• Shweta tiwari
• sanika gujar
• prerna wakadmane
• Aakash gupta
• pranjali gurnule

The project aims to develop Machine Learning (ML) algorithms to optimize energy consumption .The project seeks to intelligently manage energy usage monitoring , data analysis and predictive modeling . In the complex working environment of the Internet of things (IoT) , there are many differences in the work between many devices , as well as complex associations and energy constraints . The IoT devices will collect energy consumption data and environmental variables , fed into the ML model to create personalized energy optimization strategies for users. The ultimate goal of this project to contribute to a greener and more sustainable future by empowering individuals and businesses to make informed decisions and reduce their carbon footprint. This research paper delves into the fusion of Internet of things (IoT) devices and Machine learning (ML) algorithms to address this pressing challenge By synthesizing IoT data streams with ML models this research define novel strategies for dynamic energy management , load forecasting ,anomaly detection ,and adaptive control .Through an extensive review of existing literature and empirical analysis , this study investigates the efficacy of leveraging IoT sensors ML techniques to optimize usage across diverse domains.

"Energy consumption optimization using iot device", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.l54-l58, April-2024, Available :http://www.jetir.org/papers/JETIR2404B06.pdf

"Energy consumption optimization using iot device", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppl54-l58, April-2024, Available at : http://www.jetir.org/papers/JETIR2404B06.pdf