Project

# Title Team Members TA Documents Sponsor
7 Non-Intrusive Smart Unlocking Mechanism for College Dormitory Rooms
 Arnav Mehta
Raghav Pramod Murthy
Yuhao Cheng
 John Li proposal1.pdf
# Non-Intrusive Smart Unlocking Mechanism for College Dormitory Rooms

Team Members:
Raghav Pramod Murthy (raghavp4)\
Arnav Mehta (arnavm7)\
Yuhao Cheng (yuhaoc7)

# Problem
Many college students living in dorms frequently face the problem of forgetting their keys. For many students, it’s their first time having to manage keys to get into their rooms, and with busy schedules, it’s very easy to forget or even misplace them. This can create a huge hassle. While some systems, like facial recognition systems, can bypass the standard key-lock system, they are not feasible to install on the college dorm doors; they need to be drilled into the interior of doors, which is costly. Other forms of authentication, such as voice recognition, are not easy to add either. This brings us to a more practical and non-intrusive solution: a lock/unlocking mechanism that does not modify the internal locking system of the door. Almost all door locks can be unlocked through the rotation of some exterior component of the door like the lock or the handle. This naturally leads us to explore a solution geared towards a flexible rotation system that can more easily integrate with existing door locks.

# Solution
We propose a portable system that turns the lock on the door (similar to how a person on the inside of the door would manually turn it to let someone in). This non-intrusive unlocking mechanism will be portable and transferable – it can be easily removed from one door and put onto another. The user attempting to access a room would scan their face on an app, and make a sound for 5 seconds (picked up by a microphone on the cellphone) to initiate voice authentication. The authentication would occur in the backend. If the face and the voice match a face and voice that has been previously registered on the app, the web app will send a signal to the microcontroller to initiate the unlocking process. The user will also be able to register other faces and voices (for example for their roommate) to allow multiple people to use this unlocking system. An important note is that this entire unlocking system will not interfere with manual unlocking with a key.



# Solution Components

## Subsystem 1: Turning Mechanism
This will be the component that physically turns the lock to unlock the door once it receives a signal.

ESP32-S3 microcontroller chip\
DRV8825 Stepper Motor Driver\
Stepper Motor: STEPPERONLINE Nema 17 Stepper Motor Bipolar 2A\
Custom PCB\
LM1117-2.5 Voltage Regulator\
12 V Battery\
Flexible Steel Cable to turn the handle

## Subsystem 2: Facial recognition + Voice Recognition app/User Interface for Authentication

Function: Authenticate the user by scanning their faces and analyzing their voice

Components:
Android app\
Flask backend hosted in GCP\
Google Cloud speech-to-text + recognition API\
DeepFace open source model to compare faces\
MongoDB instance to store face data / voice data


# Criterion For Success

Unit Test Goals:
1. Desired accuracy of the facial recognition model: 95% (on large online dataset and around 20 of our own pairs of cellphone images)
2. Desired accuracy of the speech-to-text + recognition API model: 90%
3. Processing times (from when user submits voice and face to when the signal is sent to the PCB) under 5 seconds

Functionality Goals:
Portability/Transferability of Unlocking System:
1. We will achieve this goal if we can mount our contraption onto a door in under ten minutes.

Facial Recognition + Voice Recognition:
1. We will achieve this goal if users who authenticate themselves (registering their face and voice), take a picture of themselves, and submit a voice sample can unlock the door without a key.
2. We will achieve this goal if an unauthorized user (a user who has not authenticated themselves with face and voice through the app) is unable to open the door.

Interactive Proximity Donor Wall Illumination

Sungmin Jang, Anita Jung, Zheng Liu

Interactive Proximity Donor Wall Illumination

Featured Project

Team Members:

Anita Jung (anitaj2)

Sungmin Jang (sjang27)

Zheng Liu (zliu93)

Link to the idea: https://courses.engr.illinois.edu/ece445/pace/view-topic.asp?id=27710

Problem:

The Donor Wall on the southwest side of first floor in ECEB is to celebrate and appreciate everyone who helped and donated for ECEB.

However, because of poor lighting and color contrast between the copper and the wall behind, donor names are not noticed as much as they should, especially after sunset.

Solution Overview:

Here is the image of the Donor Wall:

http://buildingcampaign.ece.illinois.edu/files/2014/10/touched-up-Donor-wall-by-kurt-bielema.jpg

We are going to design and implement a dynamic and interactive illuminating system for the Donor Wall by installing LEDs on the background. LEDs can be placed behind the names to softly illuminate each name. LEDs can also fill in the transparent gaps in the “circuit board” to allow for interaction and dynamic animation.

And our project’s system would contain 2 basic modes:

Default mode: When there is nobody near the Donor Wall, the names are softly illuminated from the back of each name block.

Moving mode: When sensors detect any stimulation such as a person walking nearby, the LEDs are controlled to animate “current” or “pulses” flowing through the “circuit board” into name boards.

Depending on the progress of our project, we have some additional modes:

Pressing mode: When someone is physically pressing on a name block, detected by pressure sensors, the LEDs are controlled to

animate scattering of outgoing light, just as if a wave or light is emitted from that name block.

Solution Components:

Sensor Subsystem:

IR sensors (PIR modules or IR LEDs with phototransistor) or ultrasonic sensors to detect presence and proximity of people in front of the Donor Wall.

Pressure sensors to detect if someone is pressing on a block.

Lighting Subsystem:

A lot of LEDs is needed to be installed on the PCBs to be our lighting subsystem. These are hidden as much as possible so that people focus on the names instead of the LEDs.

Controlling Subsystem:

The main part of the system is the controlling unit. We plan to use a microprocessor to process the signal from those sensors and send signal to LEDs. And because the system has different modes, switching between them correctly is also important for the project.

Power Subsystem:

AC (Wall outlet; 120V, 60Hz) to DC (acceptable DC voltage and current applicable for our circuit design) power adapter or possible AC-DC converter circuit

Criterion for success:

Whole system should work correctly in each mode and switch between different modes correctly. The names should be highlighted in a comfortable and aesthetically pleasing way. Our project is acceptable for senior design because it contains both hardware and software parts dealing with signal processing, power, control, and circuit design with sensors.

Project Videos