Application of Fuzzy Logic System for Solving Agricultural Problems Using Nanotechnology in Chas, Bokaro, Jharkhand

Mukesh Kumar Sinha; Rajesh Kumar Tiwari

doi:10.26713/cma.v17i3.3552

Authors

Mukesh Kumar Sinha University Department of Mathematics, Binod Bihari Mahto Koyalanchal University, Dhanbad, 826004, Jharkhand, India https://orcid.org/0009-0006-2088-8547
Rajesh Kumar Tiwari University Department of Mathematics, Binod Bihari Mahto Koyalanchal University, Dhanbad, 828103, Jharkhand, India

DOI:

https://doi.org/10.26713/cma.v17i3.3552

Keywords:

Fuzzy Logic System, Nanotechnology, Precision Agriculture, Nano-Sensors, Pest Management.

Abstract

Agriculture in the Chas block of Bokaro district, Jharkhand, India, faces persistent challenges, including irregular rainfall, degraded soil fertility, pest infestations, poor input efficiency, and limited technological adoption among small and marginal farmers. This study presents an integrated Fuzzy Logic System (FLS) combined with nanotechnology-based agricultural interventions, such as nanosensors, nano-fertilizers, and nano-pesticides. This study aims to develop a robust, adaptive decision-support system tailored to the local climatic and soil conditions of Chas, thereby improving irrigation scheduling, nutrient management, and pest control. Field data from multiple agricultural plots in Chas were collected using nanosensor systems and traditional soil test reports. The fuzzy inference model utilizes linguistic variables such as low soil moisture, medium pest intensity, and high nutrient deficiency to produce optimized real-time recommendations. The results indicate notable improvements: irrigation efficiency increased by 22%, fertilizer utilization improved by 18%, and pest-related losses decreased by 27%. This study demonstrates the effectiveness of combining fuzzy logic with nanotechnology for sustainable agricultural development in semi-urban and rural regions such as Chas. This study addresses the critical need for improved decision-making tools in agricultural environments characterized by uncertainty, incomplete information, and environmental variability. The integrated framework offers a scalable, affordable, and farmer-friendly mechanism for strengthening decision-making and enhancing crop productivity.

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