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IoT Based Vehicle Horn & Noise Detection System

📑 10 slides 👁 37 views 📅 1/24/2026
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Introduction

Project aims to reduce noise pollution using IoT

Introduction
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Problem Statement

  • Noise pollution causes health issues & disturbances
  • Manual monitoring is inefficient and inconsistent
  • Modified vehicle exhausts exceed permissible noise levels
  • Lack of automated systems for noise violation detection
Problem Statement
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System Architecture

  • Microcontroller (Arduino/RPi) processes sound input
  • Sound sensor detects dB levels above threshold
  • Buzzer and OLED display provide instant alerts
  • IoT module sends data to cloud for monitoring
System Architecture
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Key Components

  • Sound sensor module (LM393 based)
  • ESP8266 for WiFi connectivity
  • 0.96" OLED display for warnings
  • Active buzzer for audible alert
Key Components
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Working Principle

  • Continuously monitors ambient sound levels
  • Compares readings with preset noise threshold
  • Triggers alerts when threshold is exceeded
  • Stores violation data with timestamp for analysis
Working Principle
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Threshold Calibration

  • Adjustable for different locations (residential/commercial)
  • Set slightly above normal traffic noise levels
  • Complies with local noise pollution regulations
  • Can be modified via simple code adjustment
Threshold Calibration
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Alert Mechanism

  • Buzzer sounds for 5-10 seconds upon violation
  • Display shows "NOISE VIOLATION DETECTED"
  • Multiple violations trigger escalated alerts
  • Optional SMS notification to authorities
Alert Mechanism
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IoT Integration

  • Data logged to cloud platform (ThingSpeak/Blynk)
  • Enables remote monitoring of noise hotspots
  • Historical data for pattern analysis and reports
  • Potential integration with traffic management systems
IoT Integration
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Applications

  • Near schools, hospitals, and residential areas
  • Traffic police enforcement of noise regulations
  • Smart city infrastructure development
  • Research on urban noise pollution patterns
Applications
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Conclusion

  • Effective solution for automated noise monitoring
  • Low-cost implementation with basic components
  • Scalable for city-wide deployment
  • Contributes to smarter, quieter urban spaces
Conclusion
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