Project

# Title Team Members TA Documents Sponsor
21 Continuous Vehicles Capture
 Binyang Shen
Jiawei Zhang
Yining Guo
Zijin Li
 design_document2.pdf
final_paper2.pdf
final_paper3.pdf
presentation1.pptx
proposal1.pdf
#Problem

With the increasing size of cities and growing traffic flow, traditional traffic monitoring means (e.g., manual observation, fixed detectors, etc.) are often difficult to balance real-time and accuracy. The traffic department is in urgent need of a portable monitoring system that can obtain real-time road traffic density, number of vehicles and congestion conditions to assist traffic management and optimize traffic flow.

#Solution Overview

The aim of this project is to build a Raspberry Pi based traffic monitoring system that utilizes cameras for uninterrupted video capture and image processing algorithms to identify and count vehicles in real time. Meanwhile, the system can analyze the traffic density and congestion level in real time to provide data support for traffic flow optimization. Ultimately, we will create a visual dashboard that enables relevant departments or personnel to view road conditions and receive congestion alerts at any time, improving the efficiency and accuracy of traffic management.

#Solution Components

Outdoor enclosures and camera mounting systems
Design and build a protective outdoor housing to ensure that the camera can consistently and steadily capture road conditions in all weather conditions.
Consider waterproof, dustproof and temperature control to ensure the reliability of the system in outdoor environment.
Image Processing and Vehicle Recognition Module
Image processing algorithms deployed on the Raspberry Pi accurately identify and count vehicles in a live video stream.
Vehicle types and traffic density are analyzed using deep learning or traditional computer vision techniques.
Real-time visualization dashboards
Aggregate information such as the number of identified vehicles, traffic flow density, etc. through the data interface.
Design user-friendly graphical interface to present key indicators in charts, real-time curves, etc. and configure congestion alert push.

#Criteria for Success

Accuracy assessment: Vehicle detection and counting should be correct to a usable level (≥ 90%).
Real-time requirements: the system is capable of near real-time video analysis on the Raspberry Pi platform and rapid visualization of the data.
Robustness testing: Multiple tests under different weather, light and traffic flow conditions to ensure reliable operation of the outdoor chassis and the overall system.
Congestion Early Warning Effect: Evaluate the system's ability to identify and warn of congestion status, and verify its effectiveness in assisting traffic management decisions.

Through the gradual realization of the above goals, we will provide a set of efficient, low-cost, low-power and stable real-time traffic monitoring solutions for the traffic management department, contributing to the reduction of urban congestion and the improvement of travel efficiency.

Mimicry Stage Lighting Control System

Haozhe Chen, Ruiqi Li, Anqi Tan, Zhaohua Yang

Featured Project

This project aims to build a mimicry stage lighting control system. Generally speaking, the direction control system (usually a robot arm) will imitate the movements of the operator's arms so that the direction of the light can be controlled arbitrarily. In addition, the color of the light array can be determined by either the operator or the inherent information extracted from the music that is being played. Also, the whole system can be built in small size and can be installed easily, so that it can be deployed in scenarios like home parties.

More specifically, an operator (mostly a presenter or DJ) holds (or wears) a control device, the joystick, in each hand. The joysticks track the movement of each arm and transmit the direction information to the central server. This information is then processed and redirected to the mounted projector light arrays to control the actual direction of beams. Each hand controls each side of the lighting array. The system can also memorize a period of movement and playback. Besides, the color of the lights can be manually determined or be automatically determined by the rhythm or tempo of the music being played. The movement of the light gimbal can even be determined by the inherent feature of music.

Project Videos