Projects

Saiwa collaborated with Windward Drones to develop an AI-powered solution that automatically identifies, counts, and maps individual trees from high-resolution drone imagery. By combining advanced computer vision with aerial data collection, the system transforms thousands of images into accurate, geo-referenced forestry insights in just minutes. The solution helps forestry professionals, landowners, and environmental organizations streamline inventory management, monitor large landscapes more efficiently, and make faster, data-driven decisions with detailed visual reports and spatial analytics.

GreenTech Projects partnered with Saiwa to develop an AI-powered computer vision workflow for automated seedling tray analysis using drone imagery. The project focused on detecting and localizing seedling blocks, identifying empty cavities within propagation trays, and improving the speed and consistency of nursery monitoring operations. By combining aerial imagery with machine learning–based image analysis, the project demonstrated the potential of automated nursery assessment for large-scale propagation environments. The solution utilized RGB drone imagery collected over seedling fields and propagation areas. Saiwa developed and trained custom machine learning models capable of identifying tray structures and detecting empty cells across nursery blocks. The project was successfully completed and validated the feasibility of applying AI-based image processing to greenhouse and nursery production workflows

In 2026, Saiwa continues its collaboration with Ducks Unlimited Canada (DUC) to advance drone-based monitoring of invasive aquatic vegetation. Building on previous phases focused on segmentation accuracy and geospatial localization, this phase introduces enhanced pixel-level semantic segmentation of European Water Chestnut (EWC) to enable detailed mapping of both individual plants and dense colonies across diverse aquatic environments.

In 2026, Saiwa continues its collaboration with Ducks Unlimited Canada (DUC) to further enhance drone-based monitoring of invasive aquatic vegetation. Building on last year’s high-accuracy RGB-based Water Soldier detection pipeline, this new phase focuses specifically on determining whether each detected plant is located above or below the water surface.