Daniel Kawabata
Mobile developer | Android/IOS | Aspiring AI Engineer
New to Contra
Daniel is ready for their next project!
:Lift Box is an application designed to collect and use training data from groups or gym boxes. A gateway connects to multiple smart lockbars and gathers motion and performance data during workouts.
The app retrieves this data from the gateway via WebSocket and displays it in real time in a clear and easy-to-understand way. Users can view motion data, track lifted weight, and monitor their training progress over time.
Lift Box provides a practical solution for analyzing group training data, helping users and coaches better understand performance and evolution.
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ABCCar controls a car’s pneumatic suspension system using a mobile device. It communicates via BLE (Bluetooth Low Energy), allowing the user to adjust the suspension in a practical and intuitive way.
The project involves migrating an existing app originally developed in Java to Flutter. This makes the application more modern and allows it to run on Android and iOS while keeping the same core features.
Through the app, users can send commands to change the suspension settings and receive information about the current status of the system, with great control and convenience.
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Lift is a sports telemetry app for Olympic Weightlifting, designed for high-performance and athletic athletes.
It enables data-driven workouts, historical performance tracking, and continuous improvement based on measured metrics — all combined with engaging badges and meaningful goals to keep athletes motivated.
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My Movement is a gym progress-tracking app focused on improving overall workout quality and movement efficiency. It allows users to save and review workout history, visualize real-time range-of-motion graphs, and receive movement quality notifications during training.
The app includes AI-generated workouts tailored to individual needs and integrated chat screens for guidance and engagement. An intelligent NFC system embedded in each piece of equipment enables automatic device detection, equipment availability tracking, and accurate workout association during training.
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