SensLoc: sensing everyday places and paths using less energy

By Donnie H. Kim, Younghun Kim, Deborah Estrin, Mani B. Srivastava. ACM International Conference on Embedded Networked Sensor Systems, 2010

301 citations recorded by the source corpus.

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DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications (2017, background): “• Case Study 2: A user shares accelerometer data with a realtime life-logging app that helps with travel planning (useful inferences) [45], [34].”
On the validity of geosocial mobility traces (2013, methodology): “In the following, we describe our data collection process and the two datasets used for our study.”
Accelerometer-based transportation mode detection on smartphones (2013, background): “During periods of extended stationary behavior, the application could also be switched off until notable kinematic movement is detected from the accelerometer [14] or the primary GSM cell changes [26].”
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey (2020, methodology): “user’s location [47], microphones and Bluetooth are used to analyze human interactions [48], and CO2 sensors are employed to estimate the air quality [49].”