Below are mock ups, wireframes, and design processes.
Buildingtracer is an AI and face-recognition software that makes use of live video feed throughout the campus or organization. Cameras are installed in and outside of buildings and around popular intersections to track individual’s movement throughout their visit. Individuals are generated a unique ID for every visit based on physical traits, they may be linked to past visits using facial recognition, and who’s movement and locations are recorded to a central database. Data will be used to support the campus’ population including but not limited to its general staff, administration, and researchers. Some of my roles in this project included helping draft and identify stakeholders and goals, exploring alternate approaches, and designing wireframes for the application.
My team had to first understand those who fall under this system - both directly and indirectly. By doing so, we would be able to design a surveillance system that can fully encapsulate what our client envisions. Below is a draft of the lists we made to brain storm the possible stakeholders, goals, constrains, and assumptions in regards to the project.
Below is a PDF outlining the audience, stakeholders, goals, constraints, and assumptions for the system
This approach utilized QR codes that
would be posted in public locations for
users to scan with their mobile device
and report their location.
While it would be cheap to implement, it does not provide enough motivation for users to report and would lead to inaccurate results.
This approach would have users download an
application that had access to their mobile
device's GPS services for location tracking.
While it would be easy to implement, it does not reliably trace all people on a campus (People who do not download the application, those who do not have a mobile device with an internet connection).
The system would use an AI and face-recognition software that makes use of live video feed throughout the campus or organization. Data will be used to support the campus’ population including but not limited to its general staff, administration, and researchers.
Individuals are generated a unique ID for every visit based on physical traits, they may be linked to past visits using facial recognition, and who’s movement and locations are recorded to a central database.
Cameras are installed in and outside of buildings and around popular intersections to track individual’s movement throughout their visit.
Below are some mock ups and low to mid fidelity wireframes that we created. The first image is a mock up of the tracking software and AI working to assign unique IDs to people. The following images are heat maps to display the live population densities in the areas shown.
I learned a lot about the importance of identifying all possible stakeholders for a project. It made the design process much smoother, ensuring that we were accounting for all possible factors throughout the project. I will definitely be utilizing this skill in all future projects.
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