Projects

Multispectral Submersion Classification of Water Soldier in Drone Imagery

Jan 2026

Development
Multispectral Submersion Classification of Water Soldier in Drone Imagery
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.
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Sam Watson Ecology

Ordered by

 Sam Watson Ecology

Computer vision–based bat monitoring solution

Nov 2025

Development
Computer vision–based bat monitoring solution
This article introduces a computer vision–based bat monitoring solution developed by Saiwa in collaboration with Sam Watson Ecology. The system analyzes images and videos captured from residential and building environments to detect bats and their nests. The goal is to deliver one of the first commercial ecological monitoring solutions that is accurate, cost-effective, and easy to deploy for environmental agencies, researchers, and industry partners.
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SAIGE

Ordered by

 SAIGE

Indigenous Scholarship Matching for SAIGE

Mar 2025Apr 2025

Delivered
Indigenous Scholarship Matching for SAIGE
Saiwa Inc. built and delivered an AI-driven scholarship matching system for SAIGE, helping Indigenous students across Canada find and apply for scholarships tailored to their identity, education, and region. The platform automates bursary collection from government databases, uses AI for matching and ranking, and supports pre-filled applications with admin validation — significantly improving accessibility, accuracy, and efficiency.
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Paramoria Agri-Science Inc

A Collaboration with

 Paramoria Agri-Science Inc

Molecular and Machine Learning-Based Monitoring of Fusarium Dry Rot in Potatoes

Jul 2025

Development
Molecular and Machine Learning-Based Monitoring of Fusarium Dry Rot in Potatoes
The project introduces a groundbreaking solution to combat Fusarium dry rot, a major issue for potato producers in Alberta, causing millions in annual losses. The solution combines two advanced technologies: eDNA monitoring to track Fusarium spore populations and AI-powered wounding detection to identify mechanical damage during harvest. With industry partnerships, the project aims to develop species-specific Fusarium detection kits, integrate real-time monitoring, and reduce storage waste. By providing predictive insights, the project seeks to improve storage yield retention and offer proactive disease management tools to producers.
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