IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Future Trends in IoT, Control Systems, and Remote Sensing Integration for Precision Agriculture

Future Trends in IoT, Control Systems, and Remote Sensing Integration for Precision Agriculture
View Sample PDF
Author(s): V. Dankan Gowda (Department of ECE, BMS Institute of Technology and Management, Karnataka, India), B. C. Kavitha (BGS Institute of Technology, Adichunchanagiri Univeristy, Mandya, India), Sajja Suneel (Institute of Aeronautical Engineering, Dundigal, India), N. Suganthi (Dayananda Sagar College of Engineering, Bangalore, India)and Madan Mohanrao Mohanrao Jagtap (Symbiosis International University, Pune, India)
Copyright: 2025
Pages: 28
Source title: Integrating Intelligent Control Systems With Sensor Technologies
Source Author(s)/Editor(s): Abdulsattar Abdullah Hamad (University of Samarra, Iraq), Sudan Jha (Kathmandu University, Nepal)and Khalid Al-Badri (University of Samarra, Iraq)
DOI: 10.4018/979-8-3373-0330-7.ch001

Purchase

View Future Trends in IoT, Control Systems, and Remote Sensing Integration for Precision Agriculture on the publisher's website for pricing and purchasing information.

Abstract

This chapter discusses how IoT and remote sensing are revolutionalising precision agriculture through the provision of real-time information to inform the management of crops and other resources. Specifically, this chapter explores the main technologies with focus on how they have been adopted within contemporary agriculture production systems. New technologies like, IoT sensors, satellite, UAVs, and LiDAR are helping farmers to keep an eye on the condition of the soil, status of crops, and the prevailing weather condition at a given time; in this way productivity is increased, resources are not wasted, and the environment is kept sustainable. The chapter discusses these technologies from a developmental perspective, from the early rudimentary uses to the sophisticated types of the current generation and then show how these technologies can transform farming. However, the prospective of applying big data has its limitations; they include the following: high initial costs, data integration problems and limited technological access in developing regions.

Related Content

Licheng Huang, Bochen Xue, Yiming Chen, Peihang Wu, Yuezhong Wang, Aquil Mirza Mohammed. © 2026. 34 pages.
Hong Rui Zhou, Min Hao Ling, Tong Yao Li, Xiang Li, Yi Ran Wu, Cong Wu. © 2026. 34 pages.
Chenyu Liu, Yaxin Luo, Jingyan Zeng, Liyuan Fan, Mingyuan Tang, Cong Wu. © 2026. 28 pages.
Haochen Shi, Xuan Luo, Junhao Huang, Yixiong Feng, Zihan Meng, Aquil Mirza Mohammed. © 2026. 34 pages.
Ruiman Huang, Shuxin Jia, Zeyu Min, Haoyue Zhang, Hewa Majeed Zangana. © 2026. 32 pages.
Shu Kei Ling, Pak Sun Wong, Kwan Ho Yuen, Mohammad Al Khaldy. © 2026. 40 pages.
Enlong Dong, Huakun Huang, Huakai Huang, Ruize Liu, Hengxian Li. © 2026. 34 pages.
Body Bottom