Abstract

Energy waste in the hospitality sector is a serious issue that this work takes on by introducing machine vision to
spot problems automatically. Data on energy use and everyday operations was gathered and analysed, and the
study ends up flagging those unexpected inefficiencies, sometimes in surprising areas. In most cases, using live
visual data to guide specific changes slashes energy waste by about 30%, which naturally cuts costs while nudging
establishments toward greener practices. The findings also suggest that pairing smart automated detection with
traditional methods can shift the energy efficiency game, not just in hotels but, quite frankly, in industries like
healthcare, where the environmental impact is huge. By putting together a reliable automated detection system,
the research shakes up the usual ways of managing energy and even points the way for similar strategies in other
sectors. More broadly, these results push for more responsible, eco-friendly practices that help meet global
sustainability goals and may even boost public health through reduced emissions and smarter resource use.
Overall, the evidence leans toward embracing machine vision as a key tool in rethinking energy consumption,
potentially transforming how various industries handle their energy needs.