ABODE-Net: An Attention-based Deep Learning Model for Non-intrusive Building Occupancy Detection Using Smart Meter Data

Zhirui Luo, Ruobin Qi, Qingqing Li, Jun Zheng, Sihua Shao

Occupancy information is useful for efficient energy management in the building sector. The massive high-resolution electrical power consumption data collected by smart meters in the advanced metering infrastructure (AMI) network make it possible to infer buildings’ occupancy status in a on-intrusive way. In this paper, we propose a deep leaning model called ABODE-Net which employs a novel Parallel Attention (PA) block for building occupancy detection using smart meter data. The PA block combines the temporal, variable, and channel attention modules in a parallel way to signify important features for occupancy detection. We adopt two smart meter datasets widely used for building occupancy detection in our performance evaluation. A set of state-ofthe-art shallow machine learning and deep learning models are included for performance comparison. The results show that ABODE-Net significantly outperforms other models in all experimental cases, which proves its validity as a solution for non-intrusive building occupancy detection.

Luo, Z., Qi, R, Q. Li, Zheng, J., Shao, S. (2023). ABODE-Net: An Attention-based Deep Learning Model for Non-intrusive Building Occupancy Detection Using Smart Meter Data. In: Qiu, M., Lu, Z., Zhang, C. (eds) Smart Computing and Communication. SmartCom 2022. Lecture Notes in Computer Science, vol 13828. Springer, Cham. https://doi.org/10.1007/978-3-031-28124-2_15

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Requirements

conda create -n abode_net python=3.11
conda activate abode_net
pip install -r requirements.txt

Run Demo

python train.py --model ABODE_Net --dataset ECO

Citation

@InProceedings{10.1007/978-3-031-28124-2_15,
    author="Luo, Zhirui
    and Qi, Ruobin
    and Li, Qingqing
    and Zheng, Jun
    and Shao, Sihua",
    editor="Qiu, Meikang
    and Lu, Zhihui
    and Zhang, Cheng",
    title="ABODE-Net: An Attention-based Deep Learning Model for Non-intrusive Building Occupancy Detection Using Smart Meter Data",
    booktitle="Smart Computing and Communication",
    year="2023",
    publisher="Springer Nature Switzerland",
    address="Cham",
    pages="152--164",
}