Projects

In partnership with Vineland Research and Innovation Centre and with funding support from the Ontario Centre of Innovation (OCI), Saiwa is developing an advanced computer vision and AI-powered platform for early stress detection in greenhouse-grown sweet peppers. This project replaces an earlier cucumber-focused initiative and targets sweet pepper crops—another economically significant greenhouse product in Ontario. By leveraging drone and robotic imagery acquisition, alongside real-time deep learning models, this initiative aims to reduce losses from disease, optimize intervention timing, and improve crop yield and quality.

Phragmites Detector is an AI-driven system that uses drone imagery and adaptive machine learning to identify and track invasive Phragmites in wetlands. Designed for conservation groups, it offers scalable, accurate, and user-friendly tools for early detection, monitoring, and ecological reporting.

In late 2024, Saiwa Co and Ducks Unlimited Canada launched a project to enhance UAV-based detection and surveillance of the invasive aquatic plant Water Soldier (Stratiotes Aloides) using advanced image processing and deep learning. The team addressed challenges from dense and submerged vegetation, environmental noise, and irregular plant shapes by reformulating the task as semantic segmentation. The project delivered a robust model achieving 95.52% pixel accuracy, enabling accurate monitoring of both isolated plants and dense colonies, supporting early intervention, efficient management, and a scalable foundation for future multispectral enhancements.

In early 2025, Saiwa and Airwyse collaborated to automate counting of pollination bags in pine orchards using autonomous drones and AI-driven image analysis. This innovative solution replaced labor-intensive manual counting, improving accuracy and efficiency in yield prediction. Tested on 44 pine trees, the system demonstrated promising results, paving the way for scalable orchard management automation.