Development of WiFi based human behavior detection in indoor environment

• Main Author: Wang, Dazhuo
• Other Authors: Xie Lihua
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/74686
• Institution: Nanyang Technological University

With the aging of population, fall is becoming a critical risk to this society, as it endangers elder people greatly. As the current technologies are no longer able to meet people’s increasing demand for convenience, privacy, accuracy and safety. A new solution of human behavior detection system need to be developed. This report is about the new solution: WiFi based human behavior detection for fall detection. It introduces about the theories about these technologies, the literature review of research and study done by previous researcher in this field, how the project of development of WiFi based human behavior detection is carried. This report gives detail about the objective and scope of this project and different components that constitutes this system. The first stage of this project is report reading, data collection and data analysis. The second stage is the development of the algorithm, which involves machine learning which could learn the pattern of different waveform, thus being able to decide whether there is any falling event. The third stage is development of the corresponding android application, which involves UDP connection protocol. The last stage is the translation of the algorithm into common used programming language. Finally, the objective of project is fulfilled with the system successfully designed, which is able do learn the waveform pattern and make decision from the structure.