AgriSense: IoT-Driven Precision Agriculture for National Food Sustainability and Development
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Keywords

AgriSense
Internet of Things (IoT)
Precision Agriculture
Privacy Preservation
Sustainable Food Security

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How to Cite

Onwuegbuzie, I. U., & Emordi, F. U. (2026). AgriSense: IoT-Driven Precision Agriculture for National Food Sustainability and Development. Tech-Sphere Journal for Pure and Applied Sciences, 3(1), 140–160. https://doi.org/10.5281/zenodo.23335306

Abstract

Precision agriculture integrates digital technologies to improve agricultural resource management, productivity, and sustainability, while the Internet of Things (IoT) enables real-time monitoring of soil and environmental conditions through connected sensors. In Nigeria, inefficient water and fertilizer use, declining soil health, climate variability, and limited access to timely agricultural information constrain sustainable food production. This study presents AgriSense, an IoT-driven precision agriculture platform designed to support data-informed farm management under Nigerian agricultural conditions. The study adopts a mixed-method research framework incorporating descriptive, experimental, and analytical approaches, with proposed data sources including IoT sensor measurements, farmer surveys and interviews, field observations, and relevant weather information. The AgriSense platform integrates soil-moisture, nitrogen-phosphorus-potassium (N-P-K), soil-pH, temperature, and humidity monitoring with farm and field management, sensor-status tracking, automated alerts, agronomic recommendations, and reporting functions. The demonstrated interface represents agricultural fields and crops across Asaba Demonstration Farm, Jos Highland Farm, and Sokoto Smart Farm. Its threshold-based alerts identify conditions associated with low soil moisture, low nitrogen, acidic soil, high temperature, and sensor connectivity faults, linking selected conditions to recommended management actions. The available demonstration establishes the platform’s integrated monitoring and decision-support functionality. However, because the interface identifies its environment as a live simulation, the displayed information does not independently establish improvements in crop yield, input-use efficiency, soil health, or farmer income. The study provides a technological foundation for subsequent field validation of IoT-enabled precision agriculture and its potential contribution to sustainable food security in Nigeria.

https://doi.org/10.5281/zenodo.23335306
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Copyright (c) 2026 Tech-Sphere Journal for Pure and Applied Sciences

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