Dataset for the paper "A Dataset and Baseline Approach for Identifying Usage States from Non-Intrusive Power Sensing With MiDAS IoT-based Sensors"

The state identification problem seeks to identify power usage patterns of any system, like buildings or factories, of interest. In this challenge paper, we make power usage dataset available from 8 institutions in manufacturing, education and medical institutions from the US and India, and an initial unsupervised machine learning based solution as a baseline for the community to accelerate research in this area.

Additional data for more days (from January-August 2022) for the same locations presented in our paper can be requested for research purposes by contacting the authors.

Our GitHub repository - https://github.com/ai4society/PowerIoT-State-Identification

If you are using this data, please cite,

@inproceedings{midas-state-id,

author = {Bharath C Muppasani and C J Anand and Chinmayi Appajigowda  and Biplav Srivastava  and Lokesh Johri},

title = {A Dataset and Baseline Approach for Identifying Usage States from Non-Intrusive Power Sensing With MiDAS IoT-based Sensors},

booktitle = {Proc. Thirty-Fifth Annual Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI-23)},
year = {2023},
keywords = {Signal Processing (eess.SP), Artificial Intelligence (cs.AI), Machine Learning (cs.LG), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences},
copyright = {Creative Commons Attribution Non Commercial No Derivatives 4.0 International}

}