Embedded Files
Maze Robot - Closed Challenge
Maze Robot - Closed Challenge
The Maze Robot – Closed Challenge is an autonomous robot designed to navigate and solve a maze using real-time decision-making based on sensor input. Built for a timed robotics challenge, the robot used infrared and ultrasonic sensors to detect walls and openings, enabling it to follow the right-hand wall strategy to reach the maze exit. Programmed with Arduino, the robot also featured basic obstacle avoidance, path correction, and decision logic to handle dead ends and junctions effectively. The project demonstrated how embedded systems and sensor fusion could be used to develop responsive, self-guided machines in constrained environments.
Key Learnings
Key Learnings
Implemented maze-solving algorithms using real-time sensor feedback
Gained practical experience in Arduino-based robotics programming
Learned to integrate and calibrate IR and ultrasonic sensors for environmental mapping
Understood the importance of mechanical design and stability for autonomous movement
Strengthened debugging, testing, and iterative improvement skills in embedded system development
GPS Tracker for the Visually Impaired
GPS Tracker for the Visually Impaired
The GPS Tracker for the Visually Impaired is a wearable device developed during a hackathon to assist individuals with visual impairments in navigating their surroundings more safely and independently. Using a combination of GPS modules, ultrasonic sensors, and haptic feedback, the system provides real-time location awareness and obstacle detection. The device is programmed using Raspberry Pi and integrates vibration motors to notify users of obstacles in their path while simultaneously offering directional feedback for GPS-guided navigation. Designed to be compact, affordable, and user-friendly, the solution aims to bridge the accessibility gap for those with vision impairments.
Key Learnings
Key Learnings
Hands-on experience with Raspberry Pi programming and sensor integration
Real-world application of GPS modules and ultrasonic range sensors
Use of haptic feedback as a non-visual communication method
Importance of human-centered design for accessibility and usability
Team collaboration and rapid prototyping under time constraints during a hackathon setting
PatchTO
PatchTO
PatchTO is a civic engagement and infrastructure reporting tool developed during a hackathon to help Toronto residents report urban issues such as potholes, graffiti, broken signage, or other city damage. The app allows users to submit reports by taking photos, tagging the location via GPS, and categorizing the type of problem. These reports are then sent to a centralized database, which can be accessed by city maintenance teams for review and dispatch. The platform aims to bridge the gap between citizens and city services by creating a streamlined, community-powered reporting system that promotes a cleaner, safer urban environment.
Key Learnings
Key Learnings
Developed a civic-tech solution that integrates user feedback with municipal infrastructure
Learned to work with GPS-based location tagging and image uploads for issue tracking
Gained experience designing user-friendly reporting workflows for public participation
Strengthened skills in frontend-backend communication and real-time data handling
Understood the value of community-driven problem-solving and city collaboration through tech
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