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Parking Lot Occupancy

Undergraduate Senior Project focusing on detecting vehicle occupancy for parking lots

GitHub license

Abstract

As The College of New Jersey increases its student and faculty size, there is an ever increasing need to manage its growth appropriately. One area in particular need of attention is parking on campus. Currently, many commuting facility, staff, and students attempt to find available parking spaces by driving around to different parking lots and guessing where parking spaces may be available.

The Parking Lot Availability and Traffic Prediction System provides commuters with information about the availability of free parking spaces, which will not only alleviate traffic congestion but also increase coordination for commuters. This system is made up of three components: detection nodes to detect vehicles entering and exiting parking lots, a base station that will host a wireless network to collect traffic data from each detection node, and a web server to provide current parking space availability at a glance. Each detection unit contains: sensors, wireless radio, and custom solar charging circuit for renewable outdoor operation. The base station contains a microcomputer and a wireless radio to communicate with each detection unit. All traffic data is securely stored and displayed on an Amazon web server which is accessible to TCNJ commuters. The final product allows commuters to view the status of open spaces and make The College of New Jersey a better and more coordinated campus. This system can be adapted to any environment with a gate and/or a road.

Overall Architecture

Overall Architecture

Credits

Core Team

  • Warren Seto (Computer Engineer, Class of 2018)
  • Nikita Eisenhauer (Electrical Engineer, Class of 2018)
  • Stephanie Fournier (Electrical Engineer, Class of 2018)
  • Matthew Cook (Computer Engineer, Class of 2018)
  • Dr. Larry Pearlstein (Advisor)

With help from...

  • Michael Steeil (TCNJ Engineering Laboratory Technician)
  • Grant Cignarella (Mechanical Engineer, Class of 2020)
  • Joshua Acker (Mechanical Engineer, Class of 2018)
  • Lindsey Abramson (Computer Science, Class of 2018)
  • Elisa Idrobo (Computer Science, Class of 2018)
  • Philip Franco (Electrical Engineer, Class of 2019)
  • Justin Cheng (Mechanical Engineer, Class of 2017)