Plataforma web para monitoreo y visualización de parámetros ambientales en café mediante sensores IoT

Abstract

The main objective of this study was to design and develop a web platform for real-time monitoring of air and soil parameters in coffee plantations. The research was carried out at Hacienda La Papaya, Saraguro, Ecuador. The software development methodology used was SCRUM, which is oriented to the creation of fast and adaptable solutions to change. For data collection, an IoT sensor network was implemented using LoRa e32 modules that allowed wireless communication over long distances in areas without internet. The sensors used were: RS485 for the soil (measuring NPK, humidity, temperature, salinity, conductivity, and pH variables) and AM2302 for the air (temperature and humidity). An HLK-RM08 gateway was used for data transmission. For data processing, a backend was structured in Node.js, in charge of receiving and validating the data coming from the sensors and then storing them in the PostgreSQL database. For the visualization of real-time information, Grafana was used to create interactive panels,which allowed a more in-depth analysis of the data. The results obtained demonstrated the functionality and reliability of the platform, the processing and data storage capacity was validated for the end users' needs, which was 500 readings/hour, with a latency of less than one minute in the dashboard. This solution was validated as a viable and low-cost tool that optimizes agronomic management, thus boosting agriculture and creating a base from which it can be expanded with the implementation of predictive modules, georeferencing, and even artificial intelligence.