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AssigneeTelcordia Technologies, Inc.
InventorsArchan Misra, Benjamin Falchuk, Atanu Roy Chowdhury
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A scalable middleware for supporting energy-efficient, long-term remote health monitoring and the capture and transmission of relative causative contextual history where data is collected using physiological sensors and transported back to the middleware through a mobile device serving as a gateway. The key to energy efficient operations lies in the adoption of an Activity Triggered Deep Monitoring paradigm, where data collection episodes are triggered only when the system is determined to possess a specified set of causative contexts. The system supports on-demand collection of causative contextual history using a low-overhead provenance collection sub-system. In a preferred embodiment the behavior of this sub-system is configured using an application-defined context composition graph. The resulting causative context history stream provides valuable insight into the states and conditions surround sensor readings and allows improved human interpretation of the ‘episodic’ sensor data streams.
A method of capturing, transmitting and reconstructing causative contextual history that elaborates on data collected by an adaptive continuous remote monitoring application using one or more mobile devices as a gateway, the method comprising the steps of:
A method for storing, tracking and recreating the relevant causative contextual history of a user with regard to raw data sensed at the user, the method comprising the steps of:
A system for capturing causative contextual history for remote monitoring comprising:
A method of capturing, transmitting and reconstructing causative contextual history that elaborates on data collected by an adaptive remote monitoring application using a mobile device, the method comprising the steps of:
Dependencies are inferred from the claim text.