Ghost in the Machine
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine What I Built TouchGrass AI is a purpose-built micro-expedition application designed around one strict rule: The screen should be the shortest part of the experience. Developers, students, and desk workers can spend most of their day in front of screens, and even short breaks can turn into more screen…
<h2>Ghost in the Machine: TouchGrass AI</h2>
TouchGrass AI is an open-source micro-expedition application aimed at reducing screen time by turning short breaks into outdoor adventures. The app's core principle is to keep the screen the shortest part of the experience. Users select a time budget (5, 15, 30, or 60 minutes) and an outdoor environment such as a park, backyard, urban area, trail, or waterfront.
Upon selecting these parameters, the AI generates a sensory outdoor micro-quest with physical activities like observing nature, listening to birds, feeling tree bark, or exploring surroundings. Pocket Mode then dims the screen and urges the user to put their phone away and step outside. After completing the activity, users capture one field photo, which is classified locally using a MobileNetV4 ONNX model to distinguish nature/outdoor findings from indoor technology.
The application records activities and outdoor minutes in a private local SQLite journal, maintaining user privacy. The AI runs locally on the CPU, ensuring fast inference times around 11–16 milliseconds without the need for a GPU or CUDA environment. By eliminating cloud AI API calls and telemetry, TouchGrass AI preserves user privacy and offers offline capability, making it suitable for use in places with poor cellular connectivity.
The project emphasizes open innovation, utilizing lightweight open-weight ONNX models and local inference to stay independent of proprietary AI providers.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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