Volume no :
10 |
Issue no :
01
Article Type :
Google Scholar
Author :
Dr R Senthilkumar, Arshad Khan.S, Bharath.S, Dhanushu.S, Hari krishna.A
Published Date :
13 - March - 2026
Publisher :
Journal of Artificial Intelligence and Cyber Security (JAICS)
Page No: 1 - 6
Abstract : Agriculture plays a vital role in the economic development of many countries, especially India, where a large portion of the population depends on farming for their livelihood. However, farmers often face challenges such as lack of access to real-time market information, unpredictable weather conditions, fluctuating crop prices, and limited knowledge of profitable markets. These challenges can lead to poor decision-making, reduced productivity, and financial losses.This paper proposes a Smart Agriculture Market Intelligence and Decision Support System designed to assist farmers in making informed agricultural and marketing decisions. The system integrates modern technologies such as data analytics, agricultural market information systems, and decision support mechanisms to provide farmers with reliable and timely insights. It collects and processes agricultural data such as crop prices, market demand, weather information, and regional agricultural trends.By analyzing this data, the system provides recommendations regarding crop selection, optimal selling time, and nearby markets offering better prices. The platform reduces farmers' dependency on intermediaries by providing direct access to updated agricultural information. The system is developed as a web-based application using modern technologies including React.js for the user interface, Node.js and Express.js for backend processing, and MongoDB for data management. Experimental results demonstrate that the system improves transparency in agricultural markets and enhances farmers' ability to make strategic decisions. The proposed solution contributes to better agricultural planning, increased profitability, and improved efficiency in the agricultural supply chain. Future enhancements may include machine learning-based prediction models, IoT-based farm monitoring systems, and mobile application integration for wider accessibility.
Keyword Smart Agriculture, Agricultural Market Intelligence, Decision Support System, Crop Recommendation, Data Analytics in Agriculture, Weather Information Systems, Digital Farming
Reference:

1.
Deepa, R., Karthick, R., Velusamy, J., & Senthilkumar, R. (2025). Performance analysis of multiple-input multiple-output orthogonal frequency division multiplexing system using arithmetic optimization algorithm. Computer Standards & Interfaces, 92, 103934.
2.
Senthilkumar, Dr.P.Venkatakrishnan,Dr.N.Balaji, Intelligent based novel embedded system based IoT Enabled air pollution monitoring system, ELSEVIER Microprocessors and Microsystems Vol.77, June 2020
3.
M. Muthalakshmi, N.Mythili, Gurkirpal Singh, R.Senthilkumar (2025). Innovative Approaches for Evaluating Sugarcane Quality: Utilizing Near-Infrared Spectroscopy to Forecast Brix, Pol, and Fiber Content in Commercial Agricultural Domains. Journal of Food Processing, Wiley, https://doi.org/10.1111/jfpe.70233
4.
Senthilkumar Ramachandraarjunan, Venkatakrishnan Perumalsamy & Balaji Narayanan 2022, ‘IoT based artificial intelligence indoor air quality monitoring system using enabled RNN algorithm techniques’, in Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2853-2868
5.
N. Nagarani, M. Muthalakshmi , E. S. Vinothkumar and R. Senthilkumar (2026) ‘Optimized Contrastive Multi-Level Graph Neural Networks-Based Pigment Epithelial Detachment Detection in OCT images’ International Journal of Information Technology & Decision Making 2026 World Scientific DOI: 10.1142/S0219622026500343
6.
Sanitha P C; Syed Nageena Parveen; Shaik Thaherbasha; M. Shanmugapriya; T. Kalaivani; R. Senthilkumar, Transparent Nutrition: An Explainable AI-based Diet Tracking System for Preventing Nutrition-Related Disorders. 2025 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) DOI:10.1109/ICoICI65217.2025.11252549
7.
T. Jayasri; M.R. Archana Jenis; P.B. Aswathy; S. Manoranjitham; Christo George; R. Senthilkumar Identity-First Defense in Zero Trust Security Architecture to Protect Cyberspace 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) DOI:10.1109/ICoICI65217.2025.11254505
8.
J. Uthayakumar; Swapna; A. Ravikumar; S. Sreeraj; R. Senthilkumar; Babu Pandipati AI-Driven Water Resource Management Systems 2025 2nd International Conference on Computing and Data Science (ICCDS) DOI: 10.1109/ICCDS64403 .2025.11209318
9.
R.Swathiramya; V.V.Karthikeyan; P.Sumathi; Sruthy K V; Afreen Hussain; R.Senthilkumar Multimodal Machine Learning Models for Intelligent Interpretation of Text, Image and Audio Inputs 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) DOI:10.1109/ICERECT65215.2025.11377322
10.
Srinju.M; Dr.V.Dhanasekaran; S. Guruprasath; Dr.K.Edison Prabhu; K.J Godlin Debby; Dr.R.Senthilkumar AI-Based Recommendation System for Weight Management Using User Feedback and Health Metrics 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) DOI: 10.1109/ICERECT65215.2025.11379842
11.
J. O. Adeyemi, M. K. Oladunjoye, and A. A. Olatunji, “IoT Based Smart Crop Monitoring System for Agriculture,” International Journal of Advanced Computer Science and Applications, vol. 11, no. 4, pp. 1–8, 2020.
12.
S. R. Nandhini and M. N. Raja, “IoT Based Smart Agriculture Monitoring System,” International Journal of Engineering and Advanced Technology, vol. 8, no. 6, pp. 248–252, 2019.
13.
Food and Agriculture Organization (FAO), “Digital Technologies in Agriculture and Rural Areas – Status Report,” FAO, Rome, Italy, 2019.
14.
R. Zhang, M. Wang, and Y. Wang, “Precision Agriculture – A Worldwide Overview,” Computers and Electronics in Agriculture, vol. 36, pp. 113–132, 2002.
15.
J. A. Stankovic, “Research Directions for the Internet of Things,” IEEE Internet of Things Journal, vol. 1, no. 1, pp. 3–9, Feb. 2014.
16.
React Documentation, “React – A JavaScript Library for Building User Interfaces,” Available: https://react.dev
17.
Node.js Foundation, “Node.js Documentation,” Available: https://nodejs.org
18.
MongoDB Inc., “MongoDB Database Documentation,” Available: https://www.mongodb.com/docs
19.
Express.js Documentation, “Express – Fast, Unopinionated Web Framework for Node.js,” Available: https://expressjs.com
20.
AMIS (Agricultural Market Information System), “Agricultural Market Intelligence and Price Monitoring,” Available: https://www.amis-outlook.org