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ARTIFICIENT: MobiDataLab Hackathon Winners demonstrate how data can help mobility in Leuven
The MobiDataLab Hackathon winners, Artificient, represented a deep-tech start-up originated from RWTH Aachen University in Germany. The international & female-empowered Europe’s leading institute in automotive engineering has over 20 years of combined experience in the industry. They produced a particularly relevant solution to the Leuven Challenge with a very solid basis and technical features.
Find out all about how they did it and YOU can do it too!
ARTIFICIENT INTERVIEW
Can you tell us a bit about your project at the hackathon: what is the title, the format, the purpose of your solution?
Our project centered around the Leuven challenge, wherein our goal was to create a solution that would optimize multimodal mobility hub placements in Leuven. In response to this challenge, we designed MAIP, the Mobility Hub Planning and Integration Platform. MAIP serves as an interactive tool intended for use by municipalities like Leuven, enabling them to pinpoint the optimal sites for constructing new mobility hubs, thereby maximizing the accessibility for the broader community.
What are the benefits or potential real-world applications of your project?
The common goal for cities is to diminish the use of private vehicles as a means of reducing road congestion and minimizing carbon emissions. This objective has gained even more significance with the emergence of shared mobility services. Multimodal mobility hubs have become pivotal in facilitating smooth transitions between transportation modes and alleviating inconveniences for commuters. Nevertheless, determining the optimal hub locations poses a complex challenge.
Our solution leverages a data-driven approach, which means that when provided with similar data as input, the system can autonomously propose hub locations tailored to the unique characteristics of different cities. This innovative tool holds the potential to revolutionize urban planning by offering cities the capability to adapt and optimize mobility hub placement according to their specific needs and circumstances. In doing so, it can significantly contribute to the broader goal of reducing road congestion and carbon emissions while enhancing the overall transportation experience for residents and visitors.
What was the inspiration behind your project idea?
We took the perspective of both Leuven’s residents and the municipal authorities, envisioning how typical individuals would utilize a mobility hub and how city planners could integrate our solution into their strategies. We noticed that most of the existing solutions in related works, such as urban park space planning, predominantly rely on either global or regional optimization. Relying solely on global optimization tends to concentrate hubs in densely populated areas, making them inaccessible to suburban residents. Conversely, regional optimization can result in the construction of redundant hubs, which poses budgetary challenges for the city. Therefore, we devised a hybrid method to address the shortcomings inherent in conventional approaches.
What were the main challenges you encountered during the hackathon, and how did you overcome them?
In hackathons, the most significant hurdle invariably revolves around time limitations. It’s critical to establish the right overall solution direction, foresee potential challenges and outcomes, and organize the division of work and priorities before delving into the coding phase. In the initial stages of our project, we dedicated a substantial amount of time to tasks such as data preprocessing, preliminary research, and deliberating on a specific solution, taking into account potential obstacles that might arise. This proactive approach proved instrumental in preventing time waste due to subsequent changes or reevaluations of the chosen solution.
What tools, technologies or programming languages did you use to create your project?
Our primary tools for this project consisted of Python as the programming language and the Google Maps API.
How did your team collaborate during the hackathon? Do you have any tips for effective team collaboration?
Our approach started with dividing the team members to individually assess each challenge and the provided data, with the aim of identifying the challenge that aligns most closely with our skill sets. Following this, we engaged in brainstorming sessions to explore several general solution directions. Subsequently, we assigned one team member to conduct a more in-depth analysis of the provided data, while the rest of the team conducted preliminary research on each proposed solution. By merging the insights gained from the data analysis and the outcomes of our preliminary research, we arrived at a final solution choice and meticulously planned its particulars. Lastly, we deconstructed the entire solution into subcomponents and allocated each team member the responsibility of addressing them individually.
What do you think made your project stand out from other participants?
We saw numerous impressive ideas from other teams, including both innovative tools/apps and methodologies. What sets our project apart, in my opinion, is our ability to harmoniously integrate both of these elements. We leveraged the provided data more effectively, developed a novel optimization approach, and transformed this approach into an interactive tool, thereby achieving a well-rounded and distinctive solution.
Do you have any plans to continue developing or implementing your project after the hackathon?
Absolutely. We’ve observed that infrastructure planning and management, such as the optimization of mobility hubs, presents a widespread challenge not only in Leuven but in nearly all European cities. There exists a substantial demand for data-driven solutions and tools like the one we developed during the hackathon. Given the constraints of time, we had to make numerous assumptions and simplifications. Our intention is to persist in addressing this challenge by enhancing the algorithms, taking into account all potential use cases, and ultimately refining the solution into a practical and widely applicable tool for cities.
Are there any memorable moments or amusing anecdotes you’d like to share about your participation in the hackathon?
Hackathons offer a unique blend of challenges, not only our problem-solving abilities but also our capacity to manage time constraints effectively. While winning the Hackathon is undoubtedly a memorable moment, what truly sticks in our memory is our team’s all-nighter in the hotel lobby, coding and discussing our project amidst curious glances from passersby. We managed to wrap up system integration and final testing just moments before the submission deadline, and the overwhelming sense of relief after enduring such intense pressure was truly unforgettable.
What advice would you give to future hackathon participants who aspire to win the competition?
To begin with, I strongly recommend entering the hackathon as a team with members possessing complementary skill sets. Additionally, I found it incredibly beneficial to gain a comprehensive understanding of the provided resources, including data and tools, prior to engaging in group discussions and brainstorming sessions for developing a solution. Otherwise, you may discover that the available resources are insufficient to support the intended solution you aim to create.
Are you planning to take part in Codagon this November?
Certainly, we aim to seize the opportunity at Codagon to advance the development of our solution.
Connect with Artificient
To know more about the team and their activities, get in touch with them!
Artificient’s website: https://artificient.de
Artificient’s LinkedIn Page: https://www.linkedin.com/company/artificient-mobility-intelligence
NB: This interview was realised by MobiDataLab’s partner Hove, who also greatly organised the MobiDataLab Hackathon in Paris in September 2023.