Smart Trichoscopy Application With a Hardware Case

SMART TRICHOSCOPY APPLICATION WITH A HARDWARE CASE

Customer

Our customer is a global healthtech company specializing in innovative hair research and diagnostics solutions. They offer patented technology that delivers precise and objective trichoscopy measurements, helping to improve the diagnosis of hair-related diseases and treatment monitoring.

Business Challenge

Our customer wanted to develop a mobile iOS and Android application that would work with a company’s proprietary computer vision algorithm and analyze patients’ hair photos taken with the help of a smartphone on its own or paired with a special hardware case.

Technology Solutions:

• A three-layer architecture based on the BLoC architecture pattern
• Extended Flutter functionality with C++ through Darf FFI
• IoT hardware case calibration using C++, OpenCV, and Dart FFI
• Modification of the camera’s native API to allow users to manually select the specific lens
• Fish-eye distortion elimination thanks to using Darf FFi and OpenCV library

Value Delivered:

• Seamless communication between IoT hardware case and mobile application
• Reduced image processing time from 2 minutes to less than 10 seconds by using Darf FFI to force Flutter to call C++ functions for optimization purposes
• Enhanced camera capabilities

Technologies: Flutter, Camera2/CameraX, Dart FFI, OpenCV and C++, SQLite 3, Android APIs, Firebase, Intercom Integration, BLoC Pattern.