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.

Autonomous Sailboat

Riley Baker, Arthur Liang, Lorenzo Rodriguez Perez

Autonomous Sailboat

Featured Project

# Autonomous Sailboat

Team Members:

- Riley Baker (rileymb3)

- Lorenzo Pérez (lr12)

- Arthur Liang (chianl2)

# Problem

WRSC (World Robotic Sailing Championship) is an autonomous sailing competition that aims at stimulating the development of autonomous marine robotics. In order to make autonomous sailing more accessible, some scholars have created a generic educational design. However, these models utilize expensive and scarce autopilot systems such as the Pixhawk Flight controller.

# Solution

The goal of this project is to make an affordable, user- friendly RC sailboat that can be used as a means of learning autonomous sailing on a smaller scale. The Autonomous Sailboat will have dual mode capability, allowing the operator to switch from manual to autonomous mode where the boat will maintain its current compass heading. The boat will transmit its sensor data back to base where the operator can use it to better the autonomous mode capability and keep track of the boat’s position in the water. Amateur sailors will benefit from the “return to base” functionality provided by the autonomous system.

# Solution Components

## On-board

### Sensors

Pixhawk - Connect GPS and compass sensors to microcontroller that allows for a stable state system within the autonomous mode. A shaft decoder that serves as a wind vane sensor that we plan to attach to the head of the mast to detect wind direction and speed. A compass/accelerometer sensor and GPS to detect the position of the boat and direction of travel.

### Actuators

2 servos - one winch servo that controls the orientation of the mainsail and one that controls that orientation of the rudder

### Communication devices

5 channel 2.4 GHz receiver - A receiver that will be used to select autonomous or manual mode and will trigger orders when in manual mode.

5 channel 2.4 GHz transmitter - A transmitter that will have the ability to switch between autonomous and manual mode. It will also transfer servos movements when in manual mode.

### Power

LiPo battery

## Ground control

Microcontroller - A microcontroller that records sensor output and servo settings for radio control and autonomous modes. Software on microcontroller processes the sensor input and determines the optimum rudder and sail winch servo settings needed to maintain a prescribed course for the given wind direction.

# Criterion For Success

1. Implement dual mode capability

2. Boat can maintain a given compass heading after being switched to autonomous mode and incorporates a “return to base” feature that returns the sailboat back to its starting position

3. Boat can record and transmit servo, sensor, and position data back to base

Project Videos