Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 22 | Smart Stick System (Triple S) |
Pranav Nair Ritvik Manda Shivam Patel |
Dongming Liu | design_document1.pdf proposal1.pdf proposal2.pdf |
|
| # Smart Stick System (Triple S) Team Members: - Ritvik Manda (rsmanda2) - Pranav Nair (pranavn7) - Shivam Patel (shivamp6) # Problem Lacrosse players and coaches currently lack real-time, detailed performance metrics to help improve gameplay. Traditional training methods rely heavily on subjective observation, which is not very consistent. No tools such as those available for other sports like baseball, golf, soccer, etc are available to monitor and improve lacrosse form and accuracy, especially with the player alone. Since lacrosse is not a well known sport, it becomes difficult for beginners and enthusiasts to start learning the mechanics of the stick and being proficient in it. # Solution This project aims to address the need for a smart, data-driven tool that can measure shot speed, accuracy, and stick form, providing players with accurate and immediate feedback to enhance their training and technique. By incorporating motion tracking, the system will enable players to adjust to their game, fostering more efficient and targeted improvement. This will allow experienced players to obtain performance data and also aid beginners in strengthening their form and tactics. As an overview, our system will include two overall subsystems: one “base” including the pcb, a microcontroller, an LCD screen, and a camera which overall exists to act as the processing unit of the system and use computer vision to analyze a player’s form. This base alone will be able to process and provide general feedback via the LCD screen or more specific feedback via an application. The second subsystem is meant to be mounted to the back end of the lacrosse stick and must be relatively small and lightweight. It will include a small microcontroller with low energy bluetooth capability as well as an accelerometer and gyroscope to transmit more detailed info about swing speed and stick angle to the base. This detailed dataset can lead to enough information to process form and more important information like how fast and what trajectory a ball would have been thrown. # Solution Components ## Subsystem 1: LaxHub (external, box unit) LaxHub is the main processing unit of this system and contains the custom PCB, microcontroller, LCD screen, and camera, as well as necessary functionality to talk to subsystem 2 via bluetooth. The LaxHub will need to be powered by a rechargeable battery. - Microcontroller: ESP 32 - LCD Screen: ST7735R SPI LCD Screen - Camera: Focus 5MP OV5647 Sensor - Rechargeable Battery: Jameco ReliaPro Lithium Ion Polymer Battery 3.7V 500mAh Rechargeable ## Subsystem 2: LaxSense (stick unit) LaxSense is a subsystem that mounts on the lacrosse stick, which will contain the microcontroller, accelerometer, and the gyroscope. These parts will work in conjunction to keep track of performance metrics such as shot speed, stick angle, and form. Because this is a standalone device, this will need to be powered by a small battery system. - Microcontroller: LOLIN D1 mini (based on ESP-8266EX) - Accelerometer + Gyroscope: MPU6050 OR WT901BLE MPU9250 - Rechargeable Battery: B0143KH9KG, 3.7V-2600mAh-9.62Wh,18650 Rechargeable Li-ion Battery Pack ## Subsystem 3: TripleS (Application) Since the LCD display in LaxHub can’t show all metrics and history, this app will manage data display and analysis. - React: Front-end framework for the application. - Kinesis Data Streams: Real-time data streaming from the Smart Lacrosse Stick. - Kinesis Data Analytics: Real-time analysis of the streamed data. - AWS Lambda: Process data from Kinesis streams. - DynamoDB: Store historical data for retrieval. - AWS Amplify: For app deployment and hosting. # Criterion For Success 1. Accuracy of Metrics: Ensure the stick unit measures shot speed and stick angle with a precision within ±5% of actual values, validated through calibration and expert comparison. 2. Real-Time Feedback: Provide performance feedback with a latency of less than 5 seconds from sensor data capture to display on the app, ensuring immediate and actionable insights. 3. Scalability: Ensure the cloud infrastructure can handle varying loads and scale automatically to accommodate increasing data and user activity without performance degradation. |
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