Abstract:
This study examines how machine learning and artificial intelligence (AI) may be used to solve urgent worldwide issues with waste and energy management. It presents a tho...Show MoreMetadata
Abstract:
This study examines how machine learning and artificial intelligence (AI) may be used to solve urgent worldwide issues with waste and energy management. It presents a thorough framework for employing AI technology to track and optimize trash production and energy use in residential communities. The framework reduces energy consumption and increases waste management efficiency by using sensors, data processing, predictive modelling, and real-time monitoring to enable data-driven decision-making. It emphasizes how AI has the power to transform conventional methods and usher in a more sustainable future. The study offers a cutting-edge framework for waste and energy management monitoring that is based on machine learning and provides real-time insights and forecasts to help with decision-making. Constant data analysis maximizes the use of resources, resulting in reduced costs, increased operational effectiveness, and advantages for sustainability. Although there are still obstacles to overcome, such as data security and upfront costs, this paradigm is an essential first step towards effective and accountable resource management.
Published in: 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023)
Date of Conference: 21-23 December 2023
Date Added to IEEE Xplore: 30 August 2024
Electronic ISBN:978-1-83724-025-8