TY - GEN
T1 - Indoor Human Identification Using Advanced Machine-Learning-Based Strategy
AU - Al-Naimi, Ibrahim
AU - Baniyounis, Mohammed
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Major research efforts have been exerted to improve the accuracy of indoor person identification and facilitate the context-aware home services. These researches suffered from the low value of Correct Classification Rate (CCR), due to several technical reasons. In this paper, an advanced system combines pyroelectric infrared and floor-pressure sensors is proposed to identify persons in smart homes. Cooperative Multi-sensor strategy has been adopted to extract explicit information indicating the person's body size to improve the identification accuracy. A novel Machine-Learning-Based strategy is proposed to extract distinctive feature vector that represents the person's body size. Neural Network (NN) and Support Vector Machine (SVM) are used to improve the CCR of person identification. A prototype was designed and implemented. In addition, several test cases were conducted to examine and evaluate the effectiveness of the proposed system in identifying persons with high values of CCR.
AB - Major research efforts have been exerted to improve the accuracy of indoor person identification and facilitate the context-aware home services. These researches suffered from the low value of Correct Classification Rate (CCR), due to several technical reasons. In this paper, an advanced system combines pyroelectric infrared and floor-pressure sensors is proposed to identify persons in smart homes. Cooperative Multi-sensor strategy has been adopted to extract explicit information indicating the person's body size to improve the identification accuracy. A novel Machine-Learning-Based strategy is proposed to extract distinctive feature vector that represents the person's body size. Neural Network (NN) and Support Vector Machine (SVM) are used to improve the CCR of person identification. A prototype was designed and implemented. In addition, several test cases were conducted to examine and evaluate the effectiveness of the proposed system in identifying persons with high values of CCR.
KW - floor-pressure sensor
KW - identification
KW - Neural network
KW - pyroelectric infrared (PIR) sensor
UR - http://www.scopus.com/inward/record.url?scp=85143770521&partnerID=8YFLogxK
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U2 - 10.1109/SSD54932.2022.9955720
DO - 10.1109/SSD54932.2022.9955720
M3 - Conference contribution
AN - SCOPUS:85143770521
T3 - 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022
SP - 1924
EP - 1928
BT - 2022 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2022
Y2 - 6 May 2022 through 10 May 2022
ER -