Performing Department
(N/A)
Non Technical Summary
Comprehensive monitoring of traffic and road conditions is difficult, time-consuming, and expensive, especially in rural areas. Road monitoring faces significant challenges as the traditional Environmental Sensor Stations (ESS) and Road Weather Information Systems (RWIS), require power and communications infrastructure, high-bandwidth connection to transmit information, and substantial and scalable computing power to process data. One challenge traditional sensing technologies, such as video, radar, and lasers, experience is the availability of costly power and communications infrastructure. The effort and cost of running power and internet to allow for coverage in rural areas is simply not feasible for a large percentage of communities. Due to the unattainable cost of software required to process data once it is received, many organizations rely on the error-prone manual monitoring of data and video feeds, resulting in substantial labor hours, a distraction from higher-priority tasks, and often ineffective identification of issues. The combination of infrastructure-dependent systems, time-consuming installation and maintenance, and burdensome monitoring have prevented the adoption of large-scale road and traffic monitoring systems.Barn Owl has demonstratedthe possiblityof solving this problem for rural municipalities in our partnership with St. Louis County, MN. St. Louis County received the National Build a Better Mousetrap "Smart Transformation Award" for its remote installation of Barn Owl cameras. They agree the addition of environmental sensors to an edge-compute camera would be a force multiplier in sovling the problem of monitoring remote roads especially in adverse weather conditions. Barn Owl will continue to work with St. Louis County as a research partner on this effort while expanding our research to a broad target audience of rural cities, counties, public works teams, and road maintainers. This will ensure we identify a solution that is affordable, scalable, and creates safer and more efficent road monitoring systems.
Animal Health Component
50%
Research Effort Categories
Basic
10%
Applied
50%
Developmental
40%
Goals / Objectives
The major goal of this project is toidentify, develop, andintegrate affordable, in situ traffic and environmental sensors with edge computing devices to enable real-time data processing allowing for immediate notification and decision-making. This project will develop an integrated platform that combines cellular-connected cameras with edge compute capability for image and environmental sensor processing. Custom machine learning models will allow for efficient transmission of only relevant information saving end-users time and money. If this goal is achieved, local governments - especially those in rural environemnts - will benefit from a scalable solution that will allow them to increase safefy on rural roads and improve efficiency of road maintainers.Objective One: Which environmental sensors yield the highest impact in increasing safety and efficiency?Information sought in this objective would include:Environmental sensor solutions in use and those that would be considered optimalDegree of scientific accuracy required for inclusionCurrent coverage of road management systems versus total coverage goalsObjective Two: What will be required to integrate the various sensors into the EdgeCam platform?Identify system design requirementsDocument power and connectivity needs for each sensorUnderstand mounting and security requirementsObjective Three: What machine learning models and heuristics will prove most beneficial and create the highest levels of efficiency for the end users?Understand what existing data is being captured and what should be prioritized in Phase II: including but not limited to vehicle types, speed, crash/collision, roadway conditions (dry, wet, snow), environmental conditions (fog, smoke, etc.), obstacles such as animalsIdentify what models will be required to build intelligence on edge that will most effectively decipher which data should be transmitted and to whomDevelop a plan for building or sourcing code/models for edge analysisObjective Four: Where and in what conditions can we achieve the most comprehensive field testing?Current parties of interest include:Colorado Department of Transportation (letter of support included)St. Louis County, MN (letter of support included)Objective Five: What is the full commercial potential of this project and how will commercialization be accomplished?Throughout the course of Phase I, Barn Owl will identify the size of the commercial opportunity of this project and how to best bring it to marketIdentify market opportunityDefine preliminary go to market strategy
Project Methods
The project will be conducted using general scientific methods including:Surveys:Barn Owl will survey the target audience to quantify the size of the problem and value of the proposed solution.Surveys will be used to gather broad responses to data requirements by rural road maintainers. This will be an indicator of environmental sensors that should be considered and AI and machine learning opportunites as wellThe surveys combined with secondary research will allow us to quantify environmental impact of the proposed solution.Interviews:Barn Owl will conduct interviews with a subsection of the target audience to get more granular details on which data would be most valuable to decision makers. These data requirementswill provide a more informed approach to sensor identification.For example, if detectingthe presence of freezing ice on roads is a high value outcome for the customer, parameters for detection will be quantified and sensors will be matched up where the sensor's operational parameters can satisfy meeting the outcome of the customersBarn Owl will also interview subject matter experts and vendors to determine opportunities, costs, and challenges of specific sensor integrationsPrimary ResearchBarn Owl will conduct site visits with research partners to determine product requirements including power, connectivity, and weatherizationBarn Owl will use this research to quantify the size of the problem facing rural communities and resulting commerciail opportunity.If the proposed solution can create value that far exceeds the cost, the next step will be prototyping and testing.