2019/07/27 by Delaram Amiri, Arman Anzanpour, Amiri, Delaram +11
Computer Science · Engineering · #Context-Aware Activity Recognition Systems #FOS: Computer and information sciences #FOS: Electrical engineering #Green IT and Sustainability #Human-Computer Interaction (cs.HC) #IoT and Edge/Fog Computing #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1907.11989
openalex publication_date 2019/07/27 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28
Recent advances in the Internet of Things (IoT) technologies have enabled the\nuse of wearables for remote patient monitoring. Wearable sensors capture the\npatient's vital signs, and provide alerts or diagnosis based on the collected\ndata. Unfortunately, wearables typically have limited energy and computational\ncapacity, making their use challenging for healthcare applications where\nmonitoring must continue uninterrupted long time, without the need to charge or\nchange the battery. Fog computing can alleviate this problem by offloading\ncomputationally intensive tasks from the sensor layer to higher layers, thereby\nnot only meeting the sensors' limited computational capacity but also enabling\nthe use of local closed-loop energy optimization algorithms to increase the\nbattery life.\n