SPAI-EH: An IoT and Generative-AI System for Hail and Heavy-Rain Protection in Smallholder Agriculture in Puebla, Mexico

Abstract

Hail and sudden heavy rainfall regularly destroy vegetable and grain crops in the state of Puebla, Mexico, with the state's rural-development authority reporting thousands of damaged hectares within a single growing cycle. This paper presents SPAI-EH, a low-cost Internet of Things system that detects intense rainfall and hail in real time, automatically closes a protective gate over the affected plot, and routes the captured water toward irrigation reuse. The pilot implementation uses an ESP32 microcontroller simulated in Wokwi, combining a DHT22 temperature and humidity sensor with an analog potentiometer that emulates a rain and hail intensity sensor, a servo-actuated gate, a warning LED, and a liquid-crystal display. Readings are classified locally through threshold rules and, when connectivity is available, through a call to a cloud generative-AI model that returns a hazard classification and a gate action. Every reading is stored in an Oracle Application Express database accessed through RESTful web services, and a MIT App Inventor mobile application lets a grower monitor five simulated plots on a map and manually close a gate. Across the recorded test window, the system correctly distinguished normal conditions from three simulated hail events and one heavy-rain event in a single plot, while the remaining plots stayed within expected ranges. The paper also discusses the applicable IEEE IoT standards and the gap between the classroom pilot and a field-ready deployment.