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By monitoring human behavior unobtrusively, mobile sensing technologies have the potential to improve our daily lives. Initial results from a field study demonstrate that such passive technologies can detect a complex psychological state in an uncontrolled, real-life environment. In the web extra at https://youtu.be/n8Ap3Z44ojQ, guest editor Katarzyna Wac interviews authors Adela Timmons and Theodora...
New and emerging mobile technologies are providing unprecedented possibilities for understanding and intervening on obesity-related behaviors in real time. However, the mobile health (mHealth) field has yet to catch up with the fast-paced development of technology. Current mHealth efforts in weight management still tend to focus mainly on short message systems (SMS) interventions, rather than taking...
We introduce the sensor-utility-network (SUN) method for occupancy estimation in buildings. Based on inputs from a variety of sensor measurements, along with historical data regarding building utilization, the SUN estimator produces occupancy estimates through the solution of a receding-horizon convex optimization problem. State-of-the-art on-line occupancy algorithms rely on indirect measurements,...
Algorithmic noise tolerance (ANT) techniques have reduced power consumption in many signal-processing applications, but they typically require an error-free estimator block and do not fully exploit the statistical nature of timing errors. By approaching certain computations as estimation problems, we draw inspiration from sensor networks and develop a novel power conservation scheme in which the main...
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