Station for the Remote Measurement of the Acoustic Contamination
This bachelor's thesis project presents the development of an IoT-enabled environmental monitoring system that measures noise pollution and microclimate data using Raspberry Pi. The project combines hardware engineering, data scince and business analysis for comprehensive urban noise solution.
Station for the Remote Measurement of the Acoustic Contamination
The system integrates a Raspberry Pi 4 with an AudioInjector sound card, custom-designed microphone/preamplifier, AM3203 environmental sensor, and IP65 waterproof enclosure for robust noise monitoring.
Technical implementation
- Acoustic analysis
- Equivalent continous level (Leq)
- Peak measurements (Lmax, Lmin)
- Statistical analysis (L01, L10, L50, L90, L99)
- Environmental monitoring: Temperature and humidity sensing
- Real-time dashboard: Power BI visualization platform
Preamplifier Frequency Response Analysis
Laboratory characterization of the custom-designed preamplifier and microphone system in anechoic chamber conditions.
System Performance
- Processor utilization analysis under continuous monitoring loads
- Battery life optimization for field deployment
- Data accuracy comparison with professional sound level meters
Commercial Viability Study
- Market research for municipal and industrial applications
- Operational marketing plan
- Production and operations strategy
- Financial projections and ROI analysis
- Legal compliance framework
Download Full Thesis (PDF) Includes complete schematics and business plan
Download User Manual (PDF) Contains detailed installation instructions and technical specifications.
Data Visualization
Real-time Data Display
Interactive menu showing current noise levels (Leq, Lmax), environmental data, and historical trends