The truck chain processing sensor data transactions
The truck chain block and transaction explorer
A simulation tool was designed to feed the truck-sensor date into the block chain in real-time.
The smart contract on the chain handling the tracking and rating logic
Querying the smart contract on the truck chain
The truck chain reporting tool fetches the results from the chain
High-level overview: A python truck-simulator, an Ethereum-powered blockchain, and a reporting-tool frontend
A glance at the technologies involved
Bad logistics can cause life-threatening harm. In Africa, up to 80% of vaccacines go bad within the supply-chain. Many causes, including bad road conditions, extreme weather changes, and simply bad drivers can be anticipated. Global shipping companies like DHL and FedEx should be able to assess the quality of sub-contractors and accurately judge the risk of each trip.
What it does
TruckChain is a data-driven carrier quality and service risk rating agency. It is the digital Moody's of logistics. IoT data from the truck is being collected together with Fleet Board. Important events, like intrusions, off-road situations and route changes are being transfered to our own Blockchain. Thus, they become transparent and immutable. Using Blockchain Smart Contracts we determine risk ratings for carriers, trips and drivers and also enable payment authorization. This way DHL and FedEx can decide which service quality suffices for which kind of shipment. Making the decision based on data, rather than gut-feeling.
How we built it
We created the following subsystems and entities:
- Sensor-data analysis software, based on python
- Ethereum based blockchain implementation
- Transaction event sent to blockchain, resulting from continuous data analysis
- Frontend system using node.js and web3 blockchain client, displaying the trip-based carrier rating.ry.
Challenges we ran into
Explaining a blockchain project in 60 seconds Evaluate data and do work for us to create reputation system of drivers quality of delivery.
Accomplishments that we're proud of
- Actually implementing the pipeline end-to-end
- Using smart contracts to analyze the rating within the blockchain
- Building our own route simulator that turns the FleetBoard data into a live-stream
What we learned
How to connect IoT, Blockchain, and UI to evaluate deliveries quality and give the possibility for a better choice of service in future. From physical sensors data to readily apparent rating system solution.
What's next for TruckChain
- Catch up on our sleep
- Implement more parameters from sensors to give a more precise ranking of delivery quality
- Use machine-learning algorithms for anomaly detection and risk rating
- Apply verification model to bring reliability to drivers