The future of delivery will be surely autonomous. In the meantime we need interfaces that can assist drivers on the road easily. Drivers are not able to follow machine to machine communication and read data in JSON files. And, drivers should stay in charge of crucial decisions, that happen in the truck. We need solutions that provide a bridge between machines and humans. Our idea of an interactive voice assistant enables drivers to communicate hands-free with the computer. We took inspiration from Star Trek and currently available voice interfaces.

What it does

Truck assistant supports drivers in crucial decisions. It provides an interface truck drivers can talk to. Imagine a truck driver is on the road and something happens. Our AI will give him guidance for decisions and feedback. In the scenario our truck assistant, the computer, helped the driver, a human, to solve a problem. The company manages to inform the warehouse to prepare the unload the medical goods and advance the truck in the delivery line. Despite technical problems of a broken cooling system the goods could be saved and were delivered successfully.

How we built it

In our showcase we used the sensor data of Daimler and developed a Voice skill for a failing cooling system. We analyzed the sensor data and visualized it using Javascript. On the backend side we used the SUSI Java Server and for the front-end ReactJS. The skill is developed using the JSON format and a simple markup language. For the Voice Output we used Google Voice.

Challenges we ran into

  • It was a big challenge to put our presentation into 1 minute as it would not give us sufficient time to showcase the product
  • We took some time to understand the data set
  • Possible scenarios of this data set and how the corresponded with real life situations were partly unclear, but we got input from Daimler and this helped a lot

Accomplishments that we're proud of

  • We developed a solution that took all data into account
  • We got started adding the possibility of API calls, that result in an action of SUSI

What we learned

  • Real life use cases in the logistics industry

What's next for Truck Assistant

Our team consists of 6 people from 4 different countries. We are looking forward to working on this project with Daimler. We would like to get access to internal APIs and datasets to add more skills for other use cases.

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