Unlock the Benefits of Artificial Intelligence for IoT Devices
The convergence of AI, 5G, and IoT technologies brings a need for real-time information and responses. Network latency, data privacy, and consumer expectations around user experience and environmental impact are driving intelligence at the endpoint. Combining high-performance on-device compute with AI and ML capabilities will unlock new use cases and applications – we call this endpoint AI.
The Future of ML Shifts to the Edge
In just a few short years, ML technology has become a reality for endpoint devices. Arm, with support from AWS, Raspberry Pi, Arduino, the tinyML Foundation, and Edge Impulse, set out to gauge the current state of tinyML development, what’s worked and what remains a challenge.
The Dawn of Endpoint AI: Bringing Compute Closer to Data
Only 1 percent to 12 percent of company data is actually analyzed, according to a new report by Strategy Analytics. The ability to perform advanced localized processing closer to where data is collected results in faster and more accurate responses, allowing companies to maximize data insights.
This new report takes an in-depth look at endpoint AI and the new opportunities it enables, and explores the potential benefits and impacts of implementing endpoint AI across key application areas and use cases.
Endpoint AI Applications
As AI mainstream popularity grows, so does the range of applications and opportunities businesses seek to develop, which span the breadth of IoT segments. Endpoint AI use cases align to three distinct areas:
Vision, such as object classification; Voice, including keyword detection; and Vibration, for example sensor fusion.
Intelligent Thermal Vision
Conservation challenges in remote areas require an energy-efficient, cost-sensitive solution. Arribada’s vision-based ML technology uses Arm microcontrollers and Mbed OS to identify and monitor wildlife.
Advanced Voice Control
Sensory’s TrulyHandsfree keyword recognition software works with Cortex-M55 to unlock high-accuracy, low-power, customizable voice control for devices and applications.
Cartesiam’s industry-agnostic AI solution enables anomaly detection and signal classification on microcontrollers based on Cortex-M, to monitor vibrations and other signal types and predict system failure.
Enabling Intelligence on the Smallest Devices
Advances in AI deployments mean that even the smallest, cost-sensitive devices can be made smarter and more capable. Arm IP, software, tools, and our partner ecosystem make development quicker and easier for product manufacturers implementing DSP and ML capabilities on-device.
Designing Endpoint AI Devices
Arm Total Solutions for IoT provides a unique solutions-based approach combining the latest specialized processing capabilities with advanced software and tooling. Arm Total Solutions for IoT are ready to implement or build upon, simplifying your design process and streamlining product development. Find out more about the first Total Solutions for IoT configurations available today.
Building Software Applications
Project Centauri is one of the foundations of Total Solutions for IoT and is designed to solve common industry problems, reduce barriers to deployment, and enable scale across the Arm Cortex-M ecosystem. Explore tools, software, and initiatives that help developers move faster and innovate with confidence.
Talk with an Expert
Find out how Arm’s new processors are enhancing on-device machine learning capabilities to help drive innovation and open up new business opportunities.
Endpoint AI Resources
- Endpoint AI video series for hardware designers
- tinyML video playlist for software developers
- AI Virtual Tech Talk Series
- In the Race to Realize the IoT There’s No Need to Run Alone
- Cambridge Consultants: How We're Pushing the Endpoint AI Envelope
- Arm Technology Moves Compute Closer to Data Than Ever
- TinyML Enables Smallest Endpoint AI Devices
- AI for IoT Devices
- Extending the Performance of Arm’s ML Portfolio for Endpoint Devices