System and method for control and management of resources for consumers of information
a technology for information consumers and resources, applied in the field of information delivery, discovery, management and control, can solve problems such as too many apps to try, complicated problems for mobile users, and difficulty in finding useful apps for a particular purpose or suitable for a particular occasion
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example 1
[0100]Suppose a mobile device / smartphone user is attending the opera and brings with him the device 108. The device's location may be reported to the service provider 1008, for example, by the HLR reporting scheme described above, or by any suitable method, such as a GPS (global positioning system) type system (not shown). In addition, one or more other sensor-based conditions, such as a level of ambient noise or the device remaining still for a predetermined period, may likewise be reported. This information may be stored by the service provider, for example, in conjunction with an environment map 104, as discussed above. The information may additionally, or alternatively, be provided to an inference engine 118, which has access to the sensor rules database. The inference engine 118 may access a rule and decide that there is a fit to an “attending opera” situational profile. A rule based on these antecedents might be, for example, to recommend an app to automatically mute, shut off...
example 2
[0102]Suppose the user has taken his smartphone 108 while sailing on Lake Michigan. The user device 108 transmits sensor information, such as location, speed, or indicia of continuous orientation changes (i.e., from bobbing up and down on waves). The inference engine 118 receives or accesses this information and determines if there is a rule and situational profile. A rule, for example, might be to recommend a squall or weather warning app when the user is detected sailing. If the user installs the app, then the next time he meets the situational profile, the weather warning app may be activated.
example 3
[0103]In this example, more than one situational profile arises in conjunction with a particular set of antecedents. Each of the “matched” situational profiles can be associated with its own unique set of recommended apps.
[0104]A user is in his automobile circling a given block that is known to contain a Starbuck's. The service provider 1008 receives the “circling” and “Starbuck's” information into the environment map 104, which is accessed by the inference engine 118. The inference engine 118 may then infer one or more situational profiles that may be associated with these antecedents. The service provider 1008 can then send recommendations based on the situational profiles.
[0105]One such situational profile that may be associated with these antecedents is that the user is attempting to buy a cup of coffee. In this case, the user may receive a recommendation for an app that will advise the user whenever he is near a Starbuck's. Alternatively, or in addition, the user could receive ...
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