IoT Environmental Monitoring System
Public Water Company of the City of MantaSpearheaded development of an innovative, low-cost IoT environmental monitoring system for laboratory use, enabling real-time tracking of temperature and humidity conditions with customizable alerts.
- Express
- PostgreSQL
- React Native
- Arduino
- ESP32
- DHT22 Sensor
- Vue.js
- IoT
- MongoDB
Achievements and Results
Significant social impact: Besides directly benefiting laboratories, the system indirectly improved service quality for the 258,000 people depending on EPAM.
Cost reduction: Implementation of an economical system that automated monitoring in three key laboratories (Reagents, General, and Microbiology).
Advanced interface: Graphs were designed in the mobile app, offering detailed summaries of room status, average data, maximums, minimums, and alert logs.
Alerts and customization: Configurable alert limits, visual notifications in the app and LED screens, and real-time critical alerts.
Advanced queries: Features to query historical data in specific hourly ranges, with access to daily summaries and room status.
Guaranteed scalability: The system was designed to support new laboratories or rooms, ensuring its viability for future requirements.
This project not only demonstrated its technical efficacy but also its capacity to provide scalable and sustainable solutions to real problems, standing out as an essential tool for environmental monitoring at EPAM.
Project description
The project consisted of the design and implementation of an IoT system for real-time monitoring of temperature and humidity in the laboratories of the Empresa Pública de Agua de Manta (EPAM).
The initiative was developed under the Extreme Programming (XP) methodology, selected for its adaptability to small teams and encouragement of rapid iterations.
During development, weekly meetings were held with executives, ensuring constant alignment with the client's objectives and requirements.
The system integrated hardware and software, using DHT22 sensors connected to ESP32 microcontrollers for environmental data capture, which was transmitted through an Express backend and stored in MongoDB Atlas. The data was presented in a web application developed with React, a mobile app in React Native, and LED screens in the laboratories for local real-time visualization. Additionally, notifications were implemented via Firebase Cloud Messaging (FCM) for critical alerts, optimizing the control of environmental conditions.
Proposed hardware circuit (the larger one) compared to the existing sensor in the laboratories. 
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