Intelligent MEMS Sensors with On-Sensor Tiny Machine Learning

#mems #sensors #edge-computing #machine-learning
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Hybrid presentation by Dr. Mahesh Chowdhary, Fellow & Senior Director of MEMS software solutions at STMicroelectronics

Abstract

Smart sensors enable a distributed computing approach which significantly reduces the bandwidth requirement for transferring sensor data when the edge computing capabilities in microcontrollers or sensors are utilized. MEMS sensors are now commercially available with a built-in Machine Learning Core (MLC), Finite State Machine (FSM) and Intelligent Sensor Processing Unit (ISPU). These sensors can execute decision trees, neural networks, and symbolic logic directly on the MEMS sensor die. This capability allows the user to develop a variety of applications for consumer, industrial, automotive or medical devices where power consumption for applications needs to be minimized. This presentation will focus on all aspects of on-sensor machine learning that are increasingly being used to build solutions with an always-on user experience with extremely low current consumption, in order of single-digit micro-amps for MEMS sensor applications.


  Date and Time

  Location

  Hosts

  Registration


  • Date: 24 Apr 2024
  • Time: 06:30 PM to 08:00 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
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  • STMicroelectronics
  • 2755 Great America Way
  • Santa Clara, California
  • United States 95054
  • Building: 3rd Floor
  • Room Number: Geneva and Grenoble Conference Rooms
  • Contact Event Host

  • Jeronimo Segovia-Fernandez

    IEEE SFBA MEMS & Sensors Chapter, Chair

    http://sites.ieee.org/scv-mems/ 

  • Starts 29 March 2024 11:57 AM
  • Ends 24 April 2024 12:00 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
  • No Admission Charge
  • Menu: IEEE Member, Non-IEEE Member

  Speakers

Dr. Mahesh Chowdhary

Biography:


Mahesh Chowdhary, Ph.D. is a fellow and senior director of MEMS software solutions at STMicroelectronics based in Santa Clara, CA, USA. He leads effort on development of solutions and reference designs for mobile phones, consumer electronic devices, automotive and industrial applications that utilize MEMS products, computing and connectivity products. His area of expertise includes AI/ML, MEMS sensors, IoT, digital transformation, and location technologies. He has been awarded over 40 patents. Mahesh received Ph.D. in Applied Science (particle accelerators) from the College of William & Mary in Virginia.




Agenda

6:30 – 7:00 PM Registration & Networking

7:00 – 7:45 PM Invited Talk

7:45 – 8:00 PM Questions & Answers