Iot-Based Smart Waste Management for Environmental Sustainability

1. Auflage 2022
ISBN: 978-1-032-01391-6
Verlag: CRC Press

Buch, Englisch, 196 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 454 g

Reihe: Smart and Intelligent Computing in Engineering

This book consolidates and summarizes smart technologies like IoT, edge computing, and AI used in different aspects of waste material management, mitigation, and recycling for a sustainable environment. One of the cases explains how IoT-based systems and wireless sensors can be used to continuously detect common pollutants such as volatile organic compounds (VOCs), carbon monoxide, and particulate matter (PM) and how the data collected are used to assess the overall air quality and determine actions for improvements. A collection of practical case studies, this book provides a comprehensive knowledge in smart waste management to readers in universities, research centers, and industries.

Zielgruppe

Academic, Postgraduate, Professional, Professional Practice & Development, and Undergraduate Advanced

Autoren/Hrsg.

Acharya, Biswaranjan

Dey, Satarupa

Zidan, Mohammed

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
• Geowissenschaften Umweltwissenschaften Umweltwissenschaften
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Abfallwirtschaft, Abfallentsorgung
• Geowissenschaften Umweltwissenschaften Abfallbeseitigung, Abfallentsorgung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Geowissenschaften Umweltwissenschaften Umwelttechnik

Inhaltsverzeichnis

Chapter 1 E-waste Management, Chapter 2 Waste Prevention: Its Impact and Analysis, Chapter 3 Smart Waste Bin Using Ai, Big Data Analytics and Iot, Chapter 4 Iot - Based Smart Waste Management for Environmental Sustainability, Chapter 5 Iot -enabled Services for Sustainable Municipal Solid Waste Management in India, Chapter 6 Iot Enabled Smart Dustbin, Chapter 7 Municipal Waste Collection/management Using Internet of Things (Iot) for Smart Cities, Chapter 8 Serverless Iot Architecture for Smart Waste Management Systems, Chapter 9 Iot in Hospital Solid Waste Generation and Management, Chapter 10 A Fast Garbage Classification Model Based on Deep Learning

Über Autor(innen)

Biswaranjan Acharya is an academic currently associated with Kalinga Institute of Industrial Technology Deemed to be University and is pursuing a doctorate in computer application at Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India. He has received a MCA from IGNOU, New Delhi, India and M.Tech in Computer Science and Engineering from Biju Pattanaik University of Technology (BPUT), Odisha, India. He is also associated with various educational and research societies like IEEE, IACSIT, CSI, IAENG, and ISC. He has worked in industry as a software engineer and in academia at Ravenshaw University. He is currently doing research different fields like Data Analytics, Computer Vision, Machine Learning and IoT. He owns eight patents and has published several research articles in internationally repute journals.

Satarupa Dey, is an Assistant Professor in the Department of Botany, University of Calcutta, West Bengal, India. She completed her doctorate in 2012 in bioremediation of toxic metals. She was a research fellow for the Department of Biotechnology, Government of India and later worked as a visiting scientist at the Agricultural and Ecological Research Unit of Indian Statistical Institute, Kolkata. She is the recipient of the Woman Scientist (WOS A) fellowship of Department of Science and Technology, Government of India. She has published in several journals of national and international repute.

Mohammed Zidan received his Ph.D. degree from Sohag University, Egypt, in 2019. He works as a post-doctoral fellow at the Center for Photonics and Smart Materials (CPSM), Zewail City of Science and Technology. He is a research consultant at Engineering Collage, Abu Daubi University, UAE. He has published several papers and has two patents in machine learning and IoT. His current research interests include machine learning, IoT, quantum machine learning, quantum computer, Quantum IoT.