Official implementation for CIPhy:Causal Intervention with Physical Confounder from IoT Sensor Data for Robust Occupant Information Inference in the proceedings of SenSys 2022.

• Due to SenSys 2022 Organization issue, the paper has not been released in ACM Digital Library yet, please find the paper here in our lab's webpage.
• The backdoor adjustment and baseline model are following the protocol proposed in this AAAI 2016 paper.
• The CORAL model's code is adopted from Dr. Jindong Wang's Repo.
• The data used in this experiment can be found here.

If you find this paper helpful, we are more than happy if you can cite our paper :-)

@inproceedings{hu2022ciphy,
 title={CIPhy:Causal Intervention with Physical Confounder from IoT Sensor Data for Robust Occupant Information Inference},
 author={Hu, Zhizhang and Yu, Tong and Zhang, Ruiyi and Pan, Shijia},
 booktitle={Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems},
 doi={10.1145/3560905.3568304},
 year={2022} 
 }