STMicroelectronics helps Panasonic Cycle Technology bring AI to e-assisted bikes for affordable safety boost
April 03 2024 - 3:00AM
STMicroelectronics helps Panasonic Cycle
Technology bring AIto e-assisted bikes for
affordable safety boost
- The new tire pressure monitoring system1 improves safety and
user experiences
- ST’s software ecosystem tool, STM32Cube.AI, accelerates
development of the edge AI function operating on the STM32
microcontroller
Tokyo, Japan, April 3, 2024 – STMicroelectronics (NYSE:
STM), a global semiconductor leader serving customers
across the spectrum of electronics applications, has announced that
Panasonic Cycle Technology, Co. Ltd. (Panasonic) has adopted the
STM32F3 microcontroller (MCU) and edge AI development tool,
STM32Cube.AI, for their TiMO A e-assisted bike. ST’s edge AI
solutions provide a tire pressure monitoring system (TPMS) that
leverages an advanced AI function to improve rider safety and
convenience.
Panasonic is a leading producer of e-assisted bikes in Japan and
offers a wide variety of products for various uses to the Japanese
market. Their electric assist bicycle for school commuting, TiMO A,
runs an AI application on the STM32F3 MCU to infer the tire air
pressures without using pressure sensors. Based on information from
the motor and the bicycle speed sensor, the system generates a
warning to inflate the tires if necessary. ST's edge AI development
tool, STM32Cube.AI, enabled Panasonic to implement this edge AI
function while fitting into STM32F3 embedded memory space. This new
function simplifies tire air-pressure maintenance, which enhances
rider safety and prolongs the life of tires and other cycle
components. It also helps to reduce the cost and design work, as
there is no need for additional hardware such as an air pressure
sensor.
"We develop and manufacture e-assisted bikes with the mission of
delivering environmentally friendly, safe, and comfortable
transportation, accessible to all," said Mr. Hiroyuki KAMO,
Manager, Software Development Section, Development Department of
Panasonic Cycle Technology. "ST's STM32F3 MCU provides cost
competitiveness and optimal functions and performance for
e-assisted bikes. By combining the STM32F3 MCU with STM32Cube.AI,
we were able to implement the innovative AI function without the
need to change hardware. We will continue to increase the range of
models with AI functions and strive to fulfill our mission by
leveraging ST's edge AI solutions."
"ST has been actively working on the global proliferation of
edge AI in both hardware and software, providing edge AI solutions
to a wide range of products including industrial and consumer
equipment," said Marc Dupaquier, Managing Director Artificial
Intelligence Solutions, STMicroelectronics. "This collaboration
marks a key step in our efforts, and we are delighted to have
contributed to the first implementation of this AI function in
Panasonic’s e-assisted bike. We will continue to propose AI use
cases and solutions for diverse markets, anywhere we can help to
augment our life."
ST will showcase edge AI solutions, including the STM32 MCU and
a variety of AI development tools, at the AI Expo at Tokyo Big
Sight (May 22-24, 2024). The e-assisted bike and the motor unit
(cutaway sample) from Panasonic Cycle Technology, which feature the
STM32F3 MCU and STM32Cube.AI, are also scheduled to be displayed at
this expo.
How it works
The STM32F3 MCU adopted for the TIMO A is based on the Arm®
Cortex®-M4 (with a maximum operating frequency of 72 MHz) and
features a 128KB Flash, along with various high-performance analog
and digital peripherals optimal for motor control. In addition to
the new inflation warning function, the MCU determines the electric
assistance level and controls the motor.
It leverages STM32Cube.AI to reduce the size of the neural
network (NN) model and optimize memory allocation throughout the
development of this AI function. STM32Cube.AI is ST's free edge AI
development tool that converts NN models learned by general AI
frameworks into code for the STM32 MCU and optimizes these models.
The tool optimized the NN model developed by Panasonic Cycle
Technology for the STM32F3 MCU quickly and easily, and implemented
it in the flash memory, which has limited capacity.
ST offers a comprehensive edge AI ecosystem for spreading edge
AI to devices used in a wide range of scenarios. The ecosystem
includes STM32Cube.AI and also the NanoEdge AI Studio autoML tool.
Both tools are part of the soon to be available ST Edge AI Suite.
All of them are available free of charge. For details, please visit
the following webpages:
- Edge AI development tool, STM32Cube.AI
- Automatic machine learning library generator, NanoEdge AI
Studio
- Integrated suite of development software and tools, ST Edge AI
Suite announcement
- AI use cases
About STMicroelectronicsAt ST, we are over
50,000 creators and makers of semiconductor technologies mastering
the semiconductor supply chain with state-of-the-art manufacturing
facilities. An integrated device manufacturer, we work with more
than 200,000 customers and thousands of partners to design and
build products, solutions, and ecosystems that address their
challenges and opportunities, and the need to support a more
sustainable world. Our technologies enable smarter mobility, more
efficient power and energy management, and the wide-scale
deployment of cloud-connected autonomous things. We are committed
to achieving our goal to become carbon neutral on scope 1 and 2 and
partially scope 3 by 2027. Further information can be found at
www.st.com.
For Press Information Contact:
Alexis
Breton Corporate
External CommunicationsTel:
+33.6.59.16.79.08alexis.breton@st.com
1 Function to estimate tire air pressure based on motor speed
and data from the speed sensor and display on the LCD switch a
recommendation to inflate the tires.
- T4621S -- Apr 3 2024 -- ST Edge AI in Panasonic e-assisted
bikes_FINAL FOR PUBLICATION
- T4621S -- Apr 3 2024 -- ST Edge AI in Panasonic e-assisted
bikes_IMAGE
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