Abstract
Recent research has shown that the propagation of Radio Frequencies signals is affected by human movements taking place between the RF transmitter and receiver antennas. Artificial intelligence has been widely used to classify the patterns of signal propagation. With the help of a universal software radio peripheral device, a system was developed based on a real-time machine learning classification algorithm to ensure alerts of incidents are received in a timely manner. The machine learning model was built to distinguish between “No Activity” and “Movement” status of a single human subject. The model recorded a high classification accuracy of 97.8 % which enabled an accurate classification of new data in real-time.
Original language | English |
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Title of host publication | 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings |
Publisher | IEEE |
Pages | 2044-2045 |
Number of pages | 2 |
ISBN (Electronic) | 978-1-7281-4670-6 |
DOIs | |
Publication status | Published - 16 Feb 2022 |
Event | 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting - Singapore, Singapore Duration: 4 Dec 2021 → 10 Dec 2021 https://2021apsursi.org/ |
Publication series
Name | 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings |
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Conference
Conference | 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting |
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Abbreviated title | APS/URSI |
Country/Territory | Singapore |
City | Singapore |
Period | 4/12/21 → 10/12/21 |
Internet address |
Bibliographical note
Funding Information:V. ACKNOWLEDGEMENT William Taylor’s studentship is funded by CENSIS UK through Scottish funding council in collaboration with British Telecom. This work is supported in parts by EPSRC EP/T021020/1 and EP/T021063/1
Publisher Copyright:
© 2021 IEEE.
Keywords
- Human motion detection
- Channel State Information
- RF signals
- Machine Learning
- Real-time