The various technologies presented herein relate to determining a location of an individual, or an object, when a GPS may be unavailable/occluded Readings from a plurality of sensors on a mobile device can be generating a plurality of data (eg, speed, motion, temperature, biometric, etc) which can be combined to generate a probability of a user of the mobile device being at a particular location, or not Sensor readings can be weighted to enable sensors having a large effect on a degree of confidence of the probability of the user being determined to be at a location being given priority (eg, battery priority) versus those sensors which have lesser effect on the degree of confidence With the user determined to be at a location, information, a notification, an instruction, etc, can be presented to the user, via the mobile device

Journey analysis system and method

The technology described herein is directed to a health-monitoring service that facilitates contextual grouping of sensor channels for healthcare monitoring In some implementations, clustering algorithms and predictive models can be used to dynamically select the sensor channels associated with a mobile communication device that are monitored In this manner, only those sensor channels that provide meaningful signals are monitored

Contextually grouping sensor channels for healthcare monitoring

A wireless environmental sensor or monitoring device includes a processor unit, a monitor module for monitoring and collecting data corresponding to an environmental parameter, a radio module configured to enable wireless communication of the data to a remote system, and logic executable by the processor unit to: monitor wireless communication connectivity between the radio module and the remote system; and responsive to detecting a loss of wireless communication connectivity with the remote system, automatically enable a wireless access point (AP) mode of the radio module to initiate a broadcast of a local wireless network identifier to enable a client device to wirelessly locate and connect to the sensor device.

Wireless environmental sensor

A mobile device and a method for determining a place according to geolocation information is disclosed. In one aspect, the method includes triggering an action in obtaining a first set of information related to the user, and, according to the current geographical location, a second set of places. The method may also include, for each place of the second set, determining a combined probability distribution that the user is currently located in said place, according to the first set of information, a first probability distributions based on a set of parameters related to global user habits, a second probability distributions based on a set of parameters related to user habits, and a third probability distributions based on a set of parameters related to local user habits. The method may further include triggering at least one action according to the combined probability distributions of the places of the second set.

Mobile device and method for determining a place according to geolocation information

A mobile device includes a plurality of sensors, each with one or more costs associated with it. In order to reduce the cost associated with using the sensors to infer information about the device's current context, a sensor manager first collects readings from relatively low-cost sensors, and attempts to infer the device's context based on these readings. If the context cannot be unambiguously determined (within an acceptable degree of tolerance) using the low-cost sensor readings, the sensor manager activates one or more higher-cost sensors to identify the current context. In some instances, if the higher-cost sensor is still not adequate to determine the context, one or more even higher-cost sensors are activated. The weighting of the various costs associated with the sensors can be adjusted based on previous and/or predicted contexts.

Ian G. Clifton

Papers

Accurate Mobile Context Detection At Low Sensor Cost