RC Lap Timing Software -- 2

Single-Camera / RFID Lap Timing System for RC Racing Arena Project Overview We are building a standalone lap-timing system for an indoor RC car racing arena, using a single fixed-position input at the finish line. The system must detect each car crossing the finish line and calculate accurate lap times in real time, displaying results live on a dedicated monitor beside the track. Detection may be implemented using: RFID reader Computer vision (OpenCV / ArUco / object tracking) Hybrid approach (preferred if it improves reliability) The priority is accuracy, stability, and simplicity, not experimental or over-engineered solutions. Project Objectives Real-time lap detection with ±0.05 second accuracy Clear on-screen display suitable for public viewing Simple, reproducible setup on a Windows PC Clean, maintainable codebase suitable for future expansion Core Functional Requirements 1. Lap Detection & Timing Detect each car crossing the finish line using: RFID read and/or Camera-based trigger (line-crossing, marker detection, or similar) Timestamp crossings instantly and compute lap time Handle rapid consecutive crossings without missed reads 2. Real-Time Display Live lap times shown on a dedicated monitor Display options: Full-screen or windowed mode Immediate refresh on every lap detection 3. Timing Analytics The system must continuously compute and display: Fastest lap (best lap) per session Average lap time per driver Current lap count 4. Driver / Car Identification Each car must be uniquely identified using one method chosen by the developer, such as: RFID tags Visual markers (ArUco, number plate, color tag) IR beacon or equivalent All lap times must be correctly assigned to the corresponding car without manual intervention during the race. 5. Lap History & Export Maintain a scrollable lap history log Export session data (CSV or similar) after the race Log should include: Car ID Lap number Lap time Timestamp Platform & Technical Constraints Operating System: NEED TO DECIDE ( OPEN FOR OPTIONS) Inputs: Standard USB camera and/or USB RFID reader Display: HDMI/monitor output Languages/Frameworks: NEED TO DECIDE ( OPEN FOR OPTIONS) (Setup must be simple and well-documented) Python, C++, OpenCV, TensorFlow, or equivalent MANDATORY: Must run offline (no internet dependency) Deliverables Hardware specification List of electrical components required Preference for plug-and-play USB devices Mounting recommendations if applicable Working application Compiled executable or Clean Python environment with requirements file Source code Fully documented Logical structure No hard-coded environment dependencies Setup & Configuration Guide Camera/RFID placement Calibration steps Screen layout customization Common failure modes and fixes Accuracy Proof Short test video or RFID test run Matching timing log Demonstrated accuracy within ±0.05 seconds Milestones (Suggested) Milestone 1 – System Design (20%) Architecture overview Detection method finalized Hardware list approved Milestone 2 – Core Detection Engine (30%) Reliable lap detection Timing accuracy validated Milestone 3 – UI & Analytics (25%) Live display Best/average lap calculations Lap history logging Milestone 4 – Final Delivery & Validation (25%) Clean install Documentation Accuracy test submission Future Scope (Not in Current Budget) Multi-camera split timing Cloud leaderboard Player login and replay integration Design decisions should not block these future extensions. Ideal Freelancer Profile Experience with: Computer vision or RFID systems Sports timing, object tracking, or OCR-like problems Strong debugging and real-world hardware integration skills Able to prioritize robustness over novelty Proposal Requirements Please include: Relevant past work (vision, RFID, or timing systems) Proposed detection approach (camera, RFID, or hybrid) Estimated timeline Total cost with milestone breakdown Assumptions or constraints you foresee Evaluation Criteria Technical soundness of approach Proven experience with similar systems Clarity of documentation and communication Ability to meet accuracy and reliability targets

ID do Projeto: 40161496