1. Brainstorming Process

Our brainstorming process followed the Design Thinking methodology, emphasizing divergent thinking to generate a wide range of ideas, particularly focusing on smart features. We considered five main problems: campus navigation, parking at Universidad de los Andes, lack of interest in university sports, food waste on campus, and accessibility issues for disabled people.

The process we followed took us to multiple places:

PUT ON THE USERS' SHOES:

We started by empathizing with the users, considering their pain points and needs for each problem. This involved reviewing interview data and situational analyses for each problem area. Most of our problems deal with life at university, which is great since we all know this experience and also know multiple people who we were able to interview.

UNDERSTANDING:

We analyzed the situations and contexts surrounding each problem, diving deep into the "What?", "How?", "Why?", and "Who?" aspects of each issue.

CAME UP WITH CRAZY IDEAS:

We encouraged wild ideas without judgment, focusing on quantity over quality initially. We used techniques like rapid ideation and round-robin brainstorming to generate as many ideas as possible, especially those incorporating smart features. Eliminating the word "But" from our vocabulary was a great practice for he development of this excercise.

Below are the ideas derived from the process, with an emphasis on smart features:

Campus Navigation:

• AR-powered navigation using smartphone cameras for real-time, intuitive directions
• AI-driven personalized route suggestions based on user preferences, class schedules, and historical data
• Crowdsourced real-time updates on campus events, obstacles, and study spot availability
• Indoor positioning system using Bluetooth beacons for precise location tracking inside buildings

Parking at Universidad de los Andes:

• AI-powered predictive parking availability based on historical data, current trends, and event schedules
• Smart license plate recognition for automatic payment, access control, and personalized parking suggestions
• IoT sensors for real-time parking spot occupancy detection and guidance
• Machine learning algorithm to optimize parking space allocation based on user patterns

University Sports Engagement:

• AI-driven personalized sports event recommendations based on user interests and friend activity
• Augmented reality features for enhanced spectator experience during live events
• Gamification elements with virtual rewards for attending events and supporting teams
• Social media integration for real-time sharing and community building around university sports

Food Waste App:

• AI-powered food surplus prediction system for campus eateries to optimize production
• Smart notification system considering user location, preferences, and dietary restrictions
• Blockchain-based reward system for consistent participation in food waste reduction
• Computer vision technology to quickly assess and categorize available surplus food items

Accessibility for Disabled People:

• AI-powered voice navigation system for visually impaired students
• Smart wheelchair routing system that considers accessibility features of buildings and pathways
• Automated real-time captioning and sign language interpretation for lectures and events
• IoT-enabled smart buildings that adapt to individual user needs (e.g., automatic door opening, adjustable desk heights)

Apart from the shown photos, evidence of this task is demonstrated through the comprehensive list of ideas generated, which was made in a Google Document in which we were all able to add text. The process applied concepts taught in class, such as empathizing with users and encouraging divergent thinking. Screenshots of our brainstorming sessions, including digital whiteboards or mind maps, would typically be included here to provide visual evidence of the process.

2. Decision Process

After generating ideas through divergent thinking, we employed a convergence strategy to evaluate and categorize them. We used the following categories to help us analyze our ideas:

THE RATIONAL CHOICE:

Parking at Universidad de los Andes: This problem is ubiquitous, feasible, and directly affects many students. The smart features proposed, such as AI-powered predictive availability and IoT sensors, seemed achievable within our technological constraints.

THE MOST LIKELY TO DELIGHT:

Food Waste App: This idea appeals to both cost-conscious students and those interested in sustainability. The smart notification system and AI-powered surplus prediction could significantly improve user experience and engagement.

THE DARLING:

University Sports Engagement: This was our team's favorite due to its potential for increasing campus spirit and social interaction. The AR features and gamification elements were particularly exciting to us.

THE LONG SHOT:

Accessibility for Disabled People: While incredibly impactful, this solution might require significant technological investment and infrastructure changes across the campus.

To choose the idea for the semester, we used a decision matrix, a technique used for convergent thinking. We evaluated each idea based on criteria such as feasibility, potential impact, alignment with course objectives, and integration of smart features.

Train of thought for choosing the Parking at Uni problem:

We recognized that as potential users, we had a deep understanding of the problem, which would aid in creating a user-centered solution. The ubiquity of the issue meant a large potential user base, increasing the impact of our solution. The problem allowed for the integration of various smart features (AI, IoT, machine learning), aligning well with course objectives and our learning goals.

Implementation seemed feasible within the semester timeframe, considering our technical skills and available resources. The potential for immediate, tangible impact on student life was high, which could lead to strong user adoption and feedback. The smart features proposed for this problem struck a balance between innovation and practicality, making it an ideal learning opportunity. The data-driven nature of the parking problem (usage patterns, peak hours, etc.) provided a rich ground for applying data analysis and machine learning concepts.

By using this structured approach to evaluate our ideas, we were able to converge on the Parking at Universidad de los Andes problem as our chosen project for the semester. This decision process clearly demonstrates the use of convergence strategies and decision-making techniques taught in class, such as idea categorization and decision matrices. It also shows how we balanced various factors including feasibility, impact, and learning potential to make our final decision.

3. Empathy Maps

Overall Description for All Empathy Maps

These empathy maps represent the key user groups at Los Andes University, revealing their unique parking-related challenges. Together, they provide essential insights for developing a user-centered ParkingApp that meets the diverse needs of students, faculty (university staff), visitors, and individuals with disabilities.

Empathy Map: Felipe (Student)

Empathy Map Student

Description: This map highlights Felipe's daily struggles as a student searching for parking at Los Andes University. It reveals his frustration and stress, emphasizing the need for a more efficient and reliable parking solution.

Empathy Map: Professor Sandra (Faculty Member)

Empathy Map Professor

Description: Professor Sandra's map focuses on her time management challenges and the inefficiencies of the current parking system. It underscores the importance of reducing stress through better parking information.

Empathy Map: Lewis (Visitor)

Empathy Map Visitor

Description: Lewis's map details the anxiety of visiting an unfamiliar campus, particularly concerning parking. It stresses the need for clear guidance and accessible parking options for visitors.

Empathy Map: Carlos (Wheelchair User)

Empathy Map Person with Disability

Description: Carlos's map addresses the challenges faced by a wheelchair user, focusing on accessible parking and campus navigation. It highlights the importance of ensuring the ParkingApp is inclusive and supportive of all users.

4. Personas

Persona 1

Persona 2

5. Solution

Suggested Solution: Los Andes ParkingApp

The Los Andes ParkingApp solves parking problems at the Los Andes University, providing a friendly and efficient solution to the needs of students, faculty, visitors, and persons with disabilities.

Key Features:

• Real-Time Spot Detection: The presence of sensors within the IoT determines real-time parking availability.
• Smart Access: Recognition/input of the license plate that would facilitate access to parking, payment, and customized suggestions on places.
• Accessibility Support: Features helping to search for and receive directions to designated accessible parking spaces, thus promoting independence for those with disabilities.
• Navigation Assistance: Guides users in finding their way around complex parking facilities using indoor positioning.
• Spot Reservation: Users can reserve a parking spot in advance, ensuring availability upon arrival.
• In-App Payments: Securely pay for parking directly through the app, simplifying the payment process.

Solved Problem: It will reduce the time spent searching for parking spaces, reduce stress, and improve access. Features such as spot reservations and in-app payments make the application even more convenient, with one able to secure a parking spot and handle all payments from the app hassle-free. This holistic approach directly responds to the pain points at the base of empathy maps, offering a practical and inclusive solution to all users of Los Andes University.