AI-based platform developed to manage crowding on the Payette River
Researchers have created a new machine learning-powered platform to monitor and manage overcrowding at the Payette River recreation area in Idaho.
The Institute for Outdoor Recreation and Tourism at Utah State University, along with the U.S. Forest Service, has developed a platform utilizing artificial intelligence and machine learning technologies to address the issue of heavy congestion in the Payette River recreation corridor.
In recreation areas where traditional methods struggle to balance cost and accuracy, researchers collected data using high-resolution aerial imagery and fixed cameras. Computer vision tools processed approximately half a million images to detect vehicles in parking lots and watercraft on the river.
Published in the journal Machine Learning with Applications, the study provided detailed data on recreation capacity, use intensity, demand peaks, and physical bottlenecks. These findings served as the basis for the creation of the Payette River Recreation Management Plan.
To protect privacy standards, the research team ensured data security by masking human faces and deleting raw photographs after automated counting processes. Following the project's success, the Recreation Capacity Platform, which combines aerial maps and camera data into digital dashboards, was made available to land management agencies.