Keerthi J,
Sneha,
Pavithra R,
Shashikala,
- Student Reva University Yelahanka Karnataka India
- Student Reva University Yelahanka Karnataka India
- Student Reva University Yelahanka Karnataka India
- Student Reva University Yelahanka Karnataka India
Abstract
This paper introduces a robust IoT-based industrial pollution monitoring system aimed at addressing the critical need for effective environmental management in industrial settings. By leveraging sensor networks and real-time data analytics, the system provides continuous monitoring of various pollutants emitted from industrial activities. The integration of IoT devices streamlines data collection, transmission, and analysis, offering timely insights for proactive decision-making. This system not only facilitates compliance with environmental regulations but also helps mitigate adverse impacts on surrounding ecosystems, thereby promoting sustainable industrial practices. The proposed solution underscores the importance of utilizing IoT capabilities to foster environmental sustainability and enhance the well-being of communities affected by industrial operations. Through continuous monitoring and immediate data processing, the system ensures that industrial pollution is kept within permissible levels, reducing the risk of environmental harm. Additionally, the real-time feedback loop allows industries to promptly address pollution incidents, preventing long-term ecological damage. Overall, this innovative approach demonstrates how advanced technology can be harnessed to achieve a balance between industrial development and environmental preservation, ensuring a healthier and more sustainable future for all.
Keywords: IoT , Industrial pollution, Monitoring system, Environmental sustainability, Real-time data, Sensor networks
[This article belongs to International Journal of Pollution: Prevention & Control(ijppc)]
References
[1] ”Radical sound valuation of fetal weight with the use of deep learning “for publication in Proceedings of the 1st International Conference on Engineering, Medicine, Management, Arts and Sciences Volume 2742, Issue 1, AIP Conf. Proc. 2742, 020044 (2024) [2] “An Economical Deep Learning Framework for COVID-19 Diagnosis Using Lung Ultrasound Images”, International Conference on Advances in Science, Engineering and Technology(ICASET-2022), ISBN : 9788770227896,doi: [3].A Boubrima, W H Benchuit and Rivano, “Optimal WSN Deployment Models for Air Pollution Monitoring”, IEEE Transactions on Wireless Communications. [4] Zumyla Shanaz, Prem Kumar, R Rahul and Rajesh Kumar, “IoT based Industrial Pollution Monitoring System”, International Research Journal of Engineering and Technology (IRJET), vol. 06, no. 03, Mar 2019. [5]. Kunja Bihari and Swain G. Santamanyu, “Smart Industry Pollution Monitoring and Controlling using LabVIEW based IoT”, International Conference on Sensing Signal Processing and Security (ICSSS), 2017 [6]. ] B. C. A., R. P, and N. Kumar, Auto Care: Analysis and implementation of IOT based vehicular monitoring to detect accidents and pollution, SSRN Electronic Journal. (2019). doi:10.2139/ssrn.3462229. [7]. “Health impacts of particulate pollution in a megacity—Delhi, India”, Environmental Development, April 2013. Vol. 6, pp. 8-20 [8]. L Devahema and P.V. Sai Surya Vamsi, “IOT based Air Pollution Monitoring System”, Journal of Network Communications and Emerging Technologies (JNCET), vol. 8, no. 4, April 2018. [9]. Zumyla Shanaz, Prem Kumar, R Rahul and Rajesh Kumar, “IoT based Industrial Pollution Monitoring System”, International Research Journal of Engineering and Technology (IRJET), vol. 06, no. 03, Mar 2019. [10]. H. Priority, A. Air and Q. Monitoring, South African Weather Service – Highveld Priority Area Air Quality Monitoring Network Monthly Report, pp. 1-55, April 2017. [11]. L. Muduli, P. K. Jana and D. P. Mishra, “Wireless sensor network based fire monitoring in underground coal mines: A fuzzy logic approach”, Process Safety and Environmental Protection, vol. 113, pp. 435-447, 2018. [12]. M. Skilton and F. Hovsepian, “The Technology of the 4th Industrial Revolution”, The 4th Industrial Revolution, 2018.
Volume | 02 |
Issue | 02 |
Received | May 23, 2024 |
Accepted | August 4, 2024 |
Published | August 28, 2024 |