Project

# Title Team Members TA Documents Sponsor
50 Urban Noise Pollution Monitoring System
 Cj Kompare
Cornell Horne
Marc Rhymes
 Surya Vasanth design_document2.pdf
final_paper1.pdf
photo1.png
photo2.png
presentation1.pdf
proposal2.pdf
video
# Urban Noise pollution Monitoring system

Team Members:
- CJ Kompare (kompare3)
- Cornell Horne (chorne7)
- Marc Rhymes (mrhymes2)



# Problem:
Cities face escalating issues related to noise pollution, affecting the well-being of residents and the environment. Traditional methods of noise monitoring lack granularity and real-time adaptability, hindering effective intervention strategies.

# Solution:
Develop a comprehensive Urban Noise Pollution Monitoring System that employs wireless, battery-powered microphones strategically placed outdoors. This system will utilize a concentrator or gateway to collect and process data from distributed microphones, providing accurate and real-time noise pollution insights for urban planning and environmental conservation.

# Solution Components:

- Wireless, Battery-Powered Microphones
- Concentrator/Gateway Device
- Centralized Data Processing Platform
- Geographic Information System (GIS)
- User Interface (Web Application)

# Subsystem 1: Wireless, Battery-Powered Microphones:
Deploy multiple wireless, battery-powered microphones an area to capture diverse noise sources. Ensure these microphones are durable, weather-resistant, and equipped with noise level sensing capabilities.

# Subsystem 2: Concentrator/Gateway Device:
Implement a concentrator or gateway device to receive, aggregate, and forward data from all distributed microphones. This device will serve as the central hub for data collection and transmission.

# Subsystem 3: Centralized Data Processing Platform:
Develop a centralized platform for processing and analyzing noise data received from the concentrator. This platform will perform real-time noise level calculations, identify patterns, and store historical data for future analysis.

# Subsystem 4: Geographic Information System (GIS):
Integrate a GIS component to map noise levels spatially, allowing for visual representations of noise distribution across the city. This would enhance and support targeted noise reduction initiatives.

# Subsystem 5: User Interface (Web Application):
Develop a web application for users to visualize noise data. The interface should provide real-time updates, historical trends, and customizable features for specific areas of interest.

# Criteria for Success:

Hourly Data Reporting: The system should successfully report noise data to the central web application every hour, providing a consistent and reliable stream of information for analysis and decision-making.

Real-time Monitoring: Achieve real-time noise level monitoring with a latency of no more than 5 minutes, ensuring users have timely access to critical noise pollution information.

Accuracy of Noise Identification: Ensure an accuracy rate of at least 90% in identifying noise sources, allowing for precise insights into the types and sources of noise affecting urban areas.

Electronic Replacement for COVID-19 Building Monitors @ UIUC

Patrick McBrayer, Zewen Rao, Yijie Zhang

Featured Project

Team Members: Patrick McBrayer, Yijie Zhang, Zewen Rao

Problem Statement:

Students who volunteer to monitor buildings at UIUC are at increased risk of contracting COVID-19 itself, and passing it on to others before they are aware of the infection. Due to this, I propose a project that would create a technological solution to this issue using physical 2-factor authentication through the “airlock” style doorways we have at ECEB and across campus.

Solution Overview:

As we do not have access to the backend of the Safer Illinois application, or the ability to use campus buildings as a workspace for our project, we will be designing a proof of concept 2FA system for UIUC building access. Our solution would be composed of two main subsystems, one that allows initial entry into the “airlock” portion of the building using a scannable QR code, and the other that detects the number of people that entered the space, to determine whether or not the user will be granted access to the interior of the building.

Solution Components:

Subsystem #1: Initial Detection of Building Access

- QR/barcode scanner capable of reading the code presented by the user, that tells the system whether that person has been granted or denied building access. (An example of this type of sensor: (https://www.amazon.com/Barcode-Reading-Scanner-Electronic-Connector/dp/B082B8SVB2/ref=sr_1_11?dchild=1&keywords=gm65+scanner&qid=1595651995&sr=8-11)

- QR code generator using C++/Python to support the QR code scanner.

- Microcontroller to receive the information from the QR code reader and decode the information, then decide whether to unlock the door, or keep it shut. (The microcontroller would also need an internal timer, as we plan on encoding a lifespan into the QR code, therefore making them unusable after 4 days).

- LED Light to indicate to the user whether or not access was granted.

- Electronic locking mechanism to open both sets of doors.

Subsystem #2: Airlock Authentication of a Single User

- 2 aligned sensors ( one tx and other is rx) on the bottom of the door that counts the number of people crossing a certain line. (possibly considering two sets of these, so the person could not jump over, or move under the sensors. Most likely having the second set around the middle of the door frame.

- Microcontroller to decode the information provided by the door sensors, and then determine the number of people who have entered the space. Based on this information we can either grant or deny access to the interior building.

- LED Light to indicate to the user if they have been granted access.

- Possibly a speaker at this stage as well, to tell the user the reason they have not been granted access, and letting them know the

incident has been reported if they attempted to let someone into the building.

Criterion of Success:

- Our system generates valid QR codes that can be read by our scanner, and the data encoded such as lifespan of the code and building access is transmitted to the microcontroller.

- Our 2FA detection of multiple entries into the space works across a wide range of users. This includes users bound to wheelchairs, and a wide range of heights and body sizes.