Machine Learning at the Edge in Smart Factories Using TI Sitara Processors

Wednesday, May 22, 11:20 AM - 11:50 AM
Summit Track: 
Enabling Technologies
Exhibit Hall ET 2

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 session will cover TI’s deep learning solution on AM57x processors for smart factories.


Manisha Agrawal

Software Applications Engineer, Texas Instruments

Manisha Agrawal has been a Software Applications Engineer with Texas Instruments Incorporated since 2006. She has 17 years of experience in end-to-end signal chain processing of video applications including video capture, compression/de-compression, pre- and post-processing of images, 2D and 3D graphics acceleration and display. Her current area of interest is applications surrounding artificial intelligence and deep learning. Manisha received her Master’s degree in Digital Signal Processing from the Indian Institute of Technology (IIT), Kanpur and has three patents.

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