A comprehensive review on the Internet of Things in precision agriculture

• Published in: Multimedia tools and applications Vol. 84; no. 17; pp. 18123 - 18198
• Main Authors: Singh, Gurpreet, Sharma, Sandeep
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2025; Springer Nature B.V
• Subjects: Agriculture; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Deep learning; Farmers; Farming; Internet of Things; Literature reviews; Machine learning; Multimedia Information Systems; Resource utilization; Special Purpose and Application-Based Systems; Precision agriculture; Smart agriculture; Internet of Things; Machine learning
• ISSN: 1573-7721; 1380-7501; 1573-7721
• DOI: 10.1007/s11042-024-19656-0

A quickening transformation in the agriculture sector is being driven by the growth of Internet of Things (IoT) technology. The need for food production is growing quickly because it is predicted that by 2050 there will be 9.7 billion people on the planet. Farmers are responding by utilizing IoT technology to improve production, efficiency, and sustainability in agriculture. In this review study, applications, technologies, and usage of IoT technology in precision farming are investigated. Numerous IoT applications for agriculture are covered in the paper, including crop health management, smart irrigation, animal monitoring, and precision farming. Additionally, the crops and their diseases in IoT agriculture are looked at, including the crop's nutritional values. The analysis also examines the possible effects of cutting-edge IoT technologies like machine learning, deep learning, and fuzzy techniques on farming in the future. 188 scientific publications published in these six years (2018–2023) in reputed journals and conferences were the subject of a thorough literature review. This study rigorously analyzes existing gaps and proposes strategic recommendations for future enhancements, aiming to optimize the utilization of resources and pave the way for more effective and efficient processes in the times ahead. The abstract succinctly encapsulates the study's focus on critical examination, identifying areas for improvement, and providing forward-looking insights for enhanced utilization in the future. Farmers can make data-driven choices, allocate resources more efficiently, and minimize environmental effects by utilizing the power of IoT.