IBM Secures New Blockchain Patent For Mobile Data Sharing Procedure Utilizing DLT Benefits
IBM has been one of the top leaders in getting patents for blockchain based technologies. They recently revealed that they have been awarded a patent for a mobile data sharing method that uses distributed ledger technology (DLT).
The abstract of the patent says:
“A method executed by a mobile apparatus for verifying event information to be shared is disclosed. The method includes communicating with a nearby mobile or immobile apparatus to generate a verification in response to encountering the nearby mobile or immobile apparatus. The method also includes verifying the existence of an incident event in response to arriving at a place of the incident event. The method further includes publishing a verified incident event in order to add into an incident event distributed ledger used for managing event information related to the incident event.”
The patent had been filed for in November 2017 entitled “Information Sharing Among Mobile Apparatus.” In essence, this technology can be used to verify information that has been shared between two devices. A platform has the ability to accumulate data and provide it to computing nodes nearby. The status of the verification incident will be published on a DLT. This information will be shareable through mobile devices in the network.
About the connected objects, the patent says:
“Connected objects can be sensed and/or controlled remotely across existing network infrastructure, integrating connected physical objects into computer-based systems. Connected physical objects are uniquely identifiable through their embedded computing system, allowing the connected physical objects to interoperate within the existing Internet infrastructure.”
It feels likes that every month IBM comes up with a new blockchain based patent. Earlier this month BitcoinExchangeGuide had reported about IBM’s new patent directed towards a new implementation system in order to manage data as well as typical interactions for various models of Self-Driving Vehicles (SDVs).