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What is Waste-to-Energy (WtE)

Methodologies, Frameworks, and Applications of Machine Learning
Is a sustainable approach to managing solid waste by converting it into usable energy. This process involves the combustion or biological conversion of municipal solid waste, biomass, or other types of waste materials to generate electricity or heat. WtE not only reduces the volume of waste destined for landfills but also harnesses the energy content within waste to produce power, contributing to renewable energy goals and providing an environmentally conscious alternative to traditional waste disposal methods.
Published in Chapter:
Waste-to-Energy Solutions Harnessing IoT and ML for Sustainable Power Generation in Smart Cities
Tarun Kumar Vashishth (IIMT University, India), Vikas Sharma (IIMT University, India), Kewal Krishan Sharma (IIMT University, India), Bhupendra Kumar (IIMT University, India), Sachin Chaudhary (IIMT University, India), and Rajneesh Panwar (IIMT University, India)
Copyright: © 2024 |Pages: 22
DOI: 10.4018/979-8-3693-1062-5.ch007
Abstract
This chapter explores waste-to-energy (WtE) solutions empowered by the integration of internet of things (IoT) and machine learning (ML) for sustainable power generation in smart cities. By leveraging IoT sensors, real-time data acquisition optimizes waste management processes, and ML algorithms enhance operational efficiency. The potential impact of these technologies on WtE's future includes predictive maintenance, waste sorting automation, and adaptive energy production. The role of WtE in smart cities extends to decentralized energy generation, integrated waste management, and fostering circular economy principles. This study calls for further research and the adoption of sustainable practices to propel WtE as a key component in the future energy landscape of smart and resilient urban environments.
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