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ECE.07 – SpaceFinder

Team Members Heading link

  • Yacoub Awimrin
  • Ryan Lui
  • Amine Nbigua
  • Aizaz Uddin

Project Description Heading link

Our survey showed students spend five to twenty minutes looking for an available study space and many searches end in failure. Our project, SpaceFinder, is aimed at creating an affordable and efficient product that assists students to find suitable study spaces. Additionally, it optimize the use of space resources on university campuses. Our team determined that using machine learning and a camera system would be the most cost effective and reliable way to count active users in a space. We use a low power camera to collect the number of people and transport it to a central processing hub, minimizing the local energy consumption and product cost. Then, the data is made available to students using an app that can be accessed from their phones. The final design of the project was achieved through extensive research and testing. This includes testing the system’s ability to accurately count the number of people in a room, testing its reliability under different conditions, and ensuring that it meets the design specifications. In conclusion, the SpaceFinder project is a successful solution that satisfies the product design specifications. The system provides real-time information to students about available study spaces, which makes it easier for them to find suitable study environments.

Project Video Heading link