AI-powered geological survey mobile platform with offline reporting, image uploads, and intelligent field summaries.
GeoInsight is a cross-platform mobile application designed for geological field operations and remote survey workflows. The platform enables field engineers to capture site data, upload survey images, record sensor readings, and generate AI-assisted geological summaries directly from mobile devices.
The application supports offline-first workflows through local storage and provides a streamlined interface for collecting and reviewing geological reports in real time.
- Mobile-first geological survey workflow
- AI-assisted geological report summaries
- Offline caching and local report persistence
- Survey image upload and storage
- Sensor reading and field-note collection
- Structured mobile UI for field operations
Field Engineer Input
↓
Survey Form + Image Upload
↓
Local Storage (Offline Cache)
↓
AI Summary Generation
↓
Saved Geological Reports
Field engineers can record:
- site name
- location
- geological notes
- sensor readings
Users can upload geological survey images directly from mobile devices using Expo Image Picker.
The platform generates intelligent geological summaries based on:
- sensor values
- field notes
- detected risk levels
It also recommends follow-up actions for elevated geological activity.
Survey reports are cached locally using AsyncStorage, enabling field usage in remote environments with limited connectivity.
Submitted surveys are displayed as structured report cards with:
- metadata
- AI-generated summaries
- saved field information
- React Native
- Expo
- TypeScript
- AsyncStorage
- Expo Image Picker
- AI-assisted summarization logic
geoinsight/
├── app/
│ └── (tabs)/
│ └── index.tsx
├── assets/
├── package.json
└── README.md
npm startOR
npx expo start- Enter geological survey details
- Upload site image
- Input sensor readings
- View AI-generated summary preview
- Save report locally for offline access
Geological Survey Summary
Site: North Ridge
Location: Arizona Basin
Analysis:
- Sensor reading: 82
- Estimated risk level: High
Recommendation:
Sensor readings indicate elevated geological activity. Further inspection is recommended.
- Building cross-platform mobile workflows with React Native
- Designing offline-first mobile systems
- Managing image upload and local persistence
- Structuring AI-assisted field reporting workflows
- Developing modular mobile interfaces for operational use cases
- GPS integration for automatic location capture
- Cloud synchronization and backend APIs
- Real AI/ML geological classification models
- Team collaboration and report sharing
- Analytics dashboard for survey trends
Ancy Patel