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Hackathon Project: Mobile Banking Service Optimization

In May 18-19 2024, I had the incredible opportunity to participate in a hackathon at Universitat Autònoma de Barcelona. This event allowed me to collaborate with a talented team to tackle real-world challenges and innovate in meaningful ways. For more details, you can read the official news article covering the event or my LinkedIn article.


🚚 Project Overview

Our team took on a unique challenge presented by Grupo Caja de Ingenieros: to design an innovative solution for their upcoming mobile banking service truck. This mobile service is set to travel to various towns without local bank branches, providing essential banking services to underserved communities.

Our mission was to build a smart app and system to guide the mobile banking truck to its next destination while accounting for real-world conditions. This would ensure the truck could efficiently serve as many people as possible across various locations.


📍 Our Mission

The app needed to fulfill several critical goals:

  1. Optimize the Truck's Route: Ensure efficient travel between towns.
  2. Provide Flexibility for Customization: Allow staff to adjust parameters to optimize routes in real-time.

Key Routing Parameters:

  • Starting Point of the truck
  • Distances between towns
  • Traffic Conditions and estimated travel time
  • Working Hours for truck staff
  • Population Size of each town to manage waiting times and ensure everyone has access to the service

📋 Solution Outline

The challenge involved a custom version of the well-known Travelling Salesman Problem (TSP), adapted to consider weighted parameters such as population size, traffic conditions, and staff schedules. Caixa d'Enginyers provided a list of towns with relevant data, which our team used as the foundation for route optimization.

Through strategic problem-solving and algorithm design, we developed an efficient routing system that dynamically adapted to changing conditions.


🔧 Technical Approach

Our development approach was as follows:

  • Programming Language: We used Python for its versatility and rich library support.
  • Data Management: The pandas library was crucial for managing and processing data files.
  • Algorithm Design: We crafted algorithms that prioritized and adjusted routing based on real-time inputs for effective and reliable solutions.

The completed system allowed truck staff to focus on serving community members while the app managed logistical complexities.


📂 Project Resources

For more details on our implementation, you can access the documentation and source code on this Repository.


🎉 Takeaways

Participating in this hackathon was an enriching experience that improved my technical skills and deepened my understanding of real-world problem-solving. Collaborating with a team to create a solution that could positively impact communities was both challenging and rewarding.


🔖 Hashtags

#Hackathon #UAB #CaixadEnginyers #Innovation #MobileBanking #Python #TSP #ProblemSolving #TechForGood #DataScience