IoT-Based Real-Time Air and Water Quality Monitoring System Using ESP 32 and ThingSpeak

Being conscious of the environment is more important than ever in the modern, fast-paced world. In most cases, centralised systems are the ones that inform us about the safety of our surroundings; yet, clean air and Water are essential for a healthy life. To bridge that gap, the ESP32 microcontroller is utilized to develop a real-time monitoring system that is straightforward, low-cost, and uncomplicated. The system utilizes sensors for measuring air quality, including the MQ2, MQ7, and MQ135; water quality sensors, such as those for turbidity and pH, are also employed. The ESP32 collects data from these sensors and sends it to a local web dashboard for real-time viewing. Additionally, it sends the data to ThingSpeak for cloud-based monitoring. Through the use of your mobile device or computer, this technology provides instantaneous information on indoor air pollution, drinking water contamination, and environmental changes occurring in local water bodies. In addition to number interpretation, we also provide fundamental interpretation, such as determining whether the readings are safe or indicate cause for alarm. Environmental sensing should be simplified to make it more accessible to everyone. In settings where the cleanliness of the air and Water is of utmost importance, such as households, farms, small enterprises, and schools, this method is effective.

Authors

Publication Details

Journal
FMDB Transactions on Sustainable Intelligent Networks
Published
2025-03-07
DOI
https://doi.org/10.69888/ftsin.2025.000369
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

IoT-Based Real-Time Air and Water Quality Monitoring System Using ESP 32 and ThingSpeak

Ravi Shankar, Malathi Subramanian, P. Srinivasan, J. Joe Fredlin
FMDB Transactions on Sustainable Intelligent Networks
Water Quality Monitoring Technologies
article

IoT-Based Real-Time Air and Water Quality Monitoring System Using ESP 32 and ThingSpeak

Ravi Shankar, Malathi Subramanian, P. Srinivasan, J. Joe Fredlin
article en

Abstract

Being conscious of the environment is more important than ever in the modern, fast-paced world. In most cases, centralised systems are the ones that inform us about the safety of our surroundings; yet, clean air and Water are essential for a healthy life. To bridge that gap, the ESP32 microcontroller is utilized to develop a real-time monitoring system that is straightforward, low-cost, and uncomplicated. The system utilizes sensors for measuring air quality, including the MQ2, MQ7, and MQ135; water quality sensors, such as those for turbidity and pH, are also employed. The ESP32 collects data from these sensors and sends it to a local web dashboard for real-time viewing. Additionally, it sends the data to ThingSpeak for cloud-based monitoring. Through the use of your mobile device or computer, this technology provides instantaneous information on indoor air pollution, drinking water contamination, and environmental changes occurring in local water bodies. In addition to number interpretation, we also provide fundamental interpretation, such as determining whether the readings are safe or indicate cause for alarm. Environmental sensing should be simplified to make it more accessible to everyone. In settings where the cleanliness of the air and Water is of utmost importance, such as households, farms, small enterprises, and schools, this method is effective.

FMDB Transactions on Sustainable Intelligent NetworksVol. 2(1)
SRM Institute of Science and Technology
Openalex Percentile: Top 77%
Water Quality Monitoring Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.