scholarly journals TriboMotion: A Self-Powered Triboelectric Motion Sensor in Wearable Internet of Things for Human Activity Recognition and Energy Harvesting

2018 ◽  
Vol 5 (6) ◽  
pp. 4441-4453 ◽  
Author(s):  
Hui Huang ◽  
Xian Li ◽  
Si Liu ◽  
Shiyan Hu ◽  
Ye Sun
IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fahd N. Al-Wesabi ◽  
Amani Abdulrahman Albraikan ◽  
Anwer Mustafa Hilal ◽  
Asma Abdulghani Al-Shargabi ◽  
Saleh Alhazbi ◽  
...  

2019 ◽  
Vol 5 (1) ◽  
pp. 1-9
Author(s):  
Mohammad Iqbal ◽  
Chandrawati Putri Wulandari ◽  
Wawan Yunanto ◽  
Ghaluh Indah Permata Sari

Discovering rare human activity patterns—from triggered motion sensors deliver peculiar information to notify people about hazard situations. This study aims to recognize rare human activities using mining non-zero-rare sequential patterns technique. In particular, this study mines the triggered motion sensor sequences to obtain non-zero-rare human activity patterns—the patterns which most occur in the motion sensor sequences and the occurrence numbers are less than the pre-defined occurrence threshold. This study proposes an algorithm to mine non-zero-rare pattern on human activity recognition called Mining Multi-class Non-Zero-Rare Sequential Patterns (MMRSP).  The experimental result showed that non-zero-rare human activity patterns succeed to capture the unusual activity. Furthermore, the MMRSP performed well according to the precision value of rare activities.


2018 ◽  
Vol 17 (6) ◽  
pp. 1353-1368 ◽  
Author(s):  
Sara Khalifa ◽  
Guohao Lan ◽  
Mahbub Hassan ◽  
Aruna Seneviratne ◽  
Sajal K. Das

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