Khan, Md Abdullah Al HafizKukkapalli, RuthvikWaradpande, PiyushKulandaivel, SekarBanerjee, NilanjanRoy, NirmalyaRobucc, Ryan2018-09-042018-09-042016-07-20M. A. A. H. Khan et al., "RAM: Radar-based activity monitor," IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, San Francisco, CA, 2016, pp. 1-9.doi: 10.1109/INFOCOM.2016.7524361http://hdl.handle.net/11603/11212© 2016 IEEE, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer CommunicationsActivity recognition has applications in a variety of human-in-the-loop settings such as smart home health monitoring, green building energy and occupancy management, intelligent transportation, and participatory sensing. While fine-grained activity recognition systems and approaches help enable a multitude of novel applications, discovering them with non-intrusive ambient sensor systems pose challenging design, as well as data processing, mining, and activity recognition issues. In this paper, we develop a low-cost heterogeneous Radar based Activity Monitoring (RAM) system for recognizing fine-grained activities. We exploit the feasibility of using an array of heterogeneous micro-doppler radars to recognize low-level activities. We prototype a short-range and a long-range radar system and evaluate the feasibility of using the system for fine-grained activity recognition. In our evaluation, using real data traces, we show that our system can detect fine-grained user activities with 92.84% accuracy.9 PAGESen-USThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.Doppler radarRandom access memoryLegged locomotionFeature extractionIEEE 802.11 StandardMobile Pervasive & Sensor Computing LabText