International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 12 | Dec 2025
p-ISSN: 2395-0072
www.irjet.net
AI-POWERED NOISE POLLUTION MAPPER & ANALYZER FOR URBAN SPACES V. N. Mahawadiwar1, Sonali P. Chanekar2, Devang Katekhaye3, Payal Kailakhe4, Shreya Awale5, Vinay Wagh6 1Assistant Professor, Dept of Electronics & Telecommunication, KDK College of Engineering, Maharashtra, India 2,3,4,5,6,UG Student Dept of Electronics & Telecommunication, KDK College of Engineering, Maharashtra, India
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Abstract - Urban areas are becoming increasingly noisy
find out how noise changes over time, space and the activities of people to develop healthier environments.
due to rapid growth in traffic, construction, and human activities. This rising noise pollution affects public health, comfort, and overall urban livability. To address this challenge, the project proposes an AI-powered Noise Pollution Mapper and Analyzer designed to monitor and understand noise conditions in real time. The system uses IoT-based sound sensors placed across different city locations to collect continuous noise data along with accurate GPS coordinates. This information is processed using artificial intelligence models that classify the type of noise and analyze patterns over time. The processed results are visualized on an interactive map, allowing users to see noise intensity and source distribution across urban spaces. By offering real-time monitoring, automatic noise identification, and predictive insights, the system provides city planners and authorities with valuable information to make informed decisions. This approach helps in creating effective noise management strategies, improving urban planning, and promoting healthier communities. The AIpowered mapper offers a modern, scalable, and data-driven solution to better understand and reduce noise pollution in growing cities.
Regrettably, majority of the noise monitoring systems employed currently are very old and not very effective. The conventional activities are based on limited monitoring devices, short measurements and manual noise readings. These techniques fail to record the real variation of noise over the day, or in different locations within a city. Consequently, police are not usually provided with real-time data, comprehensive noise trends, and visual maps of noisy locations. There is no way one can meaningfully control or curb noise pollution without proper and sustained data. Modern technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and GIS mapping, can be used to solve these problems. The project, entitled AI-Powered Noise Pollution Mapper and Analyzer in Urban Spaces is developed based on the idea of creating a smart and automated platform that would be capable of counting noise in real-time, interpreting it intelligently, and displaying the findings in a simple and comprehensible manner. Sound sensors will be installed throughout the city as IoT devices that will constantly monitor the data on noise. These sensors can detect noise levels, record audio patterns and location data via GPS. The obtained data is analyzed with the help of the state-of-the-art AI algorithms like Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks.
Key Words: AI noise mapping, IoT sensors, noise analysis, urban pollution, GIS mapping, real-time monitoring.
1. INTRODUCTION The problem of noise pollution is among the most ongoing and yet unnoticed environmental concerns in the current rapidly developing cities. With the ever-growing population in the urban areas, the number of buildings, and day-to-day activities, the amount of unwanted noise is steadily growing. The high traffic, active construction activities, active markets, machines in industries and congested social places are all causes of increasing noise. Noise, as opposed to air or water pollution, is invisible, but its negative impact on a human life cannot be underestimated. Prolonged exposure to high or continuous noise would result in stress, inability to focus, sleeping difficulties, and cardiovascular issues and low productivity. Due to these effects, city planners and environmental departments have found it significant to
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These AI models assist the system to detect the nature of noise; whether it is traffic noise, construction noise, machinery noise, or human noise; and learn how noises vary over time. The system can also estimate what the noise will be in future based on this information, and hence authorities will be warned at an early stage to enable them to make necessary act. Lastly, all the data derived is represented in interactive heat maps and maps in GIS. Such visuals assist users to find noisy areas easily, analyze daily and long term trends and make improved decisions. These insights can be used by city planners, transportation officials and environmental agencies to develop noise control strategies, design in consideration of quieter routes,
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