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Smart Soil Intelligence: A Cloud-Integrated IoT Framework for Real-Time NPK Nutrient Monitoring in Precision Agriculture
Subject area: Agriculture and Veterinary Sciences · Area of research: IoT-Based Soil Nutrient Monitoring
Abstract
Sustainable food production depends critically on maintaining optimal concentrations of macronutrients within agricultural soil. Nitrogen (N), phosphorus (P), and potassium (K) govern plant metabolism, root development, and yield quantity in ways that cannot easily be compensated for after a growing season has begun. Yet across rural India, the dominant method of determining soil nutrient status — dispatching a physical sample to an offsite laboratory — is structurally mismatched to the timescales on which farmers must make practical decisions. The present work introduces a field-deployable, cloud-connected monitoring platform engineered to close that mismatch. The proposed architecture combines an RS485-interfaced NPK sensor module, an ESP32 dual-core microcontroller, and a wireless data pipeline terminating in a cloud analytics layer with an intelligent fertiliser recommendation engine. Sensor readings are continuously relayed to ThingsBoard, where a mobile-accessible dashboard presents real-time nutrient and moisture status through colour-coded gauge indicators. Threshold-triggered push notifications alert cultivators to nutrient deviations within seconds of a boundary crossing. Field validation conducted across agricultural plots in Wardha district, Maharashtra, using NABL-accredited wet-chemistry laboratory measurements as reference values, returned agreement rates of 94.3% for phosphorus, 95.7% for nitrogen, 96.2% for potassium, and 97.5% for soil moisture. The system is demonstrably viable for smallholder conditions, requires no laboratory infrastructure, operates continuously without manual intervention, and produces economically meaningful improvements in fertiliser use efficiency.
References
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How to cite this paper
@article{1717447,
author = {Kirti H. Kine, Nihal B. Chandwani, Nikhil Wankhede, Yash S. Wakle, Prof. Dr. Kalpana Malpe},
title = {Smart Soil Intelligence: A Cloud-Integrated IoT Framework for Real-Time NPK Nutrient Monitoring in Precision Agriculture},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {11},
pages = {439-446},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717447.pdf},
abstract = {Sustainable food production depends critically on maintaining optimal concentrations of macronutrients within agricultural soil. Nitrogen (N), phosphorus (P), and potassium (K) govern plant metabolism, root development, and yield quantity in ways that cannot easily be compensated for after a growing season has begun. Yet across rural India, the dominant method of determining soil nutrient status — dispatching a physical sample to an offsite laboratory — is structurally mismatched to the timescales on which farmers must make practical decisions. The present work introduces a field-deployable, cloud-connected monitoring platform engineered to close that mismatch. The proposed architecture combines an RS485-interfaced NPK sensor module, an ESP32 dual-core microcontroller, and a wireless data pipeline terminating in a cloud analytics layer with an intelligent fertiliser recommendation engine. Sensor readings are continuously relayed to ThingsBoard, where a mobile-accessible dashboard presents real-time nutrient and moisture status through colour-coded gauge indicators. Threshold-triggered push notifications alert cultivators to nutrient deviations within seconds of a boundary crossing. Field validation conducted across agricultural plots in Wardha district, Maharashtra, using NABL-accredited wet-chemistry laboratory measurements as reference values, returned agreement rates of 94.3% for phosphorus, 95.7% for nitrogen, 96.2% for potassium, and 97.5% for soil moisture. The system is demonstrably viable for smallholder conditions, requires no laboratory infrastructure, operates continuously without manual intervention, and produces economically meaningful improvements in fertiliser use efficiency.},
month = {May},
}