Project 7: Sound Level Monitoring System (Microphone Variant) Key Components: ⚫Server: Raspberry Pi • Input: Microphone (Sound Sensor) ⚫ Client: Laptop/Mobile Device Real-time data transmission is managed by Python scripts that serve as the backbone of the client-server communication. Description: This system continuously monitors ambient noise levels using a microphone sensor. The Raspberry Pi calculates the sound intensity and sends real-time data to a client application. If the measured noise exceeds a preset threshold (for example, 80 dB), the system triggers an alert, helping manage environments sensitive to noise levels such as classrooms or industrial settings. (implement communication between raspberry pi and computer/ mobile device using one of the protocols UDP or TCP) Example of Operation: • Server Operation: 1. Set up the microphone sensor on the Raspberry Pi to continuously sample ambient sound. 2. Convert the raw sensor data into decibel (dB) or any other readings. 3. If the noise level exceeds the threshold, automatically send an alert message to the client. • Client Operation: 1. Connect to the Raspberry Pi's data stream via a network interface. 2. Display real-time sound intensity levels on a user interface. 3. Trigger alerts if noise levels become too high.
Project 7: Sound Level Monitoring System (Microphone Variant) Key Components: ⚫Server: Raspberry Pi • Input: Microphone (Sound Sensor) ⚫ Client: Laptop/Mobile Device Real-time data transmission is managed by Python scripts that serve as the backbone of the client-server communication. Description: This system continuously monitors ambient noise levels using a microphone sensor. The Raspberry Pi calculates the sound intensity and sends real-time data to a client application. If the measured noise exceeds a preset threshold (for example, 80 dB), the system triggers an alert, helping manage environments sensitive to noise levels such as classrooms or industrial settings. (implement communication between raspberry pi and computer/ mobile device using one of the protocols UDP or TCP) Example of Operation: • Server Operation: 1. Set up the microphone sensor on the Raspberry Pi to continuously sample ambient sound. 2. Convert the raw sensor data into decibel (dB) or any other readings. 3. If the noise level exceeds the threshold, automatically send an alert message to the client. • Client Operation: 1. Connect to the Raspberry Pi's data stream via a network interface. 2. Display real-time sound intensity levels on a user interface. 3. Trigger alerts if noise levels become too high.
Chapter13: Internet And Distributed Application Services
Section: Chapter Questions
Problem 1VE
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this project is NOT for graded(marks) purposes, please help me with the introduction. give me answers for the project. i will include an image explaining everything about the project.
Transcribed Image Text:Project 7: Sound Level Monitoring System (Microphone Variant)
Key Components:
⚫Server: Raspberry Pi
• Input: Microphone (Sound Sensor)
⚫ Client: Laptop/Mobile Device
Real-time data transmission is managed by Python scripts that serve as the backbone of the
client-server communication.
Description:
This system continuously monitors ambient noise levels using a microphone sensor. The
Raspberry Pi calculates the sound intensity and sends real-time data to a client application. If
the measured noise exceeds a preset threshold (for example, 80 dB), the system triggers an
alert, helping manage environments sensitive to noise levels such as classrooms or industrial
settings. (implement communication between raspberry pi and computer/ mobile device using
one of the protocols UDP or TCP)
Example of Operation:
• Server Operation:
1. Set up the microphone sensor on the Raspberry Pi to continuously sample
ambient sound.
2. Convert the raw sensor data into decibel (dB) or any other readings.
3. If the noise level exceeds the threshold, automatically send an alert message to
the client.
• Client Operation:
1. Connect to the Raspberry Pi's data stream via a network interface.
2. Display real-time sound intensity levels on a user interface.
3. Trigger alerts if noise levels become too high.
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