Real-Time Environmental Noise Management and Control Using Raspberry Pi and Acoustic Sensors

Urban noise pollution threatens health and quality of life. This paper proposes real-time ambient noise management using acoustic sensors and a Raspberry Pi. A cost-efficient and effective noise monitoring and reduction system is the aim. The system's CPU is a Raspberry Pi. To detect noise, acoustic sensors are strategically placed. The Raspberry Pi processes sensor data in real-time and analyzes noise to gain insights. The system measures noise using FFT and noise mapping techniques. These approaches allow us to fully understand noise's properties and geographical distribution and the fundamental elements derived from acoustic data. Based on noise analysis, active control methods decrease noise pollution. This includes sound masking, adaptive noise cancellation, and intelligent activity scheduling. The Raspberry Pi makes noise control techniques easier to organize and implement. The suggested system is extensively tested in real-world conditions. Our technique successfully reduces noise pollution, identifies noise sources, and properly measures noise levels. Real-time reaction and intervention improve environmental and noise control. This research helps create a cost-effective real-time environmental noise control system. Combining the Raspberry Pi with sound sensors creates a flexible platform that may be deployed in homes, offices, and public spaces. The system's real-time noise data analysis and active noise control offer new noise management solutions.