A framework for IoT-Enabled Smart Agriculture

TL;DR

This paper introduces an IoT-based framework using Raspberry Pi and sensors for real-time weather and environmental monitoring to enhance crop management and productivity in Ugandan agriculture.

Contribution

It presents a novel IoT-enabled smart agriculture framework integrating sensors, real-time data display, remote analysis, and predictive weather forecasting to improve farming outcomes.

Findings

Framework reduces water consumption in farming.

Enhances weather forecasting accuracy.

Improves crop productivity through actionable insights.

Abstract

Unpredictable weather patterns and a lack of timely, accurate information significantly challenge farmers in Uganda, leading to poor crop management, reduced yields, and heightened vulnerability to environmental stress. This research presents a framework for IoT-enabled smart agriculture, leveraging Raspberry Pi-based technology to provide real-time monitoring of weather and environmental conditions. The framework integrates sensors for temperature, rainfall, soil moisture, and pressure, connected via an MCP3208 analog-to-digital converter. Data is displayed on an LCD for immediate feedback and transmitted to the ThingSpeak platform for centralized storage, analysis, and remote access through a mobile app or web interface. Farmers can leverage this framework to optimize irrigation schedules and improve crop productivity through actionable insights derived from real-time and forecasted data on rainfall, temperature, pressure and soil moisture. Additionally, the system incorporates predictive weather forecasting to dynamically control sensor activity, reducing energy consumption and extending sensor lifespan. Simulated using Proteus, the proposed framework demonstrates significant potential to mitigate the impacts of unpredictable weather by reducing water consumption, improving forecasting accuracy, and boosting productivity.