TY - GEN
T1 - Towards Large-Scale Wireless Sensing in Smart Buildings Using LoRa Signals
AU - Xue, Xinyu
AU - Chang, Zhaoxin
AU - Ma, Xujun
AU - Wang, Pei
AU - Zhang, Fusang
AU - Jouaber, Badii
AU - Zhang, Daqing
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026/1/1
Y1 - 2026/1/1
N2 - With the increased need for intelligent functions in smart buildings, the ability to sense the states of human subjects becomes essential. In recent years, wireless signals have demonstrated strong capability for contactless sensing. However, most wireless sensing systems currently focus on room-level scenarios. The deployment challenges and solutions in large-scale scenarios have not been sufficiently investigated. In this paper, we take the first step to explore the feasibility of utilizing LoRa signals for large-scale sensing, leveraging their advantages in wide-area sensing capabilities. However, given the fixed deployment in buildings, the sensing coverage of each device is likely to mismatch with the desired sensing area of interest (AoI). To address this challenge, we first investigate the factors affecting sensing coverage. Then, we propose to control the sensing coverage by adjusting hardware parameters, enabling human presence detection within the desired area. The effectiveness of the proposed method is validated through benchmark experiments and two case studies in real-world environments.
AB - With the increased need for intelligent functions in smart buildings, the ability to sense the states of human subjects becomes essential. In recent years, wireless signals have demonstrated strong capability for contactless sensing. However, most wireless sensing systems currently focus on room-level scenarios. The deployment challenges and solutions in large-scale scenarios have not been sufficiently investigated. In this paper, we take the first step to explore the feasibility of utilizing LoRa signals for large-scale sensing, leveraging their advantages in wide-area sensing capabilities. However, given the fixed deployment in buildings, the sensing coverage of each device is likely to mismatch with the desired sensing area of interest (AoI). To address this challenge, we first investigate the factors affecting sensing coverage. Then, we propose to control the sensing coverage by adjusting hardware parameters, enabling human presence detection within the desired area. The effectiveness of the proposed method is validated through benchmark experiments and two case studies in real-world environments.
KW - LoRa Signal
KW - Sensing Coverage
KW - Sensing-signal-to-noise Ratio
KW - Smart Building
KW - Wireless Sensing
UR - https://www.scopus.com/pages/publications/105028088328
U2 - 10.1007/978-981-95-2581-2_11
DO - 10.1007/978-981-95-2581-2_11
M3 - Conference contribution
AN - SCOPUS:105028088328
SN - 9789819525805
T3 - Communications in Computer and Information Science
SP - 160
EP - 173
BT - Artificial Intelligence of Things and Systems - 3rd International Conference, AIoTSys 2025, Proceedings
A2 - Liu, Sicong
A2 - Zheng, Xiaolong
A2 - Ma, Dong
A2 - Wu, Yuezhong
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2025
Y2 - 15 August 2025 through 17 August 2025
ER -