Projects

Hemaa.ai, in partnership with Tarmeez, delivers an AI-powered solution for date palm plantations that enables early health monitoring, precise tree counting, and targeted weed detection using drone and satellite imagery. Leveraging advanced deep learning models, this platform enhances operational efficiency, reduces costs, and promotes sustainable agriculture through timely alerts and accurate spatial data mapping.

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.