The Port Authority of Valencia (PAV), Spain, has integrated into the TradeLens platform, a blockchain ecosystem jointly developed by IBM and shipping giant Maersk, according to an official announcement published Nov. 5.
Launched in August 2018, the TradeLens platform applies blockchain technology to global supply chains. The product aims to improve trade efficiency and security, wherein all participants of the supply chain, including shipping lines, port and terminal operators, customs authorities and other parties, can interact and access shipping data and documents.
Per the announcement, PAV has integrated into the TradeLens project as “Early Adopters,” meaning that the port will contribute to the platform’s early development. Currently there are more than 20 participants in the TradeLens ecosystem.
TradeLens has reportedly already processed 154 million “data-sending events,” such as container shipping, warehousing time, and customs documentation. The platform can reportedly cut shipping times by 40 percent.
The PAV initially announced its plans to create a “smart port” based on blockchain and big data technologies in the beginning of October. Jose Garcia De La Guia, who is responsible for implementing new technologies in the PAV suggested that blockchain could improve logistics on a global scale and help create “ports without papers” and reduce the time spent on maintenance.
Other ports have also made moves to integrate blockchain technology into their operations. Last month, the largest port in Europe, the Port of Rotterdam, partnered with major Dutch bank ABN AMRO and the IT subsidiary of Samsung to test blockchain for shipping. The members of the blockchain trial expect that the technology will help reduce shipping time and simplify financial transactions.
In September, the U.K.’s leading port operator, Associated British Ports, signed an agreement with digital logistics enabler Marine Transport International to develop blockchain for its port logistics. The company reportedly expects that blockchain implementation will reduce time spent on the manual review of scattered data.
