TRANSPORTATION ADVANCEMENTS WITH IOT AND BLOCKCHAIN.
- This is the year we are seeing business networks based on block chain put into production of world.
Early adopters are using this technology to re imagine their industries ,developing a new ways of interaction that reduce friction and foster innovation,there are multitude of companies working with IBM to implement blockchain solutions to various use cases.
IBM and AOS, a Colombian company specializing in providing business solutions, are collaborating to create a solution to enhance efficiency in the logistics and transport industry throughout the country, built on IBM Blockchain and Watson IoT.
Traditionally, supply chain transactions are completed manually, creating delays and a higher risk for recording error, which can cause differences between what was recorded and what was actually loaded. By digitizing this process using blockchain and Watson IoT, the relevant information is captured directly from the sensors placed on the trucks, and entered onto the blockchain, creating a single, shared repository that all authorized participants can access and which can only be altered with consensus from all parties.
With the solution, once the truck leaves the distribution point, an automatic message is sent to the customer, informing them about the load, weight and estimated time of arrival. If part of the delivery is returned, the invoicing can be automated depending on the actual load delivered. Also, through the sensors located on the trucks, an information repository is generated using IoT and blockchain, which tracks all the exchanges, stops and transactions made by each truck and its respective load, from the distribution point to the final customer. This heightened level of transparency can help increase accountability between shippers and their customers, promoting the flow of business.
The new solution integrates Watson IoT to monitor what is happening with the trucks. The solution captures the input and output weight to define available capacity as well as which silo and which person will carry the load; and that data is also correlated to external information, such as weather, humidity, temperature and driver’s data, to estimate delivery time to customers.