Application: Animal Detection & Behavior Analysis for Direction Prediction
Industry: Wildlife Protection
Deployment Location: Canada
As the vast network of highways continues to expand and traffic conditions intensify across Canada, the incidence of wildlife-vehicle collisions (WVCs) has surged, posing a significant concern. The results of these collisions go beyond immediate personal and environmental losses, also involving substantial economic impacts.
According to the recent report from the Traffic Injury Research Foundation (TIRF), we can learn this situation more clearly from the sobering statistic that between 2000 and 2020, over 550 fatalities in Canada were attributed to WVCs. Alarmingly, over half of these tragic deaths were the result of collisions with moose, and nearly one-third were associated with deer. The report highlights a critical aspect of WVCs – a third of these incidents occur when drivers swerve to avoid animals. In fact, this reactive action intended to avert direct collisions often leads to even more serious consequences, rather than collisions with other vehicles or fixed objects.
The frequent activity of wild animals crossing roads is attributed to various factors, such as migration preparations and the breeding season. The roads, unfortunately, intersect with crucial wildlife habitat routes. In light of these alarming trends, urgent and targeted interventions and strategies are essential to mitigate risks and safeguard both human lives and the diverse wildlife that shares our habitat.
Normally, we encounter numerous animal crossing signs along county roads or habitat pathways, serving as an alert for drivers to realize the potential presence of animals. However, these warning signs may lose their effectiveness over time, as drivers might grow accustomed to them due to infrequent encounters with wild animals. To address this, it becomes essential to actively engage drivers’ awareness regarding the likelihood of encountering wildlife. By doing so, drivers can better prepare for unexpected situations, remain focused, and reduce the risk of collisions with wildlife.
To make the statistic animal crossing sign more visible, it’s important to capture the upcoming wild animals and predict their routes heading to the road.
After collecting videos from the existing cameras around the highly frequent animal activity area with light and night conditions, the animal detection model trained with the YOLO algorithm and COCO dataset can be fulfilled and further improve the detecting efficiency. All dataset preparation processes can be completed in Roboflow for annotation, cleaning, segmentation, and more.
The reComputer J2022 Edge device powered by NVIDIA Jetson Xavier NX can easily handle these data inputs and deploy the model on sites. Once the system detects moose or deer showing around or analyzes the behavior of a herd of them by predicting the moving direction heading to the road, the connected small lights on the sign will blink frequently to send an early warning signal to drivers.
Seeed NVIDIA Jetson Ecosystem
Seeed is an Elite partner for edge AI in the NVIDIA Partner Network. Explore more carrier boards, full system devices, customization services, use cases, and developer tools on Seeed’s NVIDIA Jetson ecosystem page.
Join the forefront of AI innovation with us! Harness the power of cutting-edge hardware and technology to revolutionize the deployment of machine learning in the real world across industries. Be a part of our mission to provide developers and enterprises with the best ML solutions available. Check out our success case study catalog to discover more edge AI possibilities!
Discover infinite computer vision application possibilities through our vision AI resource hub!
Take the first step and send us an email at [email protected] to become a part of this exciting journey!
Download our latest Jetson product Catalog to find one option that suits you well. If you can’t find the off-the-shelf Jetson hardware solution for your needs, please check out our customization services, and submit a new product inquiry to us at [email protected] for evaluation.