Affordable IoT-Based Irrigation System Cuts Water Use by 70% in Farming Trials

Faced with the escalating challenge of water scarcity and the disruptive impacts of climate change, researchers from Sidi Mohamed Ben Abdellah University in Morocco, the United Arab Emirates University, Ain Shams University, and Future University in Egypt, alongside collaborators from the University of Salerno in Italy and the University of Johannesburg in South Africa, have designed an innovative irrigation system. Their work focuses on fusing the Internet of Things (IoT), fuzzy logic, and cloud computing to modernize farming practices and achieve water sustainability. Unlike traditional irrigation methods, which often rely on rigid schedules or crude thresholds, this system adapts to environmental variations in real time, promising more resilient farming in water-stressed regions.

The Three Layers of Intelligence

At the core of this solution is a three-layer architecture that integrates field devices, cloud processing, and user interaction. In the field, ESP32 microcontrollers connect to soil moisture, temperature, and humidity sensors, as well as irrigation pumps that act as actuators. These devices continuously collect data and transmit it securely via the HTTP protocol. The second layer, based on the ThingSpeak cloud platform, aggregates, stores, and analyzes this incoming data, offering insights and historical patterns. The third layer provides farmers with an interactive dashboard where complex technical data is transformed into simple, actionable visuals. This dashboard not only allows them to monitor conditions but also to adjust irrigation settings with ease. By combining hardware, cloud, and user interface, the architecture ensures that irrigation decisions are precise, transparent, and farmer-friendly.

How Fuzzy Logic Changes the Game

The distinctive element of this system is its reliance on fuzzy logic, which mimics human reasoning by categorizing inputs into linguistic terms such as “low,” “medium,” or “high.” Temperature readings between 15 and 45 degrees Celsius, for example, are divided into three categories, while soil moisture between 55 and 70 percent is grouped into low, desired, and high ranges. A set of nine fuzzy rules links these inputs to irrigation outcomes labeled as short, medium, or long durations. Defuzzification then converts these qualitative outputs into precise watering times ranging from two to ten minutes. If soil moisture is low and temperature is high, the system assigns a longer irrigation period to counter evaporation, while in conditions of high soil moisture, even at high temperatures, it shortens irrigation to prevent waste. This flexibility allows the system to adapt seamlessly to variable weather conditions, offering an improvement over conventional threshold-based models.

Field Testing and Real-World Impact

The research team tested the system in Morocco’s Fez region, an area where traditional agricultural methods are still dominant. MATLAB simulations combined with Arduino IDE programming for ESP32 hardware control revealed that the system consistently kept soil moisture close to the ideal 62 percent level, even during periods of intense heat. Over the course of the study, soil moisture fluctuated between 57.5 and 65 percent, with the fuzzy logic controller dynamically adjusting irrigation times. At peak midday temperatures of 40 degrees Celsius, irrigation lasted six minutes, while cooler periods required minimal watering. This fine-tuned response reduced losses from evapotranspiration and prevented water stress in crops. Compared to conventional irrigation, the system achieved water savings of up to 70 percent, demonstrating that it can both conserve resources and sustain healthy plant growth.

The affordability of the system is equally striking. A detailed cost analysis showed that the entire setup, including the ESP32 microcontroller, soil moisture sensor, DHT22 sensor, water pump, and auxiliary components, requires only 32 US dollars. This stands in sharp contrast to traditional systems that demand significant investments in infrastructure, pipes, pumps, and labor. By offering a low-cost, high-impact solution, the researchers have made smart irrigation technology accessible to smallholder farmers, particularly in developing regions where financial barriers often block innovation.

Challenges and the Road Ahead

Despite its promise, the study acknowledges challenges in scaling and adoption. Deploying the system on large farms would require extensive sensor networks and stronger communication infrastructure, raising costs and logistical hurdles. Rural areas also face connectivity issues, since the system depends on internet access for real-time monitoring, though technologies such as LoRaWAN could mitigate this obstacle. Computational demands are another limitation, as fuzzy logic requires significant processing power. Furthermore, the definition of membership functions, central to fuzzy systems, remains subjective and may introduce inconsistencies without rigorous validation. Beyond technical barriers, socio-economic realities play a role. Farmers may resist adopting new technologies without clear incentives, training, and demonstrations of value. The authors argue for subsidies, public-private partnerships, and awareness programs to bridge this gap.

Future directions for this research are ambitious and forward-looking. One major avenue is the integration of renewable energy, particularly solar power, to make the system energy self-sufficient and more viable in remote areas. The researchers also plan to harness artificial intelligence and machine learning to refine irrigation schedules further, enabling predictive adjustments tailored to specific crops, soils, and climates. Expanding the system to handle diverse agricultural settings will enhance its relevance globally. Data security remains a priority, with future efforts focusing on stronger encryption and secure transmission protocols. Another key development will be the creation of user-friendly web and mobile interfaces that replace MATLAB with simpler, more accessible platforms. These steps aim to make the technology more robust, scalable, and practical for widespread adoption.

In essence, the collaboration among institutions from Morocco, the UAE, Egypt, Italy, and South Africa highlights how modern technology can reimagine age-old farming practices. By uniting low-cost sensors, cloud computing, and intelligent decision-making, this irrigation system not only conserves water but also builds resilience against the uncertainties of climate change. For farmers across water-scarce regions, it represents a powerful lifeline: an affordable, adaptable, and intelligent tool to secure both food production and environmental sustainability.