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Manisha Agrawal, Software Applications Engineer at Texas Instruments, presents the “Machine Learning at the Edge in Smart Factories Using TI Sitara Processors” tutorial at the May 2019 Embedded Vision Summit.

Whether it’s called “Industry 4.0,” “industrial internet of things” (IIOT) or “smart factories,” a fundamental shift is underway in manufacturing: factories are becoming smarter. This is enabled by networks of connected devices forming systems that collect, monitor, exchange and analyze data. Machine learning, including deep neural network algorithms such as convolution neural networks (CNNs), are enabling smart robots and machines to autonomously complete tasks with precision, accuracy and speed.

The Texas Instruments (TI) Sitara line of processors is helping to enable vision-based deep learning inference at the edge in factory automation products. TI’s AM57x class processors with specialized neural network accelerators and integrated industrial peripherals provide the processing and connectivity needed to enable smart factory vision applications to reduce production costs, improve quality and create safer work environments. This presentation covers TI’s deep learning solution on AM57x processors for smart factories.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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