For the first time, the tinyML Foundation has launched a contest for developers worldwide, challenging them to build advanced applications with low-power machine learning inferencing and computer vision for edge devices.
Tiny machine learning (tinyML) is broadly defined as a fast-growing field of machine learning technologies including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use cases and targeting battery-operated devices.
Here's where you come in.
We're calling on developers everywhere to devise a proof of concept using machine vision on embedded systems to address an industry-grade problem. Submissions can leverage any embedded vision hardware platform and software framework. Extra points for battery-operated, ultra-low-power projects.
Models deployed on hardware like the OpenMV Cam H7, Arduino Portenta Vision Shield, Himax WE-I Plus, Arducam Pico4ML, and Raspberry Pi are ushering in a whole new era of solutions that can now accurately identify and classify what they see, across a multitude of workloads:
Select from any of these suggested categories or choose your own area of interest. Submissions will be awarded points based on their ability to address a problem within a given industry.tinyML Summit 2021 announcement
Watch Edge Impulse co-founder Zach Shelby and OpenMV co-founder Kwabena Agyeman introduce the challenge and offer some sample applications to help get you started.Executive sponsorsPlatinum sponsors
We are giving away $6,000 in prizes to the top three submissions. Judges will score your projects based on the judging criteria outlined in the rules tab.
Hackster Impact Prize
Join Hackster as we rally with the United Nations’ Sustainable Development Goals (SDGs) in order to make today's world a smarter, healthier place. The Hackster team will select five projects that best contribute to any of the SDGs. Please refer to the specific judging criteria for this prize category.
The winner will receive the following:
- a $250 gift card;
- a 12-month subscription to Patchr Premium ($180 value);
- last but not least, they will be featured in a video interview with Hackster’s one and only Alex Glow.
Please visit the Hackster Impact Prize page for more information.
Co-founder of OpenMV, a company dedicated to making machine vision on microcontrollers easy. The OpenMV Cam makes it possible for students and hobbyists to build simple robots that can track colored objects or faces. For example, with the OpenMV Cam and a Nerf Gun engineering, major college students can build a color tracking turret for a mechatronics capstone project.Zach Shelby
An entrepreneur, angel investor and technologist in the embedded space with a passion for TinyML, embedded and Internet engineering. Zach is a former Arm VP, founder and CEO of the Micro:bit Foundation and Sensinode, active in several of his portfolio companies, and is working to bring ML to any embedded device as co-founder and CEO of Edge Impulse.Evgeni Gousev
Senior Director, at Qualcomm responsible for leading HW/SYS research and development, ultra-low power edge computing platform and machine vision, tinyML foundation member and advocate
- Autonomous Driving with OpenMV and Edge Impulse
- Arm Innovation Coffee: tinyML on OpenMV with Edge Impulse
- Arm Innovation Coffee: Embedded Machine Vision with Arduino Portenta
Tutorials & Guides
- Connecting the OpenMV Cam H7 to Edge Impulse
- Connecting the Himax WE-I Plus to Edge Impulse
- Getting Started with the Himax WE-I Plus
- Connecting the Portenta and Vision Shield to Edge Impulse
- Connecting the Eta Compute ECM3532 AI Vision Board to Edge Impulse
- AI Vision and Sensor Fusion with Himax WE-I Plus
- Ultra-Low-Power Computer Vision Applications on the Portenta
- Ultra-Low-Power Computer Vision Applications with Edge Impulse and the Eta Compute AI Vision Board
The inaugural tinyML Summit in March 2019 showed very strong interest from the community with active participation of senior experts from 90 companies. It revealed that: (i) tiny machine learning capable hardware is becoming “good enough” for many commercial applications and new architectures (e.g. in-memory compute) are on the horizon; (ii) significant progress on algorithms, networks and models down to 100kB and below; and (iii) initial low power applications in the vision and audio space. There is growing momentum demonstrated by technical progress and ecosystem development.
Gain reputation points!
Earn reputation points for participating in this contest:
- Submit a project entry: 10 points
- Submit a project entry 30 days before the deadline: 50 points
- Be among the first 10 to submit a project entry: 50 points
- Your submitted project entry wins the contest: 250 points
April 15, 2021 at 8:00AM PT
August 20, 2021 at 12:00AM PT
Winners announced by
Sep 1, 2021