We are looking for an experienced mobile app and AI/Computer Vision developer to build a proof-of-concept mobile application for automated wound measurement from smartphone photographs.
The application should allow a caregiver or clinician to capture or upload a wound photograph and automatically detect the wound area, calculate length, breadth, and estimated depth, and display the measurements directly on the image.
The solution should be available for both Android and iOS and must be installable and testable on real devices.
The project will be delivered in two phases. Phase 1 will focus on developing a functional proof of concept, while Phase 2 will refine the POC into a more complete and usable application with comparison and reporting capabilities.
### Technical Requirements
* Android and iOS mobile application
* AI-based wound detection and segmentation
* Automated wound boundary detection
* Length measurement
* Breadth/width measurement
* Depth estimation
* Measurement overlay on captured images
* Confidence indicator
* PDF or on-screen measurement report
* AI-generated wound medical report
* Version-to-version wound measurement comparison
* Healing trend visualization
* Camera and image upload functionality
* Real-device testing on Android and iOS
### Preferred Technical Approach
The developer should recommend a practical approach for estimating wound depth from smartphone imagery. Possible approaches include phone depth sensors such as iPhone LiDAR/TrueDepth or Android ARCore Depth API, stereo or multi-angle image capture, calibrated reference objects, photogrammetry, or another proven method.
The selected approach should provide a legitimate, testable measurement rather than a rough estimation.
AI/Computer Vision approaches such as YOLO, U-Net, segmentation models, image-quality checks, and other suitable open-source technologies may be considered based on the developer's recommendation.
### Phase 1 – Proof of Concept
*Budget:* USD $800
*Duration:* Approximately 1 week
The Phase 1 application should:
* Allow users to take or upload a wound photograph
* Automatically detect and segment the wound boundary
* Calculate length, breadth, and depth
* Display measurement lines and wound boundaries on the image
* Run end-to-end on Android and iOS
* Provide a working installable build
* Include a brief explanation of the technical approach
* Include first-round testing performed by the developer
### Phase 1 Deliverables
* Installable Android APK or Play Console internal test build
* Installable iOS TestFlight or equivalent build
* Source code
* Technical approach summary
* Libraries and AI/ML models used
* Testing summary
* Working demonstration
### Phase 2 – Full Working Solution
*Budget:* USD $1,000
*Duration:* Approximately 2 weeks
If Phase 1 is successful, Phase 2 will focus on improving and productionising the application.
The Phase 2 scope includes:
* Refinement of the Phase 1 POC
* Improved UX/UI
* Wireframes and UI designs
* Version-to-version wound measurement comparison
* Side-by-side comparison of previous and current measurements
* Healing trend view
* Detailed AI-generated medical wound report
* Updated Android and iOS builds
* Continued testing and bug fixing
* Updated source code and documentation
### Working Requirements
* Daily stand-up calls are mandatory
* Meetings will be conducted through Zoom
* Meetings may be recorded for project documentation
* Developer must test the application before client testing
* Regular written progress updates are required
* UX/UI designs must be reviewed and approved before full implementation
* Developer should be available for a fast-moving 1–2 week engagement
### Cost Requirements
The Phase 1 POC should be developed using the developer's existing environment and available tools.
Open-source or free-tier AI/ML libraries and models should be preferred.
Any unavoidable paid API, SDK, license, cloud GPU, or third-party service cost must be clearly identified before development begins.
### Proposal Requirements
Applicants should provide:
1. Relevant experience with AI-based image measurement, computer vision, photogrammetry, AR depth sensing, or medical imaging
2. Examples of relevant applications, repositories, demos, or case studies
3. Proposed approach for depth measurement
4. Confirmation of availability for daily stand-ups
5. Any unavoidable third-party costs
6. A realistic Phase 1 development plan
7. Confirmation that they understand the success-based Phase 1 milestone
