Aniket Vishwakarma, Himanshu Vaishya | International Journal of Microwave Engineering and Technology | Vol 11, Issue 01 | pp. 8-14 | ISSN: 2455-0337
Abstract
Agriculture is a vital sector for food security and economic growth, particularly in the developing world. Farmers, however, often face unpredictability of weather conditions, insect attacks, wasteful use of resources, and uncertainties of the market. Farmers' practices are mostly based on experience and intuition, which might not always be the best to apply. Smart Agro-Advisory Systems (SAAS) based on Artificial Intelligence (AI) offer real-time decision support to farmers, enabling them to make evidence-based decisions. These AI-driven platforms compile information from satellite images, IoT sensors, climate models, and past farm records to provide customized suggestions. Some of the most important areas of interest are crop health monitoring, irrigation scheduling, and pest control, to ensure improved use of resources and enhanced farm output. Machine learning algorithms identify trends and forecast potential risks, enabling farmers to implement preventive actions instead of reactive ones. By taking advantage of AI, SAAS increases accuracy in agriculture, minimizing input while maximizing yield and sustainability. Multilingual voice assistants and mobile applications increase accessibility, bridging the digital divide and giving farmers usable information. With the inclusion of predictive analytics, it allows decision-making to happen in advance, lessening risk brought about by climate change and market volatility. This article discusses the architecture, advantages, and deployment issues of AI-driven agro-advisory systems. It emphasizes the ways in which such platforms have the power to revolutionize contemporary agriculture by enhancing efficiency, curtailing losses, and enhancing sustainable farming. The use of SAAS can transform the agricultural industry, developing a resilience against environmental unpredictability and providing food security for generations to come.
Keyword: Agricultural sector, Food security, Economic stability, Developing countries, Artificial intelligence, SAAS (Software as a Service), Decision support system
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How to cite this article
@article{VishwakarmaA2025,
author = {Aniket Vishwakarma and Himanshu Vaishya},
title = {Smart Agro-Advisory Systems: AI-Based Platforms for Real-Time Farmer Decision Support},
journal = {International Journal of Microwave Engineering and Technology},
year = {2025},
volume = {11},
number = {01},
pages = {8--14},
issn = {2455-0337},
url = {https://journalspub.com/publication/ijmet/article=16361}
}