Iot Based Environment Monitoring System

Year : 2025 | Volume : 15 | Issue : 02 | Page : 8 14
    By

    Dukale Shivraj Haribhau,

  • Rakhi Bornare,

  • Aher Atharva Pankaj,

  • Inamdar Rijvan Raheman,

  • Shivprasad Ganesh Kadam,

  1. Research Scholar, Department of Computer Technology Sanjivani K.B.P Polytechnic Kopargaon, Maharashtra, India
  2. Lecturer, Department of Computer Technology Sanjivani K.B.P Polytechnic Kopargaon, Maharashtra, India
  3. Research Scholar, Department of Computer Technology Sanjivani K.B.P Polytechnic Kopargaon, Maharashtra, India
  4. Research Scholar, Department of Computer Technology Sanjivani K.B.P Polytechnic Kopargaon, Maharashtra, India
  5. Research Scholar, Department of Computer Technology Sanjivani K.B.P Polytechnic Kopargaon, Maharashtra, India

Abstract

Pollution combined with climate change is creating long-term problems for natural resources. Their impact on soil, air, and water cleanlinessis growing, requires smart, immediate solutions. In this paper, we report on an IoT-based Environment Monitoring System whose purpose is to monitor the air quality, temperature, humidity, and soil moisture content. It consists of an Arduino Uno, gas sensors (MQ135, MQ9, MQ6), a temperature sensor LM35, a soil moisture sensor, and a GPRS modem used for transmitting data. After data collection, Python and machine learning is used for data processing, trend analysis, and hazards prediction. Front end implementation is based on React while backend is built using Node.js to provide real-time user interactivity. Users can easily monitor environmental parameters using web and mobile dashboards created with React and React Native. When pollutant levels rise above preset levels the system automatically sends SMS notifications through a cloud service to appropriate institutions. Implementing machine learning improves prediction capabilities, consequently enabling timely responses to environmental disasters. This system, which is affordable and easy to scale, can be used in agricultural, industrial and urban settings. By utilizing cloud, IoT, and machine learning Artificial Intelligence, the suggested method fosters automation and efficiency in monitoring the environment. The system proved to be accurate in estimating the number of pollutants and predicting their changes over time, which makes it a suitable alternative to the traditional approaches. This thesis underlines the possibilities offered by IoT around environmental problems and the need to act based on information when dealing with pollution issues. Adding 5G, supporting edge solutions for quicker computation, and AI-based advice will automate the management of the environment for future developments.

Keywords: Management, solve, harm, resources, pollution, recycle, organic, materials, properly, landfills, harmful, gases, environment, nutrient-rich, fertilizer, alternative, chemical, quality, emissions, sustainability, collaboration

[This article belongs to Journal of Instrumentation Technology & Innovations ]

How to cite this article:
Dukale Shivraj Haribhau, Rakhi Bornare, Aher Atharva Pankaj, Inamdar Rijvan Raheman, Shivprasad Ganesh Kadam. Iot Based Environment Monitoring System. Journal of Instrumentation Technology & Innovations. 2025; 15(02):8-14.
How to cite this URL:
Dukale Shivraj Haribhau, Rakhi Bornare, Aher Atharva Pankaj, Inamdar Rijvan Raheman, Shivprasad Ganesh Kadam. Iot Based Environment Monitoring System. Journal of Instrumentation Technology & Innovations. 2025; 15(02):8-14. Available from: https://journals.stmjournals.com/joiti/article=2025/view=209915


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Regular Issue Subscription Review Article
Volume 15
Issue 02
Received 04/04/2025
Accepted 09/04/2025
Published 10/05/2025
Publication Time 36 Days
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