NanoEdge AI Studio enables rapid development of edge AI in ubiquitous low-power, low-cost embedded microcontrollers
Cartesiam, a company that creates artificial intelligence (AI) software for embedded systems, today announced at the Embedded World conference the availability of NanoEdge™ AI Studio, the first integrated development environment (IDE) that enables machine learning and inference directly on Arm Cortex-M microcontrollers (MCUs).
NanoEdge AI Studio is an intuitive software tool that allows system designers using Arm’s low-power, low-cost microcontrollers — which are embedded in billions of devices worldwide — to quickly, easily and inexpensively integrate machine learning directly into their everyday objects (industrial machines, IoT, automotive, household appliances, and more).
Until now, implementing AI in embedded devices has been a long, difficult and expensive process requiring the expertise of data scientists spending months or years of development time, and access to complex and extensive data sets that are difficult to source.
“Cartesiam’s NanoEdge AI Studio offers a completely different approach, with a cost- and time-efficient and self-learning AI,” said Marc Dupaquier, general manager and co-founder, Cartesiam. “It allows any embedded designer to develop application-specific machine learning libraries quickly and run the program inside the microcontroller right where the signal becomes data. It’s the only solution that can run both machine learning and inference on the microcontroller.”
Dupaquier said that NanoEdge AI Studio has been tested and deployed successfully at a number of European and US companies.
How NanoEdge AI Studio Works
In applications, NanoEdge AI Studio transforms passive sensors into autonomous agents capable of self-monitoring.
“Imagine an air conditioner that detects when its filter needs to be changed or an escalator activating its own preventive maintenance,” explained Dupaquier. “As far as security and privacy are concerned, learning an initial state locally reduces data exchanges over the network and prevents risk of falsification or intrusion. With our customers’ creativity and innovation, there will be no limits to the development of inventive solutions based on NanoEdge AI Studio.”
Machine Learning Development Studio Designed for Non-experts
NanoEdge AI Studio removes traditional AI barriers. It is designed for companies that either do not have expert resources in machine learning or that want to provide their data scientists with a complementary tool for embedded environments.
NanoEdge AI Studio Quick Technical Facts
- Runs autonomously on the developer’s workstation under Windows or Linux. Thus, no data is transmitted outside the customer’s environment.
- Will automatically test, optimize and calculate the best algorithmic combination among more than 500 million possible combinations, after the developer has described the targeted environment
- Provides the selected algorithm as a C library that is easily embeddable in the microcontroller
- Generates libraries that require only 4K to 16K of RAM, making them the most optimized AI algorithms in the industry
- Enables the execution of unsupervised learning, inference and prediction on the device edge, opening new classes of small, low-power, low-cost devices to AI for the first time
“LACROIX Electronics is a premier provider of industrial IoT solutions. We have used Cartesiam’s NanoEdge AI Studio to develop a very promising preventive maintenance solution on our production sites. Our goal was in particular to optimize the maintenance of reflow ovens. Thanks to this expertise, LACROIX Electronics can now offer its customers distinctive solutions based on AI smart sensors leveraging Cartesiam’s technology.”
Stephane Klajzyngier, executive managing director, LACROIX Electronics
“As part of its Maintenance for Industry 4.0 policy, Naval Group is partnering with Cartesiam to equip its teams with NanoEdge AI Studio technology, and thus meet the new challenges of naval maintenance. This innovation enables data generated by on-board equipment to be captured and analyzed directly at source.”
Alain Beltrando, head, Service Digitalization, Naval Group
“STMicroelectronics’ portfolio of sensors and STM32 microcontrollers covers a wide range of applications — industrial systems, smart home devices, and appliances as well as intelligent infrastructure. These components are able to perform different levels of machine learning techniques, such as simple tap detection, monitoring vibrations with ultra-low power consumption, and simultaneous image and sound classification. The unsupervised techniques implemented by Cartesiam are complementary to ST’s offering: They are particularly suited to applications where what our customers need to monitor is not something they can predict or have already observed before. This is what make this solution real life-proof.”
Ricardo De Sa Earp, GM, STMicroelectronics
“Innovation is at the heart of Schneider Electric’s strategy to accelerate digital transformation in an increasingly electric world. Integrating artificial intelligence, directly where a signal becomes data, allows us to ensure a better understanding of how our equipment operates throughout its lifetime, hence providing a better quality of service to our customers. Using machine learning libraries developed with Cartesiam’s NanoEdge AI Studio, we were able to anticipate behaviors that were previously difficult to detect. An AI that is simple to implement and directly integrated into the heart of our equipment is an important added value in future developments.”
Venanzio Ferraro, senior principal architect – Meium Voltage Offer, Schneider Electric