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Artificial Intelligence (AI)
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Enabling intelligence from the cloud to the edge and endpoint sustainably
Artificial Intelligence (AI) is transforming every aspect of life. Artificial Intelligence of Things (AIoT) is a transformational megatrend driven by four underlying market dynamics which include technology convergence, decentralized intelligence, a new design mindset, and an explosion of data.
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Technology Convergence
IoT, AI, 5G maturing roughly at the same time
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Decentralized Intelligence
Tremendous benefits of a distributed intelligence model
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New Design Mindset
AI disrupting system design approaches
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Data Explosion
Endpoint data creation to grow at 85% (2017-2025)*
*Source: IDC Research
Traditionally, the IoT has been built on a cloud-centric intelligence architecture. To truly scale and enable intelligence at all levels of the network, a decentralized intelligence architecture is needed. This means running cloud-independent inference engines on power-efficient or tiny computers within the edge and endpoints. A decentralized intelligence model has tremendous technical and economic benefits as shown below.
Why decentralize intelligence?
Real-Time Response
- Minimize latency by transforming data at the source
- Optimize processing for time-critical applications
Security & Data Privacy
- Minimize security concerns related to the transfer and flow of data
- On-device data handling tightly coupled to hardware root-of-trust
Network Agility
- Maximizing data gravity by operating on data at the source
- Reduced data transport improves power and cost efficiencies
IoT systems can be thought of as an interplay of one or more core technologies shown in the diagram below. AI and Machine Learning (ML) can be viewed as an enabler that bridges underlying technologies and applications. The use of AI can be classified broadly into three categories – Voice which deals with spoken voice and linguistics, Vision which deals with cameras, machine vision and robot vision and, finally, Real-Time Analytics which deals with mostly sensor data and time-series data that is captured from sensors.
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Renesas offers a comprehensive solution stack for AI/ML developers. A broad product portfolio spanning across sensing, connectivity, computing, and actuation covers all layers of the IoT. In addition, software, tools, solutions, and a partner ecosystem that has been purpose-built to accelerate your AIoT designs.
Renesas Ready Partner Network
Partner Ecosystem
RA Arm® Cortex®-M MCUs
RX 32-Bit Performance / Efficiency MCUs
RL78 Low Power 8 & 16-bit MCUs
RZ 32 & 64-bit MPUs
AI/ML Software
Real-time Analytics
Voice
Embedded Software
Tools
Hardware Portfolio
AI at the Core
AI at the Edge
AI at the Endpoint
MPU/MCU
Power
Connectivity
AMS and CMIC
Environmental Sensors
Featured Solutions
Reality AI Tools®
Generate and build TinyML/Edge AI models based on advanced signal processing.
RealityCheck™ HVAC
AI-enabled solution to detect anomalies and faults and predict operating conditions in smart HVAC systems.
RealityCheck™ Motor
Enable conditional monitoring and predictive maintenance functionality without relying on additional sensors.
Categories
play_circle_filledVideos & Training
Reality AI / e2 studio Integration Overview Video
An overview of how the integration of Renesas Reality AI Tools® and e2 studio IDE can simplify your development cycle and for AI / ML edge and endpoint applications. Visit the Reality AI software page for more details or download e2 studio to interact with the Reality AI Tools.
Video List
Events & Webinars
News & Blog Posts
| Renesas Partners with EdgeCortix to Streamline AI/ML Development | News | Oct 4, 2023 | |
| Renesas Extends Its AIoT Leadership with Integration of Reality AI Tools and e² studio IDE | News | Sep 21, 2023 | |
| Semiconductor Industry Is Pulling AI Across a Diversity of End Uses and Applications | Blog Post | Jul 24, 2023 | |
| Renesas Picks Its Battle on Edge AI | News | Jul 5, 2023 | |
| The New Convergence: IoT, AI and 5G Bring Actionable Intelligence to the Factory Floor | Blog Post | Jan 24, 2023 | |
| No Internet Connection for that Smart Device Design? Not a Problem with Easy-to-Deploy VUI Solutions | Blog Post | Aug 25, 2022 | |
| Revolution of Endpoint AI in Embedded Vision Applications | Blog Post | Jun 27, 2022 | |
| The Role of AI and Endpoint Real-time Data Analytics | Blog Post | Jun 13, 2022 | |
| Data Science and Data Integrity within AIoT | Blog Post | May 16, 2022 | |
| Learning at the Edge: Building Intelligence into the Industrial IoT Endpoint | Blog Post | May 5, 2022 | |
| Endpoint Intelligence | Blog Post | Apr 25, 2022 |
Application Resources
Real-time Analytics
| Title | Resource Type | Associated Product(s) |
|---|---|---|
| Anomaly Detection with RealityCheck AD | Software | RA, RZ |
| Automotive Safety Warning System (SWS) | Software | RCAR |
| RealityCheck™ HVAC Solutions Suite | Software | RA |
| RealityCheck™ Motor Add-on Toolbox | Software | RAxTx, RXxxT |
Vision
Voice
| Title | Resource Type | Associated Product(s) |
|---|---|---|
| Glass Break Detection from AIZip | Application Project | RA4, RA6 |
| Person Access System (PAS) from AIZip | Application Project | RA6 |
| Voice User Interface Reference Kit | Hardware | RA2, RA4, RA6 |
| Local Voice Trigger and Command Recognition from Cyberon Cspotter | Software | RA2 |
| Local Voice Trigger and Command Recognition with Noise Reduction from Cyberon Dspotter | Software | RA4, RA6 |