tinyML Talks: Buttonless Remote Control – Reproduce on your device

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

Date

October 10, 2022

Location

Virtual

Contact us

Discussion

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

Full-stack machine learning engineer with over 8 years of experience in the field. Before joining the Neuton team in 2018, he executed various end-to-end complex machine learning projects in multiple domains: telecom, networking, retail, manufacturing, marketing, fraud detection, oil and gas, engineering, and NLP. As a head of Machine Learning & Analytics at Neuton, Danil is working on the development of an automated TinyML platform facilitating sensor and audio data processing. Danil is an active contributor to the open-source community, with over 300,000 active users of tools featured in his repository. As an inspired writer, Danil publishes articles popularizing data science and introducing new methodologies for solving engineering tasks.

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.