OEMs building new embedded systems—or upgrading existing applications—are eager to learn how to capture and monetize data for deployment across industrial systems, wearables, medical devices, and other markets. Do you have the right software and hardware for understanding and managing data on small device computing environments for the era of IoT and AI?
In this webinar we will introduce you to STM32 devices data processing and management ITTIA DB software that power data-driven applications. You will rapidly learn how to collect, analyze, and store real-time data streams with ITTIA DB and STM32 devices.
With a live demonstration, attendees will learn about:
- Modernize existing STM32 devices for data driven applications,
- The most important integration challenges for managing data on STM32 devices,
- Options for getting ahead with STM32 data strategy,
- Building embedded applications for the IoT and AI era with ITTIA DB and STM32,
- Serious cost reduction elements for managing data-driven STM32 applications.
Meet the Experts
Founder and President, ITTIA
Edge Data Computing
Worldwide
Speaker bio:
Sasan Montaseri holds a BS Degree in Electrical Engineering from the University of Kansas with a Minor in Mathematics. He was a member of PI Mu Epsilon, National Honor Society of Mathematics. He has over 20 years of experience with the embedded industry and edge data computing. That includes microcontrollers, microprocessors and electronic control unit. His interest and focus relates to real-time data management. Under his leadership, ITTIA has grown from its inception to offer data solution to prestigious multinational customers throughout North America, Europe, and Asia.
Applications Director, STMicroelectronics
Microcontrollers, Microprocessors, and Wireless Products
Americas
Speaker bio:
Sean Newton has over 20 years of experience designing and developing various embedded systems and computer sub-systems. Presently with STMicroelectronics, he supports the STM32 family of ARM® Cortex®-M based microcontrollers. ST's current portfolio contains more than 800 microcontrollers, from robust, low-cost 8-bit MCUs up to 32-bit ARM-based Cortex®-M0 and M0+, Cortex®-M3, Cortex®-M4, Cortex®-M7 Flash microcontrollers as well as ultra-low power solutions. He holds a B.S. in Electrical Engineering and a B.S. in Computer Science from the University of Nevada, Reno.
