Inspiration

Our passion started to beat to optimising the logistics system through Fleet Boards Junction track. The task was to seek for new ways to find avoidable problems and improve current transportation services that transport goods worldwide. Collected cargo data processed with artificial intelligence gave us huge possibilities to build new kind of service to ease the transportation managers life.

What it does and how we built it

Data was collected from IoT sensors from truck. The Data was then parsed to appropriate format, cleaned and prepared for processing. Data visualisation was done in order to get insights and enable us to identify the problem and propose a solution. A machine learning algorithm was developed to predict and identify patterns to find out abnormal behaviour. Once the problem is identified, it is then pushed into the blockchain to serve as a ground truth for all stake holders in future in case of conflict.

Challenges we ran into

  1. IoT challenge: how to deal with IoT data and pre-processing data
  2. Blockchain challenge: improve transparency and traceability of logistics network and use smart contract to automate payment with bonus or penalty
  3. Machine learning challenge: How to exact the most valuable data from a big amount of IoT data and record them into blockchain
  4. Integration Challenge: integrate different technology to make most of power of it.

Accomplishments that we're proud of

  1. Connect blockchain with IoT powered by using Machine Learning
  2. Reputation system to improve carrier’s service in a long term
  3. Smart contract to motivate carrier to improve performance ( time and quality of delivery )

What we learned

As we made further investigation in the whole logistics ecosystem and what it is built of, we found out that it's really complicated and has many challenges, that should be faced by diverse professionals to solve even some of the biggest bottlenecks in the industry. The industry is full of potential cases, that could be improved with help of collection of data and by making analysis out of it.

What's next for Intelligent & Secure Logistics System

To improve our service a deeper research on the challenges on this field had to be made. By that we could get a clearer image of the present situation in the transportation ecosystem and improve the service. We would also like to interview the actual professionals who deal with the cargo, if they had some requests on what kind of information about the present situation in the cargo they are most interested in.

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