Optimizing Smart and Sustainable Agriculture for Sustainability

1. Auflage 2025
ISBN: 978-1-032-65794-3
Verlag: Taylor & Francis Ltd

Buch, Englisch, 284 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Future Generation Information Systems

This reference text addresses the importance of smart crop management for increasing yield and presents a framework for smart monitoring and regulation of crop observation. Further, it comprehensively covers important topics such as spatial decision support systems for precision farming, swarm intelligence in the optimal management of aquaculture farms, and intelligent harvesting algorithms for improving productivity.

This book:

• Presents meta-heuristic algorithms for optimization, economic crop planning, and use of effective water resource management.

• Discusses spatial decision support systems for crop productivity management, watershed management, and precision farming.

• Illustrates swarm intelligence-based optimization techniques, data mining, and machine learning methods for aquaculture operations.

• Highlights artificial intelligence and machine learning-based harvesting

algorithms for improving productivity.

• Explains the use of green Internet of Things security solutions for agriculture, plant condition management, and greenhouse simulation.

It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, agricultural science, and information technology.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Jain, Abha

Acharya, Biswaranjan

Bansal, Ankita

Rodrigues, Joel J. P. C.

Jain, Rachna

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Technische Informatik

Inhaltsverzeichnis

1. Economic Efficiency through Livestock Production Monitoring and Prediction in Smart Agriculture. 2. Smart Crop Management for Increased Yield. 3. Smart Solutions and Sustainability for Agriculture using Deep Learning. 4. Bi-LSTM based Deep Learning Model for Crop Yield Prediction. 5. Food Image Recognition and Calorie Estimation. 6. Precision Agriculture: Navigating Environmental Sustainability. 7. Moving towards Sustainable and Smart Agriculture. 8. Green IOT for Smart Agricultural Monitoring. 9. Agricapital, a three-way agro-market aggregation using Cluster CRUD operations and role of ML in agriculture. 10. Optimizing smart and sustainable agriculture for sustainability. 11. Green IoT for Smart Agricultural Monitoring. 12. Agricultural Farming Decision Support System using Artificial Intelligence: A Comparative Analysis. 13. Drones- the unmanned aerial vehicles for precision management of pests and diseases of crops.

Über Autor(innen)

Biswaranjan Acharya (Senior Member, IEEE) received his M.C.A. degree from IGNOU, New Delhi, India, in 2009, an M.Tech. degree in Computer Science and Engineering from Biju Patnaik University of Technology (BPUT), Rourkela, Odisha, India, in 2012, and a Ph.D. degree in Computer Science from Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India, in 2024. He is currently an Assistant Professor in the Department of Computer Engineering-AI and BDA at Marwadi University, Gujarat, India. He also received a research fellowship at INTI International University from December 15, 2023, to December 31, 2025. He has more than ten years of academic experience at reputed institutions such as Ravenshaw University and has also worked in the software development industry. He has co-authored more than 70 research articles in internationally reputed journals and serves as a reviewer for several peer-reviewed journals. Additionally, he holds more than 50 patents. His research interests include multiprocessor scheduling, data analytics, computer vision, machine learning, and the Internet of Things (IoT). He is currently serving as a secondary IEEE Computer Society representative to the IEEE Nanotechnology Council (NTC) Administrative Committee and as an observer of the IEEE P2851 Standard for Functional Safety Data Format. He is also associated with various educational and research societies, including IACSIT, CSI, IAENG, and ISC.

Abha Jain is an Assistant Professor at the Department of Computer Science, Dyal Singh College, University of Delhi. Prior to joining the college, she worked as full-time research scholar and received a doctoral research fellowship from Delhi Technological University (formerly Delhi College of Engineering). She received her master’s and doctorate degree in Software Engineering from Delhi Technological University. Her research interests are data mining, software quality, and statistical and machine learning models. She has published papers in international journals and conferences.

Ankita Bansal is assistant professor in the department of Information Technology in Netaji Subhas University of Technology. She has a teaching experience of more than 10 years. She was awarded doctoral degree in Computer Science from Delhi Technological University (DTU, formerly DCE). From the same University, she has also received her master’s degree in computer technology and applications and secured rank 1 in the same. She has published more than 40 papers in reputed International Journals and conferences. She also has few edited books to her credit. Her research interests are computational intelligence, Software testing, Software quality, software metrics, developing quality prediction models.

Rachna Jain, currently working as Associate Professor in Bhagwan Parsuram Institute of Technology (GGSIPU) since Aug 2021. She has worked as Assistant Professor (Computer Science Department) in Bharati Vidyapeeth's College of Engineering (GGSIPU) from Aug 2007-Aug 2021.She did her PHD from Banasthali Vidyapith in Computer Science in 2017.She received ME degree in year 2011 from Delhi college of engineering (Delhi University) with specialisation in Computer Technology and Applications. She did her B.tech (Computer Science) in 2006 from N.C College of Engineering, Kurukshetra University. Her current research interests are Cloud Computing, Fuzzy Logic, Network and information security, Swarm Intelligence, Big Data and IoT, Deep Learning and Machine Learning. She has contributed with more than 10 book chapters in various books. She has also served as Session Chair in various International Conferences. She was CO-PI of DST Project titled “Design an autonomous intelligent drone for city surveillance”. A total of 15+ Years of Academic / Research Experience with more than 50+ Publications in various National, International Conferences cum International Journals (Scopus/ISI/SCI) of High Repute.

Joel J. P. C. Rodrigues is a Professor at the Department of Informatics of the University of Beira Interior, Covilhã, Portugal, and researcher at the Institute of Telecommunications (IT), Portugal. He received a PhD degree in Informatics Engineering and a MSc degree from the University of Beira Interior, Portugal, and a 5-year B.S. degree (licentiate) in Informatics Engineering from University of Coimbra, Portugal. His main research interests include vehicular delay tolerant networks, sensor networks, body sensor networks, e-health, high-speed networks, e-Learning technologies, information and knowledge management, mobile and ubiquitous computing, and supervising several PhD and Master of Science candidates in these areas. He participated in several PhD and MSc juries. He has authored or coauthored over 80 papers in refereed international journals and conferences, book chapter, a book and a patent.