Tyrata, Inc., a tire sensor, data management and analytics company, has expanded its Scientific Advisory Board (SAB) with two experts in complex data handling, machine learning and data analytics. The new board members, both Duke University professors, will focus on optimizing data collection and analytics for the IntelliTread™ technology platform as Tyrata continues to transform how the tire and transportation industries sense and use tread wear data to improve tire safety, reduce costs, and optimize tire design and maintenance.
Tyrata CTO and Scientific Advisory Board leader Aaron Franklin is pleased to welcome Dr. Miroslav Pajic and Dr. Leslie Collins to the committee.
Dr. Pajic is an Electrical and Computer Engineering Assistant Professor at Duke University and has a deep understanding of data handling and management in the digital world of automobiles and other complex environments. Dr. Pajic will contribute his expertise to the tread wear data stream and handling solutions for the IntelliTread™ technology platform.
Dr. Collins is a Professor of Electrical and Computer Engineering at Duke University and is a world-renowned expert in the rapidly growing field of machine learning, where she works with large sets of data to determine technology specific, as well as big picture, outcomes.
“Our unique access to tire tread wear data positions Tyrata to lead the way in the extraction, handling, and use of this data for analytics,” said Dr. Aaron Franklin.
“Bringing industry experts, like Dr. Pajic and Dr. Collins, together on the Scientific Advisory Board ensures we are delivering the most valuable and effective solutions to the industry.”
“The IntelliTread™ solution may be the most significant advancement in tread monitoring from within the tire since the introduction of TPMS,” said Luka Lojk, VP of Sales and Marketing. “IntelliTread™ provides direct tread depth measurement, critical tire service information that can improve safety in passenger and commercial vehicles, as well as increase fleet management efficiency. Moreover, the increased need for better tire information from the emerging autonomous and electric vehicles market further motivates the need for real-time tread monitoring.”
Filed Under: AI • machine learning