Harnessing Digital Technologies in the Agro-Food Sector: An IoT-Driven Precision Agriculture Framework for Achieving Sustainable Development Goals

Summary

This study introduces IoT-Driven Precision Agriculture (IoT-PA), which uses sensor networks, real-time monitoring, and intelligent irrigation to boost crop output and water efficiency. The framework promotes sustainable agriculture and SDG 2 (Zero Hunger) and 12 (Responsible Consumption and Production).

Abstract

The agro-food industry is quickly digitizing to solve resource restrictions, climate unpredictability, and sustainable food production using Internet of Things (IoT), Artificial intelligence (AI), cloud computing, and data analytics. Due to rigid irrigation schedules and limited field monitoring, traditional agriculture wastes water, reduces crop yield, and harms the environment. The IoT-Driven Precision Agriculture (IoT-PA) system in this paper optimizes agricultural resource use using distributed sensor networks, real-time soil moisture and weather monitoring, and intelligent irrigation control. The proposed platform gathers environmental data, analyses field conditions, and automatically recommends irrigation to maximize crop growth and avoid water waste. Farmers may make data-driven agricultural decisions with continuous monitoring and fast notifications from the framework. The IoT-PA architecture improves irrigation efficiency, agricultural yield, and sustainable resource management compared to traditional farming. Higher agricultural production and efficient water and resource use assist Sustainable Development Goal (SDG) 2 (Zero Hunger) and SDG 12 (Responsible Consumption and Production) of the United Nations Sustainable Development Goals. The suggested smart agricultural system is scalable and practicable, promoting sustainable food production and environmental conservation.

Introduction

Food security, environmental sustainability, and economic resilience depend on agro-food enterprises¹. Agriculture must adapt to produce more food using fewer resources while minimizing its environmental impact as the global population is projected to reach approximately 10.3 billion during the mid-2080s, substantially increasing the demand for sustainable food production and efficient resource management². Simple farming practices may not solve these issues³. Climate change, soil deterioration, water shortages, and market fluctuations make this particularly true⁴. Innovati....

Protocol

Agro-food is becoming a sustainable, data-driven ecosystem thanks to digital technologies. IoT, AI, and blockchain improve supply chain transparency, food safety, and productivity. Precision Agriculture, Smart Farming, and Post-Pandemic Resilience support the Sustainable Development Goals, notably Zero Hunger, Climate Action, and Responsible Consumption and Production.

The IoT-Driven Precision Agriculture (IoT-PA) framework included an ESP32 microcontroller, soil moisture, air temperature, relative humidity (DHT22), rainfall, and light intensity (BH1750) sensors, an IoT gateway, a cloud database, and an automated irrigation controller. To p....

Results

IoT-PA architecture performance metrics include water consumption, agricultural yield, system efficiency, sustainable resource optimization, and SDG contribution. Smart technological choices improve agricultural production, sustainability, and resource management.

Dataset Description: The Agriculture Digital Twin Market Report by DataIntelo²⁶ was used as background information to support the development and contextualization of the proposed framework. T.......

Discussion

With the IoT-PA, digital agriculture may solve present problems. For resource economies and agricultural production, this paper proposes real-time monitoring, sensor-based irrigation, and data-driven decision-making. Water consumption dropped 24.62%, and agricultural output rose 95.13% using the Internet of Things, demonstrating its revolutionary sustainability potential. SDG 2 (Zero Hunger) and SDG 12 (Responsible Consumption and Production) are met with 93.85% system efficiency. The system achieved 96.31% SDG alignment.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Arduino IDE	Arduino	Version 2.x https://www.arduino.cc/en/software	Integrated Development Environment, ESP32 firmware development
Capacitive Soil Moisture Sensor	DFRobot	SEN0193	Measures volumetric soil moisture; Operating voltage 3.3–5.5 V
Cloud IoT Platform	Amazon Web Services	AWS IoT Core https://aws.amazon.com/iot-core	Cloud-based IoT platform for data storage, visualization, and remote monitoring
DC Power Supply	Mean Well	/	Supplies power to controller and pump; 12 V DC regulated output, Model: LRS-50-12
DC Water Pump	Commercially available	/	Automated irrigation; 12 V DC Pump
Digital Light Intensity Sensor	Rohm Semiconductor	BH1750FVI	Measures ambient light intensity; 1–65535 lux
ESP32 Development Board	Espressif Systems	ESP32-DEVKITC-32D	Dual-core 240 MHz MCU, Wi-Fi/Bluetooth; Main controller for sensor acquisition and irrigation control
Microsoft Excel	Microsoft Corporation	Microsoft 365 https://www.microsoft.com/microsoft-365/excel	Spreadsheet software for data organization and visualization
MQTT Broker	Eclipse Foundation	Mosquitto v2.x https://mosquitto.org	IoT message communication; MQTT protocol
Python	Python Software Foundation	Version 3.x https://www.python.org	Programming language for data preprocessing and statistical analysis
Rainfall Sensor Module	DFRobot	/	Analog/Digital output; Detects rainfall events; Model: SEN0308
Single-Channel Relay Module	Songle	SRD-05VDC-SL-C	Switches irrigation pump ON/OFF; 5 V relay
Temperature and Humidity Sensor	Adafruit Industries	DHT22 (AM2302)	Environmental monitoring; Temperature ±0.5 °C; Humidity ±2% RH
Web Browser	Google LLC	Google Chrome (latest stable release) https://www.google.com/chrome	Access to AWS IoT dashboard
Wi-Fi Router	TP-Link Technologies	/	Wireless communication between ESP32 and cloud; IEEE 802.11 b/g/n/ac; Model: Archer C6