Project

# Title Team Members TA Documents Sponsor
16 Design of a Raspberry Pi–based monitoring system for shared living environments
 Denghan Xiong
Jihao Li
Mujia Li
Shixuan Ma
 design_document1.pdf
final_paper1.pdf
proposal1.pdf
 Chao Qian
# Problem

In shared living environments such as dormitories or shared apartments, traditional access control methods such as keys or passwords can be inconvenient and insecure. Keys can be lost or copied, and passwords can be shared or forgotten. These problems make it difficult to ensure security and manage access effectively.

In addition, traditional door locks cannot automatically identify who is entering or keep records of access events. Residents or administrators may want a system that can automatically recognize authorized users and log entry activities for security purposes.

Therefore, there is a need for a lightweight and low-cost smart access control system that can detect people approaching the door, identify authorized users, and manage access automatically.

# Solution Overview

Our solution is to design a smart access control system based on a Raspberry Pi for shared living environments such as dormitories or shared apartments. The system uses a PIR motion sensor to detect human presence near the door. When motion is detected, a USB camera connected to the Raspberry Pi captures images of the person standing at the door.

The captured images are processed using computer vision techniques, and a face recognition algorithm is used to determine whether the person is an authorized user. If the user is recognized, the system activates a relay module to simulate unlocking the door. If the person is not recognized, the system records the event and displays the result.

The system also includes a graphical user interface developed with PyQt5 to display the camera feed, recognition results, and system status. A local database is used to store user information and access records.

# Solution Components

## Subsystem I – Hardware System

### Hardware I.a Motion Detection Sensor
- A PIR motion sensor detects human movement near the door.
- When motion is detected, the sensor sends a signal to the Raspberry Pi.
- This signal triggers the image capture and recognition process.

### Hardware I.b Camera Module
- A USB camera connected to the Raspberry Pi captures images of the person at the door.
- The camera provides real-time video frames for face detection and recognition.

### Hardware I.c Door Control Module
- A relay module controlled by the Raspberry Pi simulates the door unlocking mechanism.
- When an authorized user is detected, the relay activates to unlock the door.

## Subsystem II – Image Processing and Recognition

### Software II.a Image Capture and Processing
- OpenCV is used to capture video frames from the camera.
- Images are preprocessed using techniques such as resizing and color conversion.

### Software II.b Face Recognition Module
- A face recognition algorithm extracts facial features from captured images.
- These features are compared with stored user data to determine the person's identity.

## Subsystem III – User Interface and System Management

### Software III.a Graphical User Interface
- A graphical interface built with PyQt5 displays the camera feed.
- It shows recognition results and system status in real time.

### Software III.b Multithreading Framework
- A multithreaded architecture allows the system to perform multiple tasks simultaneously.
- Tasks such as video capture, face recognition, and interface updates run in parallel.

### Software III.c Local Database Management
- A local database stores authorized user information.
- The database records access logs such as time, identity, and recognition results.

# Criteria of Success

- The PIR sensor can detect human motion and trigger the system automatically.
- The camera can capture images successfully for processing.
- The face recognition module can correctly identify authorized users from stored data.
- The relay module activates to simulate unlocking the door when a valid user is detected.
- The graphical interface displays the camera feed and recognition results in real time.
- The system records access events in the local database.
- The system runs smoothly on the Raspberry Pi with minimal delay.

Wireless IntraNetwork

Featured Project

There is a drastic lack of networking infrastructure in unstable or remote areas, where businesses don’t think they can reliably recoup the large initial cost of construction. Our goal is to bring the internet to these areas. We will use a network of extremely affordable (<$20, made possible by IoT technology) solar-powered nodes that communicate via Wi-Fi with one another and personal devices, donated through organizations such as OLPC, creating an intranet. Each node covers an area approximately 600-800ft in every direction with 4MB/s access and 16GB of cached data, saving valuable bandwidth. Internal communication applications will be provided, minimizing expensive and slow global internet connections. Several solutions exist, but all have failed due to costs of over $200/node or the lack of networking capability.

To connect to the internet at large, a more powerful “server” may be added. This server hooks into the network like other nodes, but contains a cellular connection to connect to the global internet. Any device on the network will be able to access the web via the server’s connection, effectively spreading the cost of a single cellular data plan (which is too expensive for individuals in rural areas). The server also contains a continually-updated several-terabyte cache of educational data and programs, such as Wikipedia and Project Gutenberg. This data gives students and educators high-speed access to resources. Working in harmony, these two components foster economic growth and education, while significantly reducing the costs of adding future infrastructure.