Exploring the effects of below-freezing temperatures on smartphone usage

While the use of smartphones in extreme temperatures does not necessarily occur every day nor in all parts of the world, numerous use cases can be highlighted where the use of smartphones in cold temperatures is mandatory. Modern smartphones are designed to function in a wide range of temperatures, but when exposed to extreme cold temperatures the performance and reliability can significantly suffer. This paper presents a controlled laboratory experiment, using a clinical cold chamber to expose seven smartphone models to both medium cold (0 degrees C to -20 degrees C) and extreme cold (-30 degrees C) environments. The results showcase the smartphones' sensing software's lack of awareness of the cold environment, as well as reliability issues in the form of device crashes across the whole range of tested devices. We present a strategy for implementing monitoring application designs to both appropriately sense the effect of cold environments, as well as predicting device shutdowns in extreme cold. (C) 2021 The Authors. Published by Elsevier B.V.Peer reviewe

Pervasive Data Science on the Edge

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The hidden image of mobile apps : geographic, demographic, and cultural factors in mobile usage

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Evaluating Energy-Efficiency using Thermal Imaging

Energy-efficiency remains a critical design consideration for mobile and wearable systems, particularly those operating continuous sensing. Energy footprint of these systems has traditionally been measured using hardware power monitors (such as Monsoon power meter) which tend to provide the most accurate and holistic view of instantaneous power use. Unfortunately applicability of this approach is diminishing due to lack of detachable batteries in modern devices. In this paper, we propose an innovative and novel approach for assessing energy footprint of mobile andwearable systems using thermal imaging. In our approach, an off-the-shelf thermal camera is used to monitor thermal radiation of a device while it is operating an application. We develop the general theory of thermal energy-efficiency, and demonstrate its feasibility through experimental benchmarks where we compare energy estimates obtained through thermal imaging against a hardware power monitor.Peer reviewe

Hot or Not? Robust and Accurate Continuous Thermal Imaging on FLIR cameras

Wearable thermal imaging is emerging as a powerful and increasingly affordable sensing technology. Current thermal imaging solutions are mostly based on uncooled forward looking infrared (FLIR), which is susceptible to errors resulting from warming of the camera and the device casing it. To mitigate these errors, a blackbody calibration technique where a shutter whose thermal parameters are known is periodically used to calibrate the measurements. This technique, however, is only accurate when the shutter's temperature remains constant over time, which rarely is the case. In this paper, we contribute by developing a novel deep learning based calibration technique that uses battery temperature measurements to learn a model that allows adapting to changes in the internal thermal calibration parameters. Our method is particularly effective in continuous sensing where the device casing the camera is prone to heating. We demonstrate the effectiveness of our technique through controlled benchmark experiments which show significant improvements in thermal monitoring accuracy and robustness.Peer reviewe