SPARK
sPark is a personal project I built with an engineer friend who also attends SJSU. As commuters ourselves, we took it as a personal challenge to improve the parking situation on campus.
With no funding and no formal integration with the school's systems - only access to data from existing parking lot occupancy cameras - we built sPark from the ground up. The app allows students to track, predict, and plan parking in advance.
As the sole designer, my responsibility was to research and deliver a product that improves how students approach parking, reducing unnecessary search time.
MY ROLE
Product Design, Research
TOOLS USED
Figma, V0, Claude
TEAM
2 Software Engineers
P
Parking
Forecasting
Navigation
Status view, showing the occupancy status of each garage, with the option to sort or predict future occupancy.
Plan your arrival, allowing users to input their class('s) information and receive arrival suggestions based on their schedule.
Status view
Users can input a date and time, and our AI assisted prediction model will display the predicted occupancy for each garage.
Users can choose to sort garages by occupancy, distance to buildings and number of special spots.
The user selects a specific garage from the list to view its dedicated page, which includes availability, location, payment, amenities, and any other relevant details specific to that garage.
Plan your arrival
The user adds their classes one by one, inputting the class name, time, days of the week it meets, and building location. Once all classes are added, the app generates a personalized arrival plan for each day of the week.
After generating results, users receive their list with an option to adjust a safe arrival window, where results will only show below the selected number.
Users see their leave and arrive by time, sorted and calculated by their distance from their starting point to the garage, and then to their class.
LAST UPDATED APRIL 15TH