Inspiration
Smart Truck DAAM was born from the analysis of real logistics distribution data from Mollet del Vallès. We discovered that a large amount of operational time was being lost due to poor load organization, unnecessary movements inside trucks, and inefficient delivery routes.
Using clean and structured operational data from Mollet, we decided to develop an intelligent solution capable of automatically optimizing truck loading and delivery routes to improve logistics efficiency.
The project was developed with the support of Claude AI, which helped us accelerate system design, optimization logic, and interface development.
What it does
Smart Truck DAAM analyzes logistics data and:
- optimizes pallet load distribution,
- automatically assigns customers to vehicles,
- reduces operational friction during deliveries,
- improves cargo accessibility,
- minimizes unloading times,
- and optimizes delivery routes.
The platform allows users to visualize vehicles, cargo distribution, and operational metrics in real time through interactive logistics simulations.
How we built it
We built the project using:
- HTML and Python for the visual interface,
- logistics optimization models,
- pallet loading simulations,
- route and operational friction analysis,
- and real-time metrics visualization.
We worked with clean logistics data from real operations in Mollet del Vallès to model realistic distribution scenarios.
We also used Claude AI to:
- generate code structure,
- improve algorithms,
- accelerate prototyping,
- and optimize the visual user experience.
Challenges we ran into
One of the biggest challenges was transforming complex logistics data into a clear and intuitive visual representation.
We also had to balance multiple variables simultaneously:
- pallet accessibility,
- returnable items,
- barrels,
- vehicle capacity,
- and delivery schedules.
Another important challenge was building a realistic simulation using real operational data without sacrificing interface performance.
What we learned
We learned a lot about:
- logistics optimization,
- load distribution,
- data visualization,
- operational simulation,
- and intelligent transportation system design.
We also discovered how AI tools can significantly accelerate the development of complex solutions based on real-world data.
What's next for Smart Truck DAAM
We want to take Smart Truck DAAM to the next level by adding:
- real-time GPS integration,
- predictive AI for traffic and demand,
- dynamic route optimization,
- IoT integration for fleets,
- and sustainability and emissions analysis.
Built With
- claude
- excel
- flutterflow
- html
- powerpoint
- python
Log in or sign up for Devpost to join the conversation.