Front Matter -- Review and Analysis of Machine Learning Based Techniques for Load Forecasting in Smart Grid System / KV Shihabudheen, S Sheik Mohammed -- Energy Optimized Techniques in Cloud and Fog Computing / NM Balamurugan, TKS Rathish babu, K Maithili, M Adimoolam -- Energy-Efficient Cloud Computing Techniques for Next Generation / Praveen Mishra, M Sivaram, M Arvindhan, A Daniel, Raju Ranjan -- Energy Optimization Using Silicon Dioxide Composite and Analysis of Wire Electrical Discharge Machining Characteristics / MS Kumaravel, N Alagumurthi, P Mathiyalagan -- Optimal Planning of Renewable DG and Reconfiguration of Distribution Network Considering Multiple Objectives Using PSO Technique for Different Scenarios / Balmukund Kumar, Aashish Kumar Bohre -- Investigation of Energy Optimization for Spectrum Sensing in Distributed Cooperative IoT Network Using Deep Learning Techniques / M Pavithra, R Rajmohan, T Ananth Kumar, S Usharani, P Manju Bala -- Road Network Energy Optimization Using IoT and Deep Learning / N M Balamurugan, N Revathi, R Gayathri -- Energy Optimization in Smart Homes and Buildings / S Sathya, G Karthi, A Suresh Kumar, S Prakash -- Machine Learning Based Approach for Energy Management in the Smart City Revolution / S Deepica, S Kalavathi, J Angelin Blessy, D Maria Manuel Vianny -- Design of an Energy Efficient IoT System for Poultry Farm Management / G Rajakumar, G Gnana Jenifer, T Ananth Kumar, T S Arun Samuel -- IoT Based Energy Optimization in Smart Farming Using AI / N Padmapriya, T Ananth Kumar, R Aswini, R Rajmohan, P Kanimozhi, M Pavithra -- Smart Energy Management Techniques in Industries 5.0 / S Usharani, P Manju Bala, T Ananth Kumar, R Rajmohan, M Pavithra -- Energy Optimization Techniques in Telemedicine Using Soft Computing / R Indrakumari -- Healthcare / G Vallathan, Senthilkumar Meyyappan, T Rajani -- Case Study of Energy Optimization / Pedram Asef -- About the Editors -- Index -- Also of Interest

Includes index.

Online resource; title from PDF title page (John Wiley, viewed October 10, 2022).

Energy optimization and consumption prediction are necessary to prevent energy waste, schedule energy usage, and reduce the cost. Today, smart computing technologies are slowly replacing the traditional computational methods in energy optimization, consumption, scheduling, and usage. Smart computing is an important core technology in today's scientific and engineering environment. Smart computation techniques such as artificial intelligence, machine learning, deep learning and Internet of Things (IoT) are the key role players in emerging technologies across different applications, industries, and other areas. These newer, smart computation techniques are incorporated with traditional computation and scheduling methods to reduce power usage in areas such as distributed environment, healthcare, smart cities, agriculture and various functional areas. The scope of this book is to bridge the gap between traditional power consumption methods and modern consumptions methods using smart computation methods. This book addresses the various limitations, issues and challenges of traditional energy consumption methods and provides solutions for various issues using modern smart computation technologies. These smart technologies play a significant role in power consumption, and they are cheaper compared to traditional technologies. The significant limitations of energy usage and optimizations are rectified using smart computations techniques, and the computation techniques are applied across a wide variety of industries and engineering areas.

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