
Internet of Things and Unmanned Aerial Vehicles-based Applications for High-Yield Precision Agriculture
Description
The text focuses on the basic algorithms used for hard problems or multi-objective problems in precision agriculture. It comprehensively discusses precision agriculture techniques such as the use of global positioning systems, crop sensors, geographic information systems, remote sensing, and Soil sampling.
Features:
- Presents the Internet of Things-based methods for the detection of diseases and water requirements in precision agriculture.
- Focuses on the basic algorithms used for hard problems or multi-objective problems in precision agriculture.
- Covers applications of UAVs and machine learning in precision agriculture water management.
- Explains geospatial technologies for the management of pests and diseases in crops.
- Showcases case studies on leveraging the Internet of Things in agriculture for high yields.
It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electrical and communications engineering, computer science and engineering, agricultural science and engineering, and information technology.
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Persons
Amit Bage works as an assistant professor, in the Department of Electronics and Communication Engineering, at the National Institute of Technology Hamirpur, India. In his area of specialization, he is interested in electromagnetics and his recent research activities have focused on microwave antennas, microwave passive components, and sensors. He has published more than forty research papers in journals and conferences of national and international reputation.
Aman Kumar works as an assistant professor, in the Department of Electronics and Communication Engineering, at the National Institute of Technology Hamirpur, India. His research area includes designing filters, filter banks and their applications, biomedical signal/image processing, machine learning, deep learning algorithms for biomedical signals, and image processing. He has published more than twenty-five research papers in reputed journals and conferences.
Prakash Pareek is currently working as an associate professor, in the Department of Electronics and Communication Engineering, at Vishnu Institute of Technology, Andhra Pradesh, India. His research interests are optical communications, group IV optoelectronic devices, plasmonic, integrated optics, and THz photonics. He has published his research in reputed peer-reviewed Journals and conferences (more than 70). He is a senior member of IEEE and a Professional member of Optica (Formerly Optical Society of America).
Dharmendra Prasad Mahato works as an assistant professor, in the Department of Computer Science and Engineering, at the National Institute of Technology Hamirpur, Himachal Pradesh, India. His research interests include distributed computing, artificial intelligence, operating systems, databases and modelling and simulation. He has published in journals such as Applied Soft Computing, Swarm and Evolutionary Computation, ISA Transactions, Cluster Computing, Concurrency, and Computation: Practice and Experience, and conferences such as AINA, ICPP, ICDCN, and E-Science.
Rardchawadee Silapunt works as an associate professor, in the Department of Electronic and Telecommunication Engineering, at King Mongkut's University of Technology Thonburi, Thailand. Her research interests include the Internet of Things (IoT) solutions for smart farming, asset tracking, and vehicle-to-everything. She has published her research in more than 100 journals and conference papers. She is a member of IEEE and vice chair of the electromagnetics area under the Electrical Engineering/Electronics, Computer, Telecommunications, and Information Technology Association, Thailand.
Content
Chapter 1. Some Observations on Precision Agriculture using UAVs. Chapter 2. Predictive Analysis Techniques for Crop and Soil Sensors. Chapter 3. Predictive Analysis in Precision Agriculture: Leveraging IoT for Early Detection of Crop Stresses and Sustainable Farming. Chapter 4. Cloud-based Renewable Energy Integration in Smart Agriculture Using IoT. Chapter 5. Comparative Study of Manual and Autonomous UAVs for Precision Agriculture: Performance, Applications, and Challenges. Chapter 6. Advanced Crop Monitoring Using Unmanned Aerial Vehicle with Internet of Things and Cloud Computing. Chapter 7. Cloud-based Renewable Energy Integration in Smart Agriculture Using IoT. Chapter 8. Autonomous Agricultural Robotics and IoT in Precision Farming: Enhancing Productivity Through Smart Automation. Chapter 9. IoT and Edge AI Enabled Next Generation Agriculture. Chapter 10. Artificial Intelligence and Internet of Things in Sustainable Agriculture. Chapter 11. Predictive Analytics for Crop Yield Optimization: Using AI to forecast and maximize agricultural output. Chapter 12. IoT-Driven Precision Agriculture: Connected Farming for a Sustainable Future