Al-Based Environmental Noise Mapping and Prediction Around Industrial Zones
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Abstract
Abstract- Environmental noise pollution has become a disturbing phenomenon in industrial settings, impacting kuman health, wildlife, and quality of life Long-term exposure to high-level noise has been linked to auditors disease cardiovascular disease, sleep disruption, and higher levels of stress Natural environments and biodiversity are impacted by noise pollution, resulting in ecological equilibriums Traditional noise monitoring techniques, hased typically on opportunistic measurement using mobile equipment or fixed points of measurement are of limited spatial and temporal resolution. Traditional techniques do not provide a high-resolution continuous representation of the noise field, and policymakers and urban planners struggle to enact effective mitigation strategies. This paper proposes a novel artificial intelligence All-haxed environmental noise mapping method near manufacturing zones by combining dense sensor networks and deep machine learning (ML) models The sensor nodes deployed over the target area in real time sense the audio signals and examine them using sophisticated ML models to predict noise values at unseen points and identify temporal and spatial patterns. Data preprocessing, feature engineering, model training, and validation are all part of the methodology for providing high predictive reliability and accuracy First results indicate that the Al-based strategy can generate high resolution spatial and temporal noise maps to detect hotspots and trends that are not currently being tracked by conventional techniques. These data can be used to guide industrial zoning policy, noise mitigation, and public health policy. Overall, Al and ML-based environmental noise mapping is a low-cost, scalable, and accurate solution and has the capability to leave an amazing impact on environmental monitoring as well as creating healthier and more sustainable industrial environments
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Publication Details
- Type of Publication:
- Conference Name: 8Th International Conference on Mechanical Engineering and Renewable Energy
- Date of Conference: 12/10/2025 - 12/10/2025
- Venue: Chittagong University of Engineering & Technology (CUET), Chattogram
- Organizer: Chittagong University of Engineering & Technology (CUET)