Work

Innovative applications of internet of things and machine learning in sustainable agricultural irrigation management: Benefits and challenges

Year: 2025

Type: article

Abstract: • Presentation of an in-depth overview of IoT and ML applications in smart irrigation systems. • Analysis of the synergy between IoT and ML for adaptive and optimized irrigation management. • Highlighting the benefits: reduced water consumption, improved profitability, and enhanced sustainability. • Identification of the technical and economic challenges involved in adopting these systems. • Prospects for integration with renewable energies and advanced predictive models. Challenges in the agricultural sector include those relating to climate, demographics, as well as managing water resources. Using the Internet of Things (IoT), as well as the concept of artificial intelligence (AI), particularly machine learning (ML), offer technological solutions to optimize agricultural irrigation. However, the adoption of these technologies in irrigation systems remains limited due to associated risks, system complexity, and technical constraints. This article analyzes smart irrigation by integrating IoT and ML technologies in optimizing crop water use in agriculture. Effective water management is now essential to address challenges such as urbanization, climate change, and food security. IoT- and ML-based solutions offer a promising way to support more efficient and sustainable agricultural practices. This is because IoT systems provide real-time information about environmental and soil conditions. Moreover, ML techniques provide tools that will ensure that this instantaneous information obtained is of much use in making appropriate decisions in carrying out the irrigation process of agricultural products. This work provides a systematic review of the existing literature using the Preferred Reporting Items for Systematic Reviews (PRISMA) methodology. From an initial set of 1,340 publications, 108 studies met the inclusion criteria and were analyzed in depth. These studies offer a comprehensive understanding of IoT- and ML-based smart irrigation systems, highlighting their benefits in improving water conservation, irrigation efficiency, and agricultural productivity

Source: Smart Agricultural Technology

DOI: 10.1016/j.atech.2025.101661

Authors: Abdennabi Morchid, Zafar Said, Hamid Tairi

Institutions: Sidi Mohamed Ben Abdellah University, United Arab Emirates University

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,770