Improve the safety and security features of connected IoT devices with the context-aware audio processing capabilities of embedded machine learning. In this webinar you will learn how to collect, train, optimize, and deploy audio-based anomaly detection algorithms to the Texas Instruments CC1352P LaunchPad.

Read more about Edge Impulse's collaboration with Texas Instruments.

45 Minute Presentation | 15 Minute Live Q&A

In this 1-hour webinar you'll:

• Learn to collect and analyze audio datasets for ML.
• Leverage the Edge Impulse EON tuner to automatically optimize machine learning models.
• Design and deploy an environmental monitoring system using the TI CC1352P LaunchPad that detects and identifies anomalous sounds.

Want to follow along during the webinar? Purchase the hardware we'll be using at the links below.

This LaunchPad speeds development on devices with integrated power amplifier and multi-band radio support for concurrent Sub-1Ghz and 2.4-GHz operation. Protocols supported include Bluetooth® Low Energy, Sub-1 GHz, Thread, Zigbee®, 802.15.4, and proprietary RF with the compatible CC13x2-CC26x2 SDK. Available variations feature different RF matching networks and power levels.

The SimpleLink™ Wi-Fi® CC3200 Audio BoosterPack enables the evaluation and development with the digital audio peripheral [I2S] present on the SimpleLink™ Wi-Fi® CC3200 device. It contains a Class-D power amplifier to drive speakers and an ultra-low power audio codec, TLV320AIC3254, supporting programmable audio processing.

David Schwarz is a User Success Engineer at Edge Impulse, helping customers build and deploy products powered by machine learning. He is a University of Texas graduate with previous experience in embedded systems design and applications engineering. He lives in Austin Texas and enjoys reading, swimming, and programming in his spare time.

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