Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/78415
Title: Human activity recognition based on smartphone sensors
Authors: Rajendran, Abinaya
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: Human Activity Recognition otherwise called as HAR is a challenging research field that promotes quality of life by means of ambient intelligence and assisted living. The fundamental step for the development of intelligent system is to understand and start learning the human activities in the real time environment. Numerous ways for recognizing the human activities are being proposed by the researchers over the last decade. Some of these methods are discussed in this dissertation work and an attempt has been made to utilize them to recognize the human activities. The main goal of the work is to utilize the smart phone as data collection module and classify the basic activities based on the collected information. An android application has been created for the data collection which is capable of running in majority of the smart phones in the market. The designed framework is used to take data from five subjects of similar age. The basic human activities like walking, sitting, walking upstairs, downstairs and running are classified using the combination of the sensor data collected from the Smart-phone.
URI: http://hdl.handle.net/10356/78415
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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FINAL DISSERTATION REPORT_RAJENDRAN ABINAYA_G1801261A.pdf
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