Multi-sensor Based Ambient Assisted Living System

MULTI-SENSOR BASED AMBIENT ASSISTED LIVING SYSTEM Ahmet Yazar M.S. in Electrical and Electronics Engineering Supervisor: Prof. Dr. A. Enis Çetin July, 2013 An important goal of Ambient Assisted Living (AAL) research is to contribute to the quality of life of the elderly and handicapped people and help them to maintain an independent lifestyle with the use of sensors, signal processing and the available telecommunications infrastructure. From this perspective, detection of unusual human activities such as falling person detection has practical applications. In this thesis, a low-cost AAL system using vibration and passive infrared (PIR) sensors is proposed for falling person detection, human footstep detection, human motion detection, unusual inactivity detection, and indoor flooding detection applications. For the vibration sensor signal processing, various frequency analysis methods which consist of the discrete Fourier transform (DFT), mel-frequency cepstral coefficients (MFCC), discrete wavelet transform (DWT) with different filter-banks, dual-tree complex wavelet transform (DT-CWT), and single-tree complex wavelet transform (ST-CWT) are compared to each other to obtain the best possible classification result in our dataset. Adaptive-threshold based Markov model (MM) classifier is preferred for the human footstep detection. Vibration sensor based falling person detection system employs Euclidean distance and support vector machine (SVM) classifiers and these classifiers are compared to each other. PIR sensors are also used for falling person detection and this system employs two PIR sensors. To achieve the most reliable system, a multi-sensor based falling person detection system which employs one vibration and two PIR sensors is developed. PIR sensor based system has also the capability of detecting uncontrolled flames and this system is integrated to the overall system. The proposed AAL system works in real-time on a standard personal computer or chipKIT Uno32 microprocessors without computers. A network is setup for the communication of the Uno32 boards which are connected to different sensors. The main processor gives final decisions and emergency alarms are transmitted to outside of the smart home using the auto-dial alarm system iii