A Survey of Machine Learning (ML) in Sustainable Systems

Abstract

Machine learning has the ability to greatly improve sustainable systems by anticipating and maximizing the use of resources, boosting productivity, and reducing waste. Along with a review of earlier research on the incorporation of machine learning into sustainable systems, a case study of how machine learning was used to lower energy use in a residential structure is presented. The results show that machine learning can be used to generate significant cost reductions and energy efficiency. Wearable technology has added a completely new dimension to the already broad category of personal electronics. The mobile phone gave technology real individuality. Because so many services are designed around mobile phones, the market has opened up for a brand-new personalized experience utilizing wearable technologies. Fabric sensors may now be combined with wearable microcontrollers like the flora and lily pad to monitor stretch, pressure, bend, and even the direction that the body is being braced. The connections between them are based on conductive threads that follow the curve of the fabric. We'll examine how different teams used their in-depth understanding of wearable technologies to accomplish their goals in this study.