Intelligent Recreation System
Department of Computer Science and Engineering
Project Abstract
Current trends in outdoor recreation have created unsustainable demands on our public lands and roads, and the covid-19 pandemic has only exacerbated the problem as the population looks for new ways to recreate in outdoor situations. As a result, we are rapidly degrading natural resources and experiencing untenable levels of trail use, traffic, and infrastructure strain.
Historically, the tools land managers have used to track outdoor use have included such things as counting trail users by hand, parking lot vacancy rates, how often the toilet paper needs replacing at a trailhead or how frequently pit toilets need to be pumped. But all these tools measure land use by looking backwards in time. This can result in strikingly divergent predictions of future use across various land management agencies.
The Intelligent Recreation System (IRiS) looks to change this.
By conceptualizing the capturing of dynamically produced data, such as location-based services, social media, and website metrics, IRiS provides land and transportation managers with new tools for measuring and managing recreation demand. Using machine learning and/or artificial intelligence techniques to analyze these large and diverse datasets, land managers and policymakers can then quantify recreation demand before it hits the roads and trails.
With this information, strategic interventions can then be applied to balance recreation use in real time by nudging land users to recreational areas which are less congested.