User Research
Analyzed forestry workflows to identify operational bottlenecks and user needs.


Field teams relied heavily on manual calculations and physical measurements, making the process slow, repetitive, and resource-intensive.
Human involvement in counting logs and measuring diameters often resulted in inconsistencies and inaccurate volume estimations.
Lighting variations, irregular log shapes, and environmental factors made accurate measurement difficult in real-world scenarios.
Measurement records were often scattered across different formats, making inventory tracking and reporting inefficient.



Analyzed forestry workflows to identify operational bottlenecks and user needs.
Mapped measurement journeys to simplify complex field data collection.
Applied computer vision algorithms for automated log detection and measurement.
Built cross-platform experiences, ensuring consistency across Android and iOS.
Enabled uninterrupted operations through local storage and synchronization features.
Refined measurement accuracy through user feedback and testing cycles.


A mobile application that uses computer vision to automatically detect, count, and measure timber logs from captured images, cutting manual effort significantly.
Instant timber volume calculation based on detected log dimensions, enabling faster and more consistent inventory assessments.
Users can capture, store, and manage measurements in remote areas without internet connectivity, keeping field operations uninterrupted.
Each measurement can be linked to location data, letting users track timber inventories across multiple sites and regions.
Structured measurement records and reporting tools that support accurate documentation and operational transparency.



faster measurement process
measurement consistency achieved
logs processed digitally
improved field productivity

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