A Farm Environmental Monitoring System Based on The Internet of Things and Artificial Intelligence Under Field Conditions in Sudan

Document Type : Original Article

Authors

1 Yellow River Delta Intelligent Agricultural Machinery Equipment Industry Academy, Dongying 257300, China

2 Yellow River Delta Intelligent Agricultural Equipment Industry Academy, Dongying, China

3 Yellow River Delta intelligent Agricultural Machinery Equipment Industry Academy, 257300.China

4 Al-Azhar University, Assiut Branch, College of Agricultural Engineering, 71524

5 Neptune IOT, Khartoum, Sudan

6 4.0 for services and agriculture equipment Ltd. Khartoum, Sudan

10.21608/agro.2025.386734.1702

Abstract

The Internet of Things (IoT) based environmental monitoring system project addresses Sudan's challenges caused by expensive irrigation systems and poor agricultural productivity. Implementing IoT frameworks, along with soil moisture sensors within an IoT-based system, improves agricultural management processes, improves irrigation results, and enhances the accuracy of planting methods. IoT soil moisture sensors identify critical checkpoints by simultaneously monitoring temperature data, while monitoring soil water content levels and pH properties, as well as its nutrient requirements. LoRa WAN interfaces on the server enable soil moisture readings to be accessed by farmers using software applications to display current and historical data. Using artificial intelligence, this system processes collected data to generate yield forecasts, as well as environmental monitoring statistics. The new system's reduced pivot rotation time reduces operations by 16%, providing high-quality irrigation that doesn't harm plants. The implemented system has contributed to improved operational performance while reducing overall costs at the same time. The use of IoT-based crop monitoring platforms represents sustainability because automated irrigation systems work hand in hand with the lower operating expenses of precision agriculture. This advanced system improves traditional agricultural methods by improving management functions allowing for potential implementation in agricultural areas of Sudan as well as neighboring locations.

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