Detect Water Soldier RGB Drone Monitoring And Tracking

Overview

Late 2024, In a collaboration between Saiwa Co and Ducks Unlimited Canada, a project has been started that focuses on enhancing the detection and surveillance of Water Soldier through advanced image processing and deep learning techniques. For the first year, the project was planned in four phases that up to now three phases are successfully finished and delivered to the client. 

Problem Statement

Water Soldier (Stratiotes Aloides), a fast-spreading aquatic invasive species, poses significant challenges to biodiversity, waterway management, and economic activities. Native to Europe and northwest Asia, this plant has established itself in ecosystems like the Trent-Severn Waterway in Ontario, Canada. The plant grows in shallow waters, forming dense mats that overshadow native vegetation, disrupt aquatic food chains, and modify water chemistry. These changes can harm phytoplankton populations and other aquatic organisms critical to the ecosystem. Furthermore, its sharp, serrated leaves pose physical risks to swimmers and hinder recreational activities like boating and fishing. 

The economic implications are profound. For example, the United States spends over $100 million annually to manage invasive aquatic plants. Traditional management methods, such as large-scale herbicide application, have shown limited success, particularly with the recurring reappearance of Water Soldier downstream. This persistent problem highlights the need for innovative solutions that can detect and monitor infestations efficiently, allowing for early intervention and precise management strategies. Drone-based imaging combined with machine learning offers a scalable and cost-effective solution. By leveraging high-resolution imagery, drones can access difficult-to-reach areas and capture comprehensive data on Water Soldier infestations. This approach not only addresses the limitations of manual detection but also provides a pathway to proactive management that can prevent further spread to critical water systems, such as the Great Lakes.

Project Goal

The purpose of this project is to advance Ducks Unlimited Canada’s capability of UAV-based surveillance of Water Soldier through machine learning. The scope of project contains plants that are completely visible on the water surface, a significant part of the plant is emersed in RGB domain or submerged while it is visible in RGB domain due to clarity of the water.

Solution

Detecting Water Soldier in aerial imagery presents technical challenges due to the plant's interaction with its environment. Dense vegetation often overlaps with other aquatic plants, making it difficult to isolate water soldier in drone-captured images. Additionally, environmental factors such as varying water clarity, light reflections, and shadows introduce noise into the imagery. Submerged plants, which are less visible and exhibit muted spectral signatures, add another layer of complexity.

These challenges demand advanced methods that can handle variability in scale, orientation, and environmental conditions. Traditional object detection methods often fall short in such scenarios, as they are designed for standard objects with consistent visibility. Emerging deep learning models, such as YOLO and SegDecNet, have demonstrated significant promise by automating the detection process and improving accuracy. However, they require extensive computational resources, which limits their deployment on resource-constrained platforms like drones.

This constraint emphasizes the need for lightweight, real-time solutions, which is specifically optimized for such use cases. After analyzing the various model and methods we employed a customized method that handles irregularly shaped and rotated objects, such as water soldier mats in aerial imagery. Moreover, the integration of pretrained models allows for faster deployment and better generalization, reducing the reliance on extensive labeled datasets.

Outcome

By addressing these challenges through technological innovation, it becomes possible to transition from reactive to proactive aquatic ecosystem management, significantly reducing the ecological and economic impacts of Water Soldier infestations.