From Data to Decisions: A Smart IoT and Cloud Approach to Environmental Monitoring
Environmental monitoring plays a crucial role in various domains, including agriculture, healthcare, and manufacturing, where optimal environmental conditions are essential for productivity and safety. In this project, we present a smart environmental monitoring system that leverages IoT (Internet o...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00008.pdf |
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| Summary: | Environmental monitoring plays a crucial role in various domains, including agriculture, healthcare, and manufacturing, where optimal environmental conditions are essential for productivity and safety. In this project, we present a smart environmental monitoring system that leverages IoT (Internet of Things) technology and data analytics to monitor temperature and humidity levels in real-time. The system consists of a network of sensor nodes deployed in the target environment, comprising ESP32 microcontrollers and DHT11 sensors for data collection. The sensor nodes transmit data using the MQTT (Message Queuing Telemetry Transport) protocol to a cloud-based MQTT Broker hosted on HiveMQ Cloud. Data processing and visualization are handled by Node-RED, which subscribes to MQTT topics, processes incoming data streams, and stores them in a time-series database, InfluxDB Cloud. The collected data is then visualized in real-time using Grafana dashboards, which are embedded within a Flask web application, providing stakeholders with seamless access to actionable insights into environmental conditions. The smart environmental monitoring system offers numerous benefits, including improved decisionmaking, proactive maintenance, and enhanced productivity. Future enhancements could include the integration of additional sensors and the application of machine learning algorithms for predictive analytics. Overall, the project demonstrates the potential of IoT and data analytics in addressing real-world challenges related to environmental monitoring. |
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| ISSN: | 2267-1242 |