Page 23 - Jan-Feb2019
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and Ranging) data along with AVL           billion on winter road maintenance,”          shared, challenged and brainstormed
(Automatic Vehicle Location) speed         Omitaomu said. “With City of Knoxville        until we found the right solution. It was
detection data to determine the amount     road data, we developed a successful          awesome.” 
of brine to use. That tablet will then     laboratory prototype, and we’re pleased
“talk” to the actual equipment attached    to collaborate with the City and with           Prior to diving into that solution, the
to the truck, which will regulate          UT in scaling up and applying this novel      students thoroughly interviewed City
the amount of brine distributed by         approach in a real-world scenario.            Public Service officials to determine the
electronic solenoid valves.                                                              greatest needs and challenges in snow
                                             “Our goal is to give cities like            prevention methods.
  In areas that the LiDAR data has         Knoxville an intelligent approach to
identified as greater risks for ice – for  managing their resources effectively.”          “It’s really ideal to be neighbors with
example, stretches of road that are shady                                                think tank entities like ORNL and UT
or where there are changes in topography     UT students from the Haslam College         because our community benefits from
– the device will increase the amount      of Business evaluated the LiDAR data,         forward-thinking projects like this
of road treatment. When snow trucks        then added AVL data to form the               one,” Weth said. “Though I expect us to
travel lower than 30 mph, the optimal      device’s software.                            benefit from this device in Knoxville’s
brine distribution speed, the device will                                                moderate winters, I can really see it
calculate and reduce the amount of brine     LiDAR surveying relies on ultraviolet,      supporting areas up north or in the
to avoid excessive treatment.              near visible, or infrared light to image      mountains, where they receive ongoing
                                           objects such as rocks via satellite. In this  snowfall.”
  Olufemi “Femi” Omitaomu of               application, for example, LiDAR was able
the Computational Sciences and             to show which City streets will be most         City Public Service staff have attached
Engineering Division at ORNL               or least susceptible to snow and ice.         this device to one of the City’s seven
approached Chad Weth, City of                                                            brine trucks. After this winter season,
Knoxville Public Service Director,           “As my teammates and I learned from         the City will be reporting back to ORNL
several years ago about the project. A     our interviews, safety is priority No. 1,”    on brine use comparing the prototype
regional neighbor to ORNL, the City of     said Selin Anitsal, a marketing student       device and the typical brine trucks.
Knoxville’s urban setting and strategic    at Haslam. “Given that requirement, we
Snow Plan, which outlines City streets     still found ways to improve efficiency by       “We’ve been really pleased with our
in levels of priority, made Knoxville an   adjusting brine flow based upon speed         snow response over recent years, but
ideal test candidate.                      and the risk factors along the roadway.       there’s always room for improvement,”
                                                                                         said Weth. “We’re grateful to our
  “Across the United States, cities          “We had an invaluable experience            partners at UT and ORNL for the
are collectively spending about $1.5       working with the City of Knoxville, Oak       chance for our snow response to prove
                                           Ridge and Kevin Homan, our system             more effective.”
                                           engineer. We succeeded because we

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