# Title Team Members TA Documents Sponsor
69 Face Identification Door Lock
Kaiji Lu
Zan Chen
Zekun Hu
Jacob Bryan design_review
There are situations when you are back home from supermarkets with lots of bags in your hands, or when you are holding foods that you could not free any of your hand to reach the door key in your pocket, or when you are locked out helpless. We will develop such facial recognition door lock that frees both of your hands and avoid locked-out situations.

We will design our own PCB that holds a input image sensor (OV7725), a microphone, a voltage regulator, a controller and DSP processor (ATMega328P, or seperate microcontroller and DSP chip) , USB port , and this will ouput the PWM to the motor driver which will drive the motor inside the lock.

We will use PYNQ board to run the identification model. It takes the DSP input from our PCB board and outputs the identification result back to the controller.

Thank you!

Cypress Robot Kit

Todd Nguyen, Byung Joo Park, Alvin Wu

Cypress Robot Kit

Featured Project

Cypress is looking to develop a robotic kit with the purpose of interesting the maker community in the PSOC and its potential. We will be developing a shield that will attach to a PSoC board that will interface to our motors and sensors. To make the shield, we will design our own PCB that will mount on the PSoC directly. The end product will be a remote controlled rover-like robot (through bluetooth) with sensors to achieve line following and obstacle avoidance.

The modules that we will implement:

- Motor Control: H-bridge and PWM control

- Bluetooth Control: Serial communication with PSoC BLE Module, and phone application

- Line Following System: IR sensors

- Obstacle Avoidance System: Ultrasonic sensor

Cypress wishes to use as many off-the-shelf products as possible in order to achieve a “kit-able” design for hobbyists. Building the robot will be a plug-and-play experience so that users can focus on exploring the capabilities of the PSoC.

Our robot will offer three modes which can be toggled through the app: a line following mode, an obstacle-avoiding mode, and a manual-control mode. In the manual-control mode, one will be able to control the motors with the app. In autonomous modes, the robot will be controlled based off of the input from the sensors.