University of Twente Student Theses


Unobtrusive sensing using WiFi signals

Bagave, Prachi (2018) Unobtrusive sensing using WiFi signals.

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Abstract:Detecting human activities has been an actively growing research area since a few decades. It opens a wide area of applications in health care, robotics, human-media interaction, surveillance and sports. People have started accepting these technologies, either as logging their step counts or even monitoring their baby’s sleep cycle. The drawback of such devices is that each device with a different purpose comes with a new hardware and thus indulges additive costs. This project proposes to use WiFi for a device-free low-cost activity recognition system as it is easily available in offices and homes now a days. It is also ubiquitous in nature as it collects information from the environment while providing Internet. The underlying idea behind this approach is to acquire and model the changes in the multi-path WiFi radio waves due to human motion. The existing systems are based on a few basic activities like sitting, standing, running or walking for which machine learning models are trained and used for classification. This project attempts to find a more generic approach for activity recognition. Each activity is considered as a sequence of discrete static postures over time. For example walking, jogging and running are combination of same postures at different pace. The project mainly focuses on reliability of a particular application so that it could be used in real time. It is observed that static postures have limited features and are more dependent on the environmental factors and system fluctuations than dynamic activities hence less reliable.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:50 technical science in general
Programme:Embedded Systems MSc (60331)
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