Aug 2026· Journal of Intelligent Decision Making and Information Science· 0 citations· 60 references
TL;DR
This paper discusses how these sensing elements are integrated with IoT architectures, microcontroller-based nodes, wireless sensor networks, wireless sensor networks, and cloud-enabled analytics to support precision irrigation, nutrient management, disease indication, and yield-oriented crop supervision.
Abstract
The field of agriculture is encountering considerable difficulties in fulfilling the rising stresses in order to produce food while maintaining sustainability and efficient source utilization. Numerous technologies currently employed in agricultural practices for monitoring crop growth, soil efficiency, and nutrient levels have faced challenges. Some of these technologies have proven inadequate due to variations in frequency and distance range within smart farming applications. To tackle these issues, this review highlights an integration of biosensors, bioelectronics and Internet of Things (IoT) technology into agricultural performs, which has become a hopeful answer. The paper discusses how these sensing elements are integrated with IoT architectures, microcontroller-based nodes, wireless sensor networks, and cloud-enabled analytics to support precision irrigation, nutrient management, disease indication, and yield-oriented crop supervision. In addition, it compares major IoT communication technologies, reviews current applications and limitations, identifies research gaps in field deployment and system integration, and outlines future directions for robust, scalable, and intelligent agricultural biosensing systems.
The integration of Internet of Things (IoT) technologies into agriculture has emerged as a revolutionary approach for developing smart agricultural systems capable of improving productivity, resource efficiency, and sustainability. Traditional farming methods often face challenges such as climate variability, water sca...
Research Author· American Journal of Multidis...· 0 citations
This review synthesizes the current body of literature on AI-IoT integration in precision farming, covering the core enabling technologies — smart sensors, unmanned aerial vehicles, UAVs, geographic information systems, GIS, edge and cloud computing, and block chain-based traceability — and the layered architecture thr...
G. Swetha, T. Anuradha· IRASS Journal of Multidiscip...· 0 citations
The review shows that AI-IoT technologies are primarily applied in crop disease detection, precision agriculture, environmental monitoring, yield prediction, and livestock health monitoring, and the five-layered framework introduced here provides the first inductively derived organising structure that explicitly connec...
B. Ndlovu, Kudakwashe Maguraushe· Scientific Journal of Inform...· 1 citation
Efficient water management is a persistent challenge in modern agriculture, especially in arid and semi-arid regions. The development and adoption of advanced soil sensor technologies are essential for optimising water use and supporting sustainable, high-yield agricultural systems. This systematic review compares prim...
Omar Talib Khazraji, Marwan J. Hussein, Ahmed M. Almawla· Academic Journal of Electric...· 0 citations
The world today is under pressure to foster agriculture to be more productive with less water consumption, less fertilizer wastage, and less labor reliance. The Intelligent Agricultural Systems (IAS) combine Internet of Things ( IoT ) sensing, edges/cloud connectivity, and Artificial Intelligence (AI) instruments to fa...
Chinedu Okafor· International Journal of Art...· 0 citations
Agriculture is undergoing a digital transformation driven by Machine Learning (ML) and the Internet of Things (IoT), enabling sustainable food production, efficient resource utilization, and climate-resilient farming. Traditional agricultural practices are increasingly challenged by climate change, soil degradation, wa...
Mustapha Malami Idina, Mubarak Jibril Yeldu, A. Gulumbe· International Journal of Mul...· 0 citations
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