# Title Team Members TA Documents Sponsor
22 Fingerprint Recognition Door Lock
Chengrui Wu
Hanggang Zhu
Haoran Yuan
Lizhuang Zheng
Meng Zhang
# Team Members

Chengrui Wu (cw70)
Hanggang Zhu (hz66)
Haoran Yuan (haorany7)
Lizhuang Zheng (lzheng17)

# Project Title

Fingerprint Recognition Door Lock

# Problem

In our Residential College dormitories, each room door requires a student IC card to unlock. However, sometimes students may forget to bring their own card with them when they are out. The current solution is to apply for a temporary card, so a fingerprint recognition door lock can be a better solution. Currently, most fingerprint recognition door locks are integrated units. To install a new one, users must remove the entire old lock, typically requiring professional assistance. But updating all the locks in the Residential College is a huge project, and may affect students’ daily life. Thus, we propose a more user-friendly solution that allows users to integrate advanced fingerprint recognition technology with their current locks, without the needs of extensive installation processes, so that students can install the device by themselves.

# Solution Overview

We aim to create a smart, compact device that can be added to existing locks, enabling fingerprint-based unlocking. So that students can install the device easily by themselves. This device will feature a fingerprint recognition module, a control unit, mechanisms for lock interaction, a mobile app for management and GPS integration, and a wireless communication module. Besides, a security module and a power supply module are needed to support other subsystems.

# Solution Components

## Capacitive Fingerprint Sensor Module

This module will feature a state-of-the-art capacitive fingerprint sensor, known for its high sensitivity and accuracy in capturing detailed fingerprint images. It is designed to efficiently transmit high-resolution fingerprint image data to the Fingerprint Recognition Subsystem. The sensor's advanced technology allows it to quickly and accurately read a fingerprint, even under varying environmental conditions. Its compact size and low power consumption make it an ideal choice for integration into the smart door lock system. The sensor will be interfaced with the STM32 development board, ensuring seamless communication and data transfer between the sensor and the Fingerprint Recognition Subsystem.

## Fingerprint Recognition Subsystem

This will be a high-precision module with algorithms capable of accurately identifying the user's unique fingerprint patterns. It will also be able to store multiple fingerprints the user registered, for shared use among the user and other authorized individuals. The code implementation will be written into STM32 develop board to output True/False signal to the downstream controller subsystem.

## Controller Subsystem

This will be a microcontroller that manages the operations of the device, including processing fingerprint data, controlling lock mechanisms, and coordinating with the mobile app and a wireless communication module designed to retrieve messages from the app. We may choose a STM32 develop board with Wi-Fi module as the platform.

## Software UI

A mobile app for fingerprint recording and remote lock control. It will allow users to manage their fingerprints, remotely control the lock, and adjust settings such as auto-lock and unlock. It will also provide notifications about lock status and usage.

## Wireless Communication Module

An ESP8266 microchip for Wi-Fi connectivity with secure protocols, and a GPS module for location tracking. The microchip will provide the device with Wi-Fi connectivity to communicate with the mobile app, receive updates, and enable remote access and control. The module will also use secure protocols to ensure data privacy and security. Based on the GPS location of the users’ mobile phone, it will allow the lock to unlock automatically when the user's phone is nearby, and lock automatically when it is too far away,

## Security Module

The security module ensures secure wireless communications and app usage, prevents unauthorized access, and verifies user identity. It uses advanced encryption for data transmission and includes mechanisms for detecting and reporting security breaches.

## Mechanical Engine

An actuator to engage/disengage the existing lock mechanism. These will be designed to be compatible with the dorm lock design and will physically engage and disengage the lock mechanism in response to input from the control unit.

## Power Supply Subsystem

This system will include a battery and other components used to power up all the subsystems above, it should be able to last for a significant period.

# Criterion for Success

- Efficient and accurate fingerprint-based unlocking.
- Remote access and control of the lock's status through the app, ensuring exclusive user access.
- Ease of installation and removal from the existing lock, with robust security.
- Lock the door from inside, when the person is left

# Distribution of Work

- Chengrui Wu: Microcontroller and Software App
- Hanggang Zhu: Software App, Fingerprint Recognition and Security Module
- Haoran Yuan: Wireless Communication and Fingerprint Recognition, Chip and sensor selection.
- Lizhuang Zheng: Mechanical Engine, Microcontroller and Power Supply Subsystem

A Micro-Tribotester to Characterize the Wear Phenomenon

Shuren Li, Boyang Shen, Sirui Wang, Ze Wang

A Micro-Tribotester to Characterize the Wear Phenomenon

Featured Project


Many research efforts have been made to understand the complex wear mechanisms used to reduce wear in sliding systems and thus reduce industrial losses. To characterize the wear process, coefficient of friction needs to be measured “not only after completion of the wear test but also during the wear test to understand the transitional wear behavior that led to the final state”.(Penkov) In order to improve the effectiveness and efficiency of these research methods, it is necessary to improve the instrument used to characterize the wear phenomenon to better measure the friction coefficient of the material. Although the instrument can be applied on all solid samples, we will use silicon wafer coated with SiO2 as our specimen targeted object.

**Solution Overview**

The objective of the experiment is to evaluate the wear phenomenon of the sample during the sliding test so as to obtain the wear information of the material. We will design planar positioning and force sensing system to get the move and force information of our objects. To collect the data of vertical load and horizontal friction, 2 force sensors are mounted on linear rails to minimize the radial force and ensure that only the axial forces are collected. Then, the coefficient of friction can be calculated by equation:


And to determine the relationship between the coefficient of friction and the state of wear, we use a microscope to monitor the state of wear at a given location in the wear track and evaluate the wear process during each sliding cycle. In this way, we can investigate the wear transition processes with respect to the sliding distance then transport our data to a computer. Finally, we will design our data processing method in the computer to successfully obtain an acceptable result in the margin error.

**Solution Components**

1. Motion Platform: This subsystem includes a linear actuator that moves the sample in reciprocating motion along X-axis, a stationary counter surface that applies constant vertical load onto the sample, and another actuator that compresses the spring and provides a vertical load to the counter sample.

2. Specimen and Counter surface: We will test the wear and friction between the specimen and the counter surface during the sliding test. A 10 × 10 mm^2 silicon (Si) wafer coated with 50 nm thick SiO2 will be used as the specimen and a stainless-steel ball with a diameter of 1 mm was used as the counter surface.

3. Sensors: This subsystem includes two force sensors that measure the vertical load and horizontal friction. The Load Sensor should assemble along with the Z-axis actuator. To measure the friction without the effect of load, we assemble the Load Sensor and Friction Sensor sensor on the Linear Rails, as the photo attached shows. Since the sensors are strain gauges and only outputs, small changes in resistance, amplifiers, and ADC are needed to collect the signal and send converted data to the computer.

4. Data Processing: This subsystem includes acquiring raw data of load and friction on the computer, applying necessary filters to reduce noise and improve accuracy, and plotting the result that reflects the relationship between the sliding cycles and coefficient of friction for our sample.


**Criterion for Success**

1. Motion platform can perform precise reciprocation. The control system can effectively control the number and speed of reciprocating motion.

2. The acquisition unit can collect data effectively and can transfer the data that can be processed to the computer.

3. On a computer, the raw data can be processed into a readable graph based on algorithms set up. By analyzing the graph, the relationship between the data and the expected results can be correctly obtained.


Penkov OV, Khadem M, Nieto A, Kim T-H, Kim D-E. Design and Construction of a Micro-Tribotester for Precise In-Situ Wear Measurements. Micromachines. 2017; 8(4):103.