Multi-sensor based ambient assisted living system

buir.advisorÇetin, A. Enis
dc.contributor.authorYazar, Ahmet
dc.date.accessioned2016-01-08T18:25:58Z
dc.date.available2016-01-08T18:25:58Z
dc.date.issued2013
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2013.en_US
dc.descriptionIncludes bibliographical references leaves 76-84.en_US
dc.description.abstractAn 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 via telephone lines. The resulting AAL system is a low-cost and privacy-friendly system thanks to the types of sensors used.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T18:25:58Z (GMT). No. of bitstreams: 1 0006578.pdf: 7225934 bytes, checksum: f92d941440d5f77c2d12d88b988ad8ec (MD5)en
dc.description.statementofresponsibilityYazar, Ahmeten_US
dc.format.extentxvi, 84 leaves, graphsen_US
dc.identifier.urihttp://hdl.handle.net/11693/15878
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAmbient assisted livingen_US
dc.subjectvibration sensoren_US
dc.subjectpassive infrared sensoren_US
dc.subjectcomplex wavelet transformen_US
dc.subjectsupport vector machinesen_US
dc.subjectfalling person detectionen_US
dc.subjectMarkov modelsen_US
dc.subjecthuman footstep detectionen_US
dc.subjectunusual inactivity detectionen_US
dc.subjectindoor flooding detectionen_US
dc.subject.lccQA76.9.A48 Y39 2013en_US
dc.subject.lcshAmbient intelligence.en_US
dc.subject.lcshAssistive computer technology.en_US
dc.subject.lcshHome automation.en_US
dc.subject.lcshSensor networks.en_US
dc.subject.lcshSignal processing--Digital techniques.en_US
dc.subject.lcshHuman locomotion.en_US
dc.subject.lcshDetectors--Design and construction.en_US
dc.subject.lcshIntelligent control systems.en_US
dc.subject.lcshMotion control devices.en_US
dc.subject.lcshSensors.en_US
dc.titleMulti-sensor based ambient assisted living systemen_US
dc.typeThesisen_US
thesis.degree.disciplineElectrical and Electronic Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

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