Intelligent irrigation systems represent a cornerstone of modern horticultural engineering, revolutionizing water management in landscapes, nurseries, and urban green spaces. These systems integrate sensor technology, data analytics, and automated controls to deliver precise water amounts based on real-time plant and environmental conditions, reducing water waste by up to 50% compared to traditional sprinkler methods. In large-scale horticultural projects, such as public parks or commercial nurseries, the implementation of these systems has shown to improve plant survival rates by 30% while lowering operational costs by 25%.
At the core of these systems lies a network of soil moisture sensors (SMS) with a measurement accuracy of ±2% volumetric water content. Deployed at root zone depth (typically 15–30 cm), these sensors transmit data wirelessly via LoRaWAN or NB-IoT protocols to a central controller, updating soil conditions every 15 minutes. The controller, equipped with machine learning algorithms, processes data such as evapotranspiration rates (calculated using weather station inputs: temperature, humidity, wind speed, and solar radiation) and plant-specific water requirements (e.g., 20–30 mm/week for turfgrass vs. 50–70 mm/week for young trees).
