Cloud Computing for Kansas Truck parking Detection and Information System and Verification Tool

Principal Investigator(s):

Nikos Papanikolopoulos, Professor, Computer Science and Engineering


Project summary:

There is a need to determine deployment feasibility, and operational performance of KDOT truck parking system onto a proposed Kansas state-wide cloud computing and network architecture. Through analysis and logging of system failures and reasonable remedies that can be achieved within the Truck Parking detection and notification software architecture using virtual hosting and network configurations, the UMN will provide a risk assessment for moving to this environment. Concurrently, there is a need to provide tools and capabilities to allow KDOT to rapidly, and independently, assess and verify complete detection and notification process, either for current or historical records for a site, without requiring deep expertise or system knowledge. Monitoring and system validation without such tools and capabilities with the recent deployment is feasible but all parties have discovered can be a very time consuming process. This includes camera data, reconstructions, detection & sensing output, and of course notification reports. Having such a tool would save time for KDOT and aid to expedite identification and clarification of problems, should they arise.

Project details:

  • Project number: 2020055
  • Start date: 07/2019
  • Project status: Active
  • Research area: Transportation Safety and Traffic Flow