Sensor Learning Application for Precision Agriculture

Abstract

This paper presents a Sensor Learning Application for Precision Agriculture that will assist students in getting live data (from the temperature, soil moisture, and humidity sensors) for efficient environment monitoring, which will enable them to increase their understanding of the purpose of learning. The Sensor Learning Application for Precision Agriculture is proposed, where the three sensor kits have been developed as a teaching tool to help students gain the optimum knowledge for real-world application. The agriculture site was developed to describe the real situation to students with the aim for students to experience the use of sensors for real application and to ensure students do not learn only theoretically; they can be exposed to the real environment to collect the data. Sensor Learning Application is hybridized with different sensors, which are the Sun Heat Sensor Detector, Soil Moisture Sensor Kit, and Sensor Monitoring Devices integrated with a Wi-Fi module using ESP32 that will yield a live data feed using Blynk software. This project supports the Sustainable Development Goals (SDG) that successfully increase the quality of education, provide the sensor trainer kit, and indirectly achieve sustainable energy, economic growth, and social sustainability at the agriculture project site.