1. Chosen Problem and Proposed Solution

Problem

Students at Universidad de los Andes face significant challenges with campus parking. The limited parking spaces result in long wait times, uncertainty about availability, and stress for students trying to make it to class on time. The lack of real-time information on parking availability and the inefficient current system lead to wasted time, frustration, and potentially missed academic opportunities.

Description

SeneParking is a mobile application designed to streamline the parking experience at Universidad de los Andes. It offers real-time parking spot detection, smart access through license plate recognition, and in-app payments. The app also provides navigation assistance, spot reservation capabilities, and special spots for electric cars. By leveraging IoT sensors and user-friendly interfaces, SeneParking aims to reduce search times, minimize stress, and improve parking efficiency (initially in the Santodomingo building with the option of expanding to nearby parking lots) for students, faculty, and visitors.

2. Analytics Persona

3. PAS

PAS Diagram 1

Problem: There is a lack of real-time information about parking lot availability near Universidad de los Andes.

• Alternative: Look for sings that display availability or that communicates that the parking is full.

Solutions:

• Sensors and Cameras for computer vision: Use and communicate the implement sensors and cameras in each parking space to provide availability information. The idea is to take advantage of parking spots that already have this kind of infrastructure.
• Integration with payment/registration system: The most economical option, though less precise. Implemented on parking lots that do not have cameras nor sensors.

PAS Diagram 2

Problem: The estimated wait time in the queue is unknown.

• Alternative: Use location and traffic data to estimate the wait time.
• Alternative: Take a look at the long lines and calculate an approximate wait time in queue, based on experience.

Solutions:

• Location and traffic data: Provides real-time estimates but requires constant data access.
• User manual input: Easy to implement but relies on active user participation (like waze).
• Predictive analysis: Offers estimates based on historical data but is less accurate in real-time. The more data the users provides, the more accurate can the prediction be.

PAS Diagram 3

Problem: Inability to make advance reservations for parking.

• Alternative: Offer reservations based on class or specific activity schedules.
• Alternative: Pay for a monthly subscription.

Solutions:

• Online reservation system: Flexible and easy to use, but risks overbooking.
• Reservations based on schedules: Reduces peak demand but is less flexible. Will change each semester.
• Reservations for priority groups: Guarantees space for key users who may need it.

PAS Diagram 4

Problem: Users cannot access historical statistics on parking lot usage.

• Alternative: Talk among peers to find out which parking spots have the most usage.
• Alternative: Remember from memory past parking usage based on experiences.

Solutions:

• Historical database: Allows detailed analysis but requires robust storage.
• Weekly reports: Easy to implement but less interactive. Allows for a general overview of the occupation of the parking.
• Interactive graphs: Visually appealing and useful, though requires more complex development.

PAS Diagram 5

Problem: Lack of information on alternative parking options if no space is available.

• Alternative: Talk to peers/staff for information on close parking options.
• Alternative: Look for near by parking spots either by walking of driving.

Solutions:

• Information on alternative parking lots: Provides immediate solutions, creating a network of parking options, although quick it may be less convenient (distance).

PAS Diagram 6

Problem: Users cannot receive real-time notifications about changes in parking lot availability.

• Alternative: User has to be aware of the parking queue to know if it moves. Be aware of sings and other indicates that there is parking lot availability.

Solutions:

• Push notifications: Fast and direct but may be ignored if too frequent.
• Email alerts: Useful for infrequent app users, but not ideal for immediate notifications.

PAS Diagram 7

Problem: Difficulty in finding the exact location of an available parking space.

• Alternative: Step-by-step guidance from parking staff (if available) to the available space.
• Alternative: Provide sings showing available spaces or how to navigate the parking lot.

Solutions:

• Digital signage: Easy to use for all but relies on physical infrastructure.
• Interactive maps: Intuitive and useful, though dependent on data accuracy.
• Numerating parking lots: Easy to implement but may vary depending on the parking lot. May be easier to find the available parking lot (as it is numbered).

PAS Diagram 8

Problem: Users cannot access information on parking rates and payment methods before entering.

• Alternative: Display rates and payment methods in sings sometimes difficult to read or not updated.
• Alternative: Provide rate information at the entrance of the parking lot.

Solutions:

• Payment in the app: Convenient and fast but requires trust in mobile payments.
• Display rates and payment methods: Ensures users can consult this information for all parking lots nearby.

4. Context Canvas

High Resolution Context Canva

5. Business Questions

Type 1:

1.

What is the average response time for real-time parking spot availability updates, and does it exceed our target of 1 second?

Type 2:

2.

How many users successfully found and parked in a reserved spot within 5 minutes of arrival at the university?

3.

What percentage of users activate the in-app navigation feature when approaching the campus parking areas?

4.

On average, how long does it take for a user to complete the parking payment process through the app?

5.

What is the daily utilization rate of electric-car-excuslive spots?

Type 3:

6.

Which parking-related feature (spot reservation, real-time availability, or navigation assistance) is used most frequently by our users on a weekly basis?

7.

What percentage of users have clicked on the license plate recognition beta feature for automated entry?

8.

Is the usage frequency of parking sports in the Santodomingo building through our app exceeding the parking lot's capacity? Consequently, should we expand to nearby independent parking lots?

Type 4

9.

Based on our collected data on peak parking hours and user demographics, which local businesses near campus might be interested in partnering for targeted promotions or discounts to our users?

Type 5:

10.

How does the implementation of our real-time spot detection system impact both the app's performance metrics (such as server response time and data accuracy) and user behavior patterns (like frequency of app usage and time spent searching for parking)?

6. VD Map

High Resolution VD Map