Edge Devices or Always-on devices often possess limited functionality, memory, and battery life that do not meet business requirements. This forces developers to find a balance between data analysis, functionality, complexity, energy capacity, and consumption. At Neuton.AI, we have developed an innovative approach to help people create compact neural networks that can recognize complex activities with minimal memory and energy consumption. In this tutorial, you will learn how to enhance the ability of users to control consumer electronics devices with just hand gestures and how to create a similar TinyML solution of only 4Kb in total footprint by yourself.
With a universal gesture-based remote control, you can easily access and control any Bluetooth-enabled media system or presentation slides without physical contact. Neuton’s Gesture Recognition Model leveraging Silicon Labs xG24 Dev Kit for EFR32MG24 Wireless SoC can recognize eight different types of gestures with almost 99% accuracy, including swipe right, swipe left, double tap, double knock, clockwise rotation, counterclockwise rotation, idle, and an unknown class. Moreover, the Inference time for this model is less than 2.3 ms, and it has a memory footprint of only 4.2 KB in Flash and 1.4 KB RAM consumption.
This webinar will include:
– Deep dive into the solution creation process
– Different TinyML use cases’ overview
– Silicon Labs product line presentation
Schedule
Timezone: PDT
Buttonless Remote Control – Reproduce on your device
Blair NEWMAN, CTO
Neuton
Danil ZHEREBTSOV, Head of Machine Learning & Analytics
Neuton.AI
Tamas DARANYI, Product Manager
Silicon Labs
Blair NEWMAN, CTO
Neuton
With strong tech expertise and 20+ years of leadership experience, Blair Newman provides unprecedented insights into the future of AI’s development and use. As Neuton’s CTO, Blair is engaged in overseeing our business solutions as well as ensuring high-quality services are delivered to our clients.
Prior to Neuton, Blair held various leadership roles at T-Systems North America, a Division of Deutsche Telekom, being responsible for providing strategic direction and leadership in the areas of Dynamic Services (Cloud Computing), SAP Hosting, Application Operations, Managed Hosting and Infrastructure Services.
Danil ZHEREBTSOV, Head of Machine Learning & Analytics
Neuton.AI
With over 9 years of machine learning experience, Danil drives innovation at Neuton’s R&D. Before joining in 2018, he led complex projects across telecom, networking, retail, manufacturing, and more. As a Head of ML, in his current role Danil spearheads the development of an automated TinyML platform aimed at streamlining sensor data processing. Danil also plays a key role in popularizing TinyML
Tamas DARANYI, Product Manager
Silicon Labs
Tamas Daranyi holds a Master’s Degree in Electronics, and Electrical Engineering from Budapest University of Technology and Economics, has seven U.S. patents in the field, and has sixteen years of experience in the industry. Technology experience: IoT; Cloud platform development; Control and automation systems (consumer, industrial, and manufacturing); Sensor technologies; Wired & wireless communication protocols; Embedded software and systems; Industrial Acoustics; Lighting and BAS tech.
Schedule subject to change without notice.