Patent: 赵子健, 朱光旭, 沈超, 史清江, 韩凯峰 "人员检测方法、装置、电子设备以及存储介质"（申请号：2023116499786，2024）
Device: ESP32-S3 (supports other ESP32 models)
First, flash esp-csi/examples/get-started/csi_recv_router at master · espressif/esp-csi (github.com) onto the ESP32 and connect it to the router.
Then, use the system with the following command:
python main.py --port <port>
For more parameters, you can obtain help with:
python main.py --helpNote: After clicking each module button, the program will start running. To stop the program, please click the corresponding button again. Do not directly close the interface!
- CSI Display: Displays CSI amplitude, phase, and spectrum data.
- LoFi: 2D Image-Based Wi-Fi Positioning Tag Generator: Generates positioning tags using a 2D image. Users can specify anchor points in the physical world and their corresponding pixel coordinates.
- Intrusion Detection: Monitors and detects unauthorized access or breaches in a designated area.
- Fall Detection: Identifies and alerts on incidents of falling, utilizing wireless channel state information.
- Breathing Detection: Monitors and analyzes breathing patterns.
- Gesture Recognition / Action Recognition / Person Recognition / Population Estimation: Advanced functionalities for recognizing gestures, actions, individuals, and estimating the number of people in a given space. (Pending updates)
- Trajectory Tracking: In development, this feature will track the movement paths of individuals or objects.
Note: The functionalities listed above are currently under development and will be updated as progress is made.
Overview
@article{zhao2025short,
title={A Short Overview of Multi-Modal Wi-Fi Sensing},
author={Zhao, Zijian},
journal={arXiv preprint arXiv:2505.06682},
year={2025}
}
Fall Detection
@inproceedings{cai2023falldewideo,
title={FallDeWideo: Vision-Aided Wireless Sensing Dataset for Fall Detection with Commodity Wi-Fi Devices},
author={Cai, Zhijie and Chen, Tingwei and Zhou, Fujia and Cui, Yuanhao and Li, Hang and Li, Xiaoyang and Zhu, Guangxu and Shi, Qingjiang},
booktitle={Proceedings of the 3rd ACM MobiCom Workshop on Integrated Sensing and Communications Systems},
pages={7--12},
year={2023}
}
@article{chen2024deep,
title={Deep learning-based fall detection using commodity Wi-Fi},
author={Chen, Tingwei and Li, Xiaoyang and Li, Hang and Zhu, Guangxu},
journal={Journal of Information and Intelligence},
year={2024},
publisher={Elsevier}
}
@article{陈廷尉2023基于无线信道状态信息的跌倒检测,
title={基于无线信道状态信息的跌倒检测},
author={陈廷尉 and 李阳 and 韩凯峰 and 李晓阳 and 李航 and 朱光旭},
journal={信息通信技术与政策},
volume={49},
number={9},
pages={67},
year={2023}
}
Gesture Recognition / Action Recognition / Person Recognition / Population Estimation
@inproceedings{zhang2023ratiofi,
title={RatioFi: Unlocking the Potential of WiFi CSI},
author={Zhang, Dengtao and Cai, Zhijie and Zhu, Guangxu and Li, Hang and Li, Xiaoyang and Shi, Qingjiang and Shen, Chao},
booktitle={2023 International Conference on Ubiquitous Communication (Ucom)},
pages={421--425},
year={2023},
organization={IEEE}
}
@inproceedings{zhao2024finding,
title={Finding the missing data: A bert-inspired approach against package loss in wireless sensing},
author={Zhao, Zijian and Chen, Tingwei and Meng, Fanyi and Li, Hang and Li, Xiaoyang and Zhu, Guangxu},
booktitle={IEEE INFOCOM 2024-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},
pages={1--6},
year={2024},
organization={IEEE}
}
@article{zhao2024mining,
title={CSI-BERT2: A BERT-Inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing},
author={Zhao, Zijian and Meng, Fanyi and Lyu, Zhonghao and Li, Hang and Li, Xiaoyang and Zhu, Guangxu},
journal={arXiv preprint arXiv:2412.06861},
year={2024}
}
@article{zhao2025crossfi,
title={Crossfi: A cross domain wi-fi sensing framework based on siamese network},
author={Zhao, Zijian and Chen, Tingwei and Cai, Zhijie and Li, Xiaoyang and Li, Hang and Chen, Qimei and Zhu, Guangxu},
journal={IEEE Internet of Things Journal},
year={2025},
publisher={IEEE}
}
@misc{zhao2025knnmmdcrossdomainwireless,
title={KNN-MMD: Cross Domain Wireless Sensing via Local Distribution Alignment},
author={Zijian Zhao and Zhijie Cai and Tingwei Chen and Xiaoyang Li and Hang Li and Qimei Chen and Guangxu Zhu},
year={2025},
eprint={2412.04783},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.04783},
}
@INPROCEEDINGS{11149311,
author={Zhao, Zijian and Cai, Zhijie and Chen, Tingwei and Li, Xiaoyang and Li, Hang and Chen, Qimei and Zhu, Guangxu},
booktitle={2025 IEEE/CIC International Conference on Communications in China (ICCC)},
title={Does MMD Really Align? A Cross Domain Wireless Sensing Method via Local Distribution},
year={2025},
volume={},
number={},
pages={1-6},
keywords={Wireless communication;Training;Wireless sensor networks;Codes;Sensitivity;Gesture recognition;Nearest neighbor methods;Stability analysis;Sensors;Wireless fidelity;Few-shot Learning;K-Nearest Neighbors;Maximum Mean Discrepancy;Cross-domain Wireless Sensing;Channel Statement Information},
doi={10.1109/ICCC65529.2025.11149311}}
Tracking / Localization
@article{zhao2024lofi,
title={LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking},
author={Zhao, Zijian and Chen, Tingwei and Meng, Fanyi and Cai, Zhijie and Li, Hang and Li, Xiaoyang and Zhu, Guangxu},
journal={arXiv preprint arXiv:2412.05074},
year={2024}
}