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Dashcam Library is a Windows desktop application that turns large folders of dashcam recordings into a searchable trip library. I scoped,
built and tested the application end to end for a private client while working at RaftWorks.
Video library and trip organisation
Built a local indexing system that fingerprints recordings and groups clips into trips. Trip data can be rebuilt without processing every
video again, making large recording collections easier to manage.
GPS telemetry and timeline accuracy
Developed a parser for the camera’s proprietary GPS telemetry and reconciled conflicting timestamps between camera recordings and GPS data.
This connects footage to its recorded time and location.
Video playback and interface
Built the React interface and FFmpeg-based playback system, backed by a Python/FastAPI service and SQLite database.
Local storage and processing
Video files, indexing and telemetry processing stay on the user’s computer. The application does not require cloud uploads or cloud
processing.
Delivery and testing
Defined the scope and acceptance criteria across three milestones, then tested the implementation against the client’s own footage. Delivered
the first phase of the application.
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:I’m an AI & Full-Stack Developer who builds modern web applications and practical AI-powered solutions from frontend to backend. My projects include Lump Chat, a communication-focused web application; Smart Attendance, an AI-based attendance system powered by face recognition; and Local Store, a modern e-commerce platform. I work with React.js, Node.js, Python, FastAPI, MongoDB, PostgreSQL, JavaScript, OpenCV, REST APIs, and modern web technologies. My focus is on building responsive interfaces, robust backend architecture, database-driven systems, and intelligent features that solve real-world problems.
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