Fuzzy logic-based IoT system for optimizing irrigation with cloud computing: Enhancing water sustainability in smart agriculture - Abdennabi Morchid; Zafar Said; Almoataz Y. Abdelaziz; Pierluigi Siano; Hassan Qjidaa (Smart Agricultural Technology)
Faced with the growing challenges of water scarcity and the effects of climate change, intelligent irrigation management is essential to guarantee food security and promote sustainable agriculture. Traditional irrigation methods are often inefficient, waste water and expose crops to water stress. This paper proposes an innovative irrigation system integrating the Internet of Things (IoT), embedded systems, fuzzy logic and cloud computing for optimized water management. The system is based on three layers: IoT devices in the field comprising ESP32 microcontrollers, temperature and humidity sensors and actuators; a cloud layer using ThingSpeak for real-time data collection and analysis via HTTP protocol; and an interactive dashboard for irrigation monitoring and control. Mathematical modeling plays a key role, integrating fuzzy logic to dynamically adjust irrigation according to environmental conditions. MATLAB is used to simulate and visualize fuzzy membership functions, enabling optimized decision-making. Results show that the system reduces water losses by adjusting watering periods according to soil temperature and humidity. Thanks to ThingSpeak, it effectively maintains soil humidity close to the target threshold of 62 %, ensuring more precise, weather-responsive irrigation. Evaluation over an extended period shows a significant reduction in water wastage thanks to strategic management based on well-defined rules. What's more, with a cost of just 32 USD, this IoT system proves more affordable than conventional methods requiring significant investment in infrastructure and maintenance. This intelligent irrigation system represents a promising solution for sustainable water management in agriculture. By integrating real-time soil and climate data, it improves water efficiency, optimizes yields and minimizes the risk of water stress, thus contributing to the resilience of agricultural practices in the face of current and future environmental challenges.