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Smartphone-Based Anomalous Human Activity Detection and Prediction

By M. Gupta, S. Saha, V. Goyal, S. Kaul, K. Sriram, G. Gupta and S. Bali

Abstract

We propose a framework for real-time detection and prediction of anomalous human activity (AHA) using smartphones. AHA is any activity that indicates harm, or possibility thereof, to the individual carrying the phone. Examples of such activities include being pushed, being dragged and lifted. The above examples are of aberrant human mobility. Other examples of anomalous human activity, which can be in response to harm or in expectation of harm, include expression of fear (screaming, nervous walk) and flight. Our motivation originates in the staggering numbers of assaults on women in the metropolis of Delhi [1]. On the other hand, we have the proliferation of affordable smartphones that come with a variety of sensors including the microphone and the accelerometer. The challenge is to achieve a high detection rate of anomalous activity at a small false alarm rate, using sensors in a

Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.415.5008
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