دانلود کتاب مدیریت پایدار پسماندهای الکترونیکی

This book is organized into nineteen chapters. In Chapter 1, a study explores the published works of AI with EMS, RES, and SG, their effects, and their reasons. AI technology has evolved quickly in the last several decades, and its applications have rapidly increased in modern industrial systems. Similarly, nature-inspired and biological systems denote an unlimited inspiration source for developing technical systems that lead human civilization’s progress and shape our thinking style. In Chapter 2, the author introduces the concept of the progress of artificial intelligence and blockchain technology unlocking prospects toward thermal marketing accuracy. The Artificial Neural Network (ANN) is crucial for improving biomass energy prediction research. This study emphasizes the steps in modeling and using ANN in forecasting biomass thermal values. Several research gaps in the present state of the investigation on ANN, in terms of biomass and guidance for additional research, are identified. Chapter 3 will also go over growing environmental concerns over the use and depletion of non-renewable fuel sources, together with the increasing price of oil and instabilities in the oil markets, which have recently stimulated interest in producing sustainable energy sources in the form of biofuels derived from plants. Ethanol developed from lignocellulosic biomass has characteristic benefits of safety, economics, and being more environmentally friendly than fossil fuels. The lignocellulosic materials comprise 50% cellulose, 25% hemicellulose, and 25% lignin. In Chapter 4, a novel approach for a Smart Home Energy Management System for Energy Consumption Prediction is proposed using an Enhanced Bayesian Linear Regression Machine Learning algorithm (EBLRML). The residual sum of squares shows the significant linear model difference from the existing application of ML techniques where the coefficient based on correlation is lower, and the energy consumption is calculated to achieve the best-fit model. In Chapter 5, the author explains that using artificial intelligence today improves all the limitations outlined in the problem statements above. Machine learning algorithms have been used to predict crop cultivation, optimization metrics, irrigation levels, and so on, but very little has been done to predict weather and forecast agriculture. By using advanced sensors connected to a network, it is possible to identify bad weather that may threaten agriculture itself at an earlier stage. A live farm’s features can improve crop exploitation earlier in the growing cycle. In Chapter 6, the author explains that energy consumption has risen exponentially, putting pressure on the utilities to increase energy production. One of the significant concerns of the current day is that energy conservation and monitoring systems have been developed to optimize the increasing demand for energy and its consumption. Energy management systems help to decrease current consumption, prevent energy wastage, and enable the optimized utilization of available resources. In Chapter 7, the author explains a significant impediment to the widespread adoption of these energy sources in their high integration costs. However, artificial intelligence (AI) explanations and data-intensive expertise are currently being deployed in various sectors of the electrical significance chain and, given the future smart grid’s increasing complexity and data generation capacity, have the probability of adding substantial value to the system. Chapter 8 provides detailed explanations of critical issues influencing India’s entire e-waste value chain, including a lack of data inventorization, unlawful disposal, and treatment choices. As a result, this study focuses on strategic interventions that comply with existing legislation and are necessary for a long-term e-waste value chain, secure resources, social well-being, reduced environmental consequences, and overall sustainable development. Apart from these, other methods for recycling e-waste are also incorporated to maintain the environment’s integrity. Chapter 9 discusses the environmental concerns linked with discarded electronic equipment, sometimes known as “e-waste,” in detail. In addition, the development of e-waste both now and in the future, as well as any environmental difficulties that may come from its management and disposal approaches, are investigated, and the existing programs for the management of e-waste are discussed.