Applications of Internet of Things, Remote Sensing, and AI for Precision Agriculture and its Adoption Status in Nepal

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Published Feb 28, 2026
https://doi.org/10.55043/jaast.v10i1.446
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Vol. 10 No. 1 (2026): Journal of Applied Agricultural Science and Technology

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Aarju Aryal
University of Nebraska-Lincoln
Yogesh Sapkota
Youngstown State University
Bishal Lamichhane
University of Nevada
Jiban Shrestha
National Plant Breeding and Genetics Research Centre

Abstract

Modern technologies combined with precision agriculture have made revolutionary advances in the field of agriculture. The Internet of Things (IoT), remote sensing, wireless sensor networks, machine learning, and smart farm management systems have brought agriculture into a new era. In this context, the purpose of this review is to summarize the most recent advanced tools and their potential directions for further research by synthesizing the recent literature. Sensors, robotics, global positioning systems (GPS), satellites, and aerial imaging drones have facilitated data-driven actions, programmed management, and real-time monitoring in agricultural systems. These tools, when combined with Artificial Intelligence (AI) and machine learning, enable real-time decision-making and smart farm management. Some advanced applications include computer-based image recognition in weed control robots, early pest and disease detection through image identification, irrigation based on field water, fertilizer application through soil nutrient mapping, livestock health tracking through behavioral biometrics, and yield prediction analytics to inform breeding and harvest planning. The emergence of "digital agriculture" paradigms, such as Agriculture 4.0, signifies the convergence of interconnected intelligent farm management systems. In Nepal’s setting, the growing use of mobile apps and Information and Communication Technology (ICT)-enabled advice services provides smallholder farmers with crucial, location-specific information even in the absence of advanced technical infrastructure. Precision agriculture technologies have enormous promises to meet the country’s food demand. However, data privacy, technical proficiency, and technology accessibility must be resolved simultaneously. The discussion of policies and collaborative tactics required to ensure precision agricultural technology empowers rather than displaces poor food producers. Seventy-three scholarly articles on the topics of IoT, AI and precision agriculture were reviewed to introduce relevant concepts, ideas and implementations to offer a framework for the application of novel technologies in the Nepali agricultural landscape.

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Author Biographies

Aarju Aryal, University of Nebraska-Lincoln

University of Nebraska-Lincoln, Nebraska, USA

Yogesh Sapkota, Youngstown State University

Youngstown State University, Youngstown, Ohio, USA

Bishal Lamichhane, University of Nevada

University of Nevada, Reno, Nevada, USA

Jiban Shrestha, National Plant Breeding and Genetics Research Centre

National Plant Breeding and Genetics Research Centre, Khumaltar, Lalitpur, Nepal

How to Cite
1.
Aryal A, Sapkota Y, Lamichhane B, Shrestha J. Applications of Internet of Things, Remote Sensing, and AI for Precision Agriculture and its Adoption Status in Nepal. J. appl. agricultural sci. technol. [Internet]. 2026Feb.28 [cited 2026Mar.9];10(1):171-97. Available from: https://jaast.org/index.php/jaast/article/view/446

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