American multinational corporation and technology company Intel has unveiled a public demonstration of a seafood case study in supply chain traceability using blockchain technology.
The Sawtooth Lake’s distributed ledger technology is a modern approach to seafood traceability. It uses IoT sensors attached to any object that is entrusted to someone else for transport, with trackable ownership, possession, and telemetry parameters including location, temperature, humidity, motion, shock and tilt.
The blockchain technology-driven solution curbs the issues with the traditional seafood industry supply chain that includes error–prone, laborious manual record keeping, improper food storage conditions, illegal and unregulated fishing practices, among others that threaten the seafood industry’s economic security.
With the blockchain traceability solution,
- The seafood is caught by a fisherman and is physically tagged with sensors enabled by IoT.
- These sensors continuously transmit data with the details of time and location to the blockchain.
- The Sawtooth Lake facilitates, including the tracks possession changes via the distributed channels.
- Finally, the buyers will be able to access a comprehensive record of the fish’s provenance.
“The Sawtooth Lake platform enables users to design custom solutions for their supply chain. Blockchain offers a unique ability for firms to share selected information with their customers. A primary benefit is sharing the provenance or traceability,” the website stated.
Along with the release, data for four transactions from October 2016 was also made public.


FxWirePro- Major Crypto levels and bias summary
Bitcoin Sheds $491M in ETF Outflows and Retreats Below $64K; Sellers Reload for $50K
Bitcoin Pulls Back Amidst Geopolitical Tensions and ETF Outflows, Technicals Signal Caution
A Korean Family Spent 34 Years Hoarding Chinese Tea. Now They're Putting It on the Blockchain.
Part II — The listing: NFTs as bottle-stamps, and a vault the family is in no rush to sell
FxWirePro- Major Crypto levels and bias summary




