he or she agrees that support request messages should be transmitted) and/or a user opt-out action (e.g., where he or she must take an affirmative action to prevent the transmission of support request messages). At S230, the alert recommendation platform outputs an alert signal based on the alert recommendation (e.g., to a notification platform).
At S330, the system may arrange for at least some of the potential support communication devices to receive a support request message. In this way, nearby individuals associated with those devices may be able to assist the user in a timely fashion. According to some embodiments, the user device and/or the potential support communication devices may also automatically notify a public emergency services platform (e.g., associated with an ambulance, fire department, police department, one or more user “in case of emergency” contact addresses, etc.).
Note that nearby individuals 430 might be automatically selected based on location information. For example,
According to some embodiments, both an alert recommendation platform and a notification platform are implemented as part of a user device (e.g., his or her smartphone). For example,
According to some embodiments, at least one of the alert recommendation and the notification platform are implemented via a cloud-based application remote from the user device. For example,
By placing some of the processing associated with the system in a cloud-based application or service, the performance and/or battery life of the user device 910 may be improved. Moreover, the alert recommendation platform 940 and/or the notification platform 950 might utilize greater computational power as compared to a smartphone or similar device. Note that in some embodiments, the alert recommendation platform 940 and/or the notification platform 950 might be associated with an Enterprise Resource Planning (“ERP”) server, a business services gateway, a HyperText Transfer Protocol (“HTTP”) server, and/or an Advanced Business Application Programming (“ABAP”) server. According to some embodiments, elements of the system 100 may provide connectivity to a business server, such as one associated with enterprise software (including CRM, ERP, and other backend processes) to help provide assistance to individuals in substantially real-time. In this way, the power of backend knowledge (for example at back-end application server) may be used to help an individual who is in need of assistance.
Thus, embodiments, may leverage a real-time self-learning recommendation engine (e.g., associated with an SAP® Real-Time Offer Management system) not only to identify when help should be requested from an ambulance or the police, but also to perform actions such as informing nearby people about an emergency by automatically transmitting messages to individuals in the area. Such an approach may utilize powerful real-time decision making and analytics power to provide implicit signaling by a person's device in an emergency. The device may detect a critical situation (e.g., losing consciousness in a car accident) via sensors and automatically call for help and inform people in the area. As another example, a person might break an ankle while hiking on a mountain (e.g., far from any ambulance) or get mugged on a street corner. In either case, a nearby pedestrian or car driver might provide help to if he or she know about the situation.
In some cases, a person may be in an emergency situation but be unable to call an emergency service on his own (e.g., because he or she got trapped and beaten up by a criminal, lost consciousness after falling, etc.). The acceleration sensors of a smartphone and fitness tracker, the crash sensors in an onboard car computer, etc. are just some examples of devices that could detect large force impacts or vital sign problems (e.g., pulse rate, blood pressure, etc.). In other cases, a person may be able to call for help. For example, a user device might act as a “panic” button informing both official emergency services and nearby individuals. The situation might not be dangerous for the individuals and they may be able to help immediately. In other cases, the people may be able to verify that the police have been called (and may stay in the area to later act as a helpful witness).
Note that embodiments might utilize many sources of information. For example, smartphone acceleration sensors might detect when a person falls to the ground or is beaten by an attacker. In this case, communication devices may signal nearby people while allowing them to remain at a safe distance. As another example, fitness trackers with a heart rate monitor might signal an extremely high heart rate indicating an elevated stress level or cardiac infarction. Stress levels might also be measured with skin resistance sensors integrated into fitness trackers.
Any of the recommendation platforms described herein might be installed directly on a user device or in a cloud environment. When directly installed on a user device, an engine could even work offline and analyze sensor data to match locally available historical data. When available via the cloud, an engine might provide more computing power to better analyze sensor data (and would not negatively impact device battery life).
According to some embodiments, automatic alarm detection may use techniques to reduce false positives. Such techniques might include, for example, automatic learning. Note that a recommendation engine may use historical sensor data from past actual incidents. A cloud-based application hosting this type of information may centrally collect incident data from all users. Moreover, data about every emergency (either implicitly or explicitly signaled) may be uploaded and help to improve data quality. This may allow for better pattern detection by the recommendation engine in connection with future incidents. Note, however, that having data sources hosted only in the cloud might not be feasible. For example, a device may sometimes have a weak signal to a service provider (or a data plan limit has been reached) during an incident. Thus, some embodiments may provide a local mobile recommendation engine that synchronizes identified patterns from a sensor database in the cloud whenever the device can communicate online. Such an approach may let the device still react to emergencies even when it is offline.
In some implicit signaling embodiments, a recommendation engine may continuously monitor available sensors. The engine may look for patterns of data which have been connected to emergency events in the past. If a similar pattern is detected, the recommendation engine may recommend a next best action, such as: calling an ambulance, firefighters or the police; and/or informing other nearby individuals. The recommendation engine may, for example, recommend the actions that best match previous incidents. In some explicit signaling embodiments, available historical data might not be sufficient to allow the recommendation engine to automatically detect the incident and recommend an action. In this case, a user may still be able to activate the system to manually call for help.
Note that embodiments might be implemented via devices other than a smartphone. For example,
In addition to provide a display to a user in need of assistance, embodiments may also provide displays to nearby individuals via their communication devices. For example,
Accordingly, methods and mechanisms to efficiently, accurately, and/or automatically facilitate location based support request messages responsive to alert recommendations may be provided in accordance with some embodiments described herein. Note that the techniques described with respect to
The processor 1510 communicates with a storage device 1530. The storage device 1530 may comprise any appropriate information storage device, including combinations of magnetic storage devices (e.g., a hard disk drive), optical storage devices, and/or semiconductor memory devices. The storage device 1530 stores a program 1512 and an alert recommendation and/or notification platform/engine 1514 for controlling the processor 1510. The processor 1510 performs instructions of the programs 1512, 1514, and thereby operates in accordance with any of the embodiments described herein. For example, the processor 1510 may receive signals indicative of current conditions local at a user device (e.g., a smartphone) from a set of condition monitoring sensors. The processor 1510 may automatically analyze the signals and decision logic to generate an alert recommendation and output an alert signal. Responsive to the alert signal, the processor 1510 may automatically determine a set of potential support communication devices (e.g., other smartphones) based at least in part on a location associated with the user device and locations of the potential support communication devices. The processor 1510 may then arrange for at least some of the potential support communication devices to receive a support request message (e.g., nearby smartphones may receive notification messages requesting support).
The programs 1512, 1514 may be stored in a compressed, uncompiled and/or encrypted format. The programs 1512, 1514 may furthermore include other program elements, such as an operating system, a database management system, and/or device drivers used by the processor 1510 to interface with peripheral devices.
As used herein, information may be “received” by or “transmitted” to, for example: (i) the apparatus 1500 from another device; or (ii) a software application or module within the apparatus 1500 from another software application, module, or any other source.
In some embodiments (such as shown in
Referring to
The support request message identifier 1602 may be, for example, a unique alphanumeric code identifying a support request message that has been, or may be, transmitted to nearby individual. The sensors 1604 may indicate one or more sensors that provide signals indicative of a current condition local at a user device (e.g., that reflect his or her health, wellbeing, etc.). The description 1606 might reflect when the support request message was generated and the location 1608 might define his or location when the alert signal was generated (e.g., which may be used to determine nearby individuals and/or communication devices). The potential support communication devices 1610 might comprise a list of descriptions or identifiers associated with nearby individuals who received the support message request.
Thus, some embodiments may establish methods and mechanisms to efficiently, accurately, and/or automatically facilitate location based support request messages responsive to alert recommendations. The following illustrates various additional embodiments and do not constitute a definition of all possible embodiments, and those skilled in the art will understand that the present invention is applicable to many other embodiments. Further, although the following embodiments are briefly described for clarity, those skilled in the art will understand how to make any changes, if necessary, to the above-described apparatus and methods to accommodate these and other embodiments and applications.
While embodiments have been illustrated using particular types of tables and databases, embodiments may be implemented in any other of a number of different ways. For example, some embodiments might be associated with publically available information, such as weather or traffic information available via web sites.
Moreover, any of the embodiments described herein may incorporate business intelligence and/or smart learning systems to help optimize responses according to real time data from users. Such types of valuable business information may better serve customers and/or help an organization improve service quality. Similarly, embodiments may provide analysis and prediction abilities and/or let a user inform the system about unusual situations. For example, a user might inform the system that he or she was not experiencing an emergency even though the sensor data was unusual (e.g., he or she might have been on a rollercoaster ride at an amusement park).
Embodiments have been described herein solely for the purpose of illustration. Persons skilled in the art will recognize from this description that embodiments are not limited to those described, but may be practiced with modifications and alterations limited only by the spirit and scope of the appended claims.
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8559914 | Jones | Oct 2013 | B2 |
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Number | Date | Country | |
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20180144614 A1 | May 2018 | US |