Project

# Title Team Members TA Documents Sponsor
18 RFID Poker Board
 Darren Liao
KB Bolor-Erdene
Satyam Singh
 Eric Tang design_document1.pdf
final_paper1.pdf
proposal1.pdf
video
# Team Members:
- Satyam Singh (satyams2)
- Darren Liao (darrenl4)
- Khuselbayar Bolor-Erdene (kb40)

# Poker

Traditional poker tables rely on the dealer and players to track cards, bets, and pots. This process can be slow and error prone, especially in casual games where the dealer is inexperienced. Players may misread cards, deal incorrectly, or lose track of the state of the game. Live poker also lacks many of the conveniences of online poker, such as automatic hand evaluation, instant game state updates, and precise tracking of actions. Online platforms further enhance the player experience with detailed statistics, and hand histories while live games rely entirely on player knowledge.

# Solution

An RFID-enabled poker table with tagged cards helps to bridge this gap by bringing digital intelligence into the live poker experience. By embedding RFID readers in the table, the system can automatically recognize cards, display the game state in real time, and evaluate hands without error. Game state management features such as LED indicators can track dealer position, blinds, and turn order, giving players visual cues that keep the game running smoothly.

A dedicated companion app would serve as the primary user interface, providing players with immediate feedback. The app can also highlight blind positions, display whose action it is

At a high level, we will stick 13.56 MHz HF RFID sticker tags onto poker cards (and possibly chips later), place small antenna pads under the “seat” zones in front of each player, and a larger one in the middle for the community cards. We will build a main PCB with an ESP32, a single HF reader IC, and an RF MUX switch so the microcontroller unit (MCU) can scan all pads sequentially. The MCU will resolve tag UIDs into chip denominations or card identities, then send compact state updates to a small UI over Wi-Fi in near real-time.

# Solution Components

## Subsystem 1: RFID Cards and Antenna Network

Each card and chip will have a 13.56 MHz HF RFID NFC sticker (ISO 15693) attached. Antenna pads will be embedded under each player’s seat zone and a larger pad will be used for the community cards. All pads will be routed through an RF multiplexer (e.g., a 16:1 analog switch like the HMC7992) into a single HF RFID reader IC (such as PN532 or MFRC522). The microcontroller will sequentially energize each pad, cycling through them at a fast interval per pad to collect tag UIDs, filter duplicates, and reliably detect card positions in near real time.

## Subsystem 2: Central Microcontroller

The system will use an ESP32-S3 (dual-core with Wi-Fi) as the central controller. It will interface with the RFID reader via SPI or I2C and control the RF multiplexer using GPIO select lines. The microcontroller will maintain an internal mapping of card and chip UIDs to their identities (rank/suit or chip denomination) and update the game state. Once the game state is compiled, it will be serialized into JSON format and transmitted to the visualization app over HTTP for low-latency communication.

## Subsystem 3: Game Visualization App

The visualization layer will be a cross-platform application (built with Python + Flask) that receives JSON packets from the ESP32. It will display each player’s hole cards and the community cards, highlight blinds and active turns, and compute win probabilities for each player using either Monte Carlo simulation or a precomputed odds lookup. As a stretch goal, the app will also store hand histories and send LED or LCD commands back to the ESP32 to synchronize the physical table indicators with the digital state.

# Criterion For Success

- 100% accuracy in tracking the cards currently in play through 5 rounds of gameplay
- Game state is accurately updated on the app within 2-5 seconds of updating
- Board can correctly differentiate between folds and players accidentally moving their cards away from antennas

# Stretch Goals
If we have the time, we would also like to enhance the player experience by adding small LED indicators for the game state (big/small blinds, betting rounds, LCD screen showing the pot size) to help each player better understand the game without having to rely strictly on the app.

Tracking chips can be more challenging, since stacking with RFID can be difficult. However, we would love to implement this so we can build on the tech idea above and display the total pot size directly on the board along with the app.

Additionally, if desired, we could use algorithms and machine learning in the app to help players make the best decisions given the current game state.

Electronic Replacement for COVID-19 Building Monitors @ UIUC

Patrick McBrayer, Zewen Rao, Yijie Zhang

Featured Project

Team Members: Patrick McBrayer, Yijie Zhang, Zewen Rao

Problem Statement:

Students who volunteer to monitor buildings at UIUC are at increased risk of contracting COVID-19 itself, and passing it on to others before they are aware of the infection. Due to this, I propose a project that would create a technological solution to this issue using physical 2-factor authentication through the “airlock” style doorways we have at ECEB and across campus.

Solution Overview:

As we do not have access to the backend of the Safer Illinois application, or the ability to use campus buildings as a workspace for our project, we will be designing a proof of concept 2FA system for UIUC building access. Our solution would be composed of two main subsystems, one that allows initial entry into the “airlock” portion of the building using a scannable QR code, and the other that detects the number of people that entered the space, to determine whether or not the user will be granted access to the interior of the building.

Solution Components:

Subsystem #1: Initial Detection of Building Access

- QR/barcode scanner capable of reading the code presented by the user, that tells the system whether that person has been granted or denied building access. (An example of this type of sensor: (https://www.amazon.com/Barcode-Reading-Scanner-Electronic-Connector/dp/B082B8SVB2/ref=sr_1_11?dchild=1&keywords=gm65+scanner&qid=1595651995&sr=8-11)

- QR code generator using C++/Python to support the QR code scanner.

- Microcontroller to receive the information from the QR code reader and decode the information, then decide whether to unlock the door, or keep it shut. (The microcontroller would also need an internal timer, as we plan on encoding a lifespan into the QR code, therefore making them unusable after 4 days).

- LED Light to indicate to the user whether or not access was granted.

- Electronic locking mechanism to open both sets of doors.

Subsystem #2: Airlock Authentication of a Single User

- 2 aligned sensors ( one tx and other is rx) on the bottom of the door that counts the number of people crossing a certain line. (possibly considering two sets of these, so the person could not jump over, or move under the sensors. Most likely having the second set around the middle of the door frame.

- Microcontroller to decode the information provided by the door sensors, and then determine the number of people who have entered the space. Based on this information we can either grant or deny access to the interior building.

- LED Light to indicate to the user if they have been granted access.

- Possibly a speaker at this stage as well, to tell the user the reason they have not been granted access, and letting them know the

incident has been reported if they attempted to let someone into the building.

Criterion of Success:

- Our system generates valid QR codes that can be read by our scanner, and the data encoded such as lifespan of the code and building access is transmitted to the microcontroller.

- Our 2FA detection of multiple entries into the space works across a wide range of users. This includes users bound to wheelchairs, and a wide range of heights and body sizes.