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Real-Time Analytics on MCUs & MPUs

Real-Time Analytics & Non-Visual Sensing

Edge AI and TinyML have paved the way for enterprises to build smart product features that use machine learning running on highly constrained edge nodes.

Reality AI is an Edge AI software development environment that combines advanced signal processing, machine learning, and anomaly detection on every MCU/MPU Renesas core. The software is underpinned by the proprietary Reality AI ML algorithm that delivers accurate and fully explainable results supporting diverse applications. These include equipment monitoring, predictive maintenance, and sensing user behavior as well as the surrounding environment – enabling these features to be added to products with minimal impact on the BoM.

Reality AI software running on Renesas processors will help you deliver endpoint intelligence in your product offering and support your solutions across all markets.

Try Reality AI Explorer to experience firsthand how Reality AI Tools can help you develop AI and TinyML solutions in industrial, automotive, and commercial applications.

Technical Advantages

Fully Integrated Toolchain

The Reality AI software comes with integration to Renesas e2studio, plus support for all Renesas cores and MCU dev boards. Integration with Renesas Motor Control kits is available as an add-on option.

Small Footprint for Speed & Accuracy

Unlike approaches that use quantization, compression, pruning or other machine learning techniques that make models small but erode accuracy, Reality AI combines advanced signal processing methods with machine learning that deliver full accuracy in a tiny footprint without compromises.

Transparency with Model Explainability

No engineer will deploy a solution they don't understand, so Reality AI offers transparency into model function based on time and frequency, as well as full source code available in C or MATLAB. You can always explain to colleagues and stakeholders why models perform as they do, and why they should be trusted.

Cost Optimization

Instrumentation and data collection are >80% of the cost of most machine learning projects, and Reality AI has analytics that can help reduce the cost of both. Reality AI Tools® can identify the most cost-effective combinations of sensor channels, find the best sensor locations, and generate minimum component specifications. It can also help you manage the cost of data collection by finding instrumentation and data processing problems as data is gathered.

Reality AI Software Solutions

Reality AI Tools®

Automatically explore sensor data and generate optimized models

RealityCheck™ AD

Anomaly detection for monitoring factory and process-industry assets

Automotive Seeing with Sound (SWS)

Combine hardware and software to give passengers a new level of protection

RealityCheck™ HVAC Solutions Suite

Complete framework for smart, self-diagnosing HVAC systems

RealityCheck™ Motor Toolbox

Advanced software toolbox enabling predictive maintenance and anomaly detection

Reality AI Utilities

Plug-in module for Renesas e² studio

Resources

ドキュメント

分類 タイトル 日時
ホワイトペーパー PDF 2.20 MB
ホワイトペーパー PDF 951 KB
パンフレット PDF 679 KB
ホワイトペーパー PDF 655 KB
ホワイトペーパー PDF 717 KB
ホワイトペーパー PDF 4.89 MB 英語
6件

ビデオ&トレーニング

Reality AI Overview

See how you can use Reality AI software and tools to develop products using sensors and machine learning on low-power, general purpose microcontrollers from Renesas. Learn more at renesas.com/ai

ニュース&ブログ

三相BLDC/PMSMモータのセンサレス負荷検出によるモータ性能の向上とストレスの軽減 ブログ 2024年10月16日
高度なAI/ML開発ツールへの無償アクセスを開発者に提供します ブログ 2024年7月16日
組み込み用エッジAI/TinyML導入ツールReality AI Toolsの無償評価版「Reality AI Explorer Tier」を提供開始 ニュース 2024年7月16日
Design AI/ML Applications the Easy Way ブログ 2024年3月13日
AIモデル生成のReality AI Toolsと統合開発環境e² studioがシームレスに統合 ニュース 2023年9月21日
How to Maximize the Lifespan of Electric Motors ブログ 2023年6月29日
FFTs and Stupid Deep Learning Tricks ブログ 2022年8月31日
Peaks and Valleys: How Data Segmentation Can Conserve Power and CPU Cycles in Edge AI Systems ブログ 2022年8月30日
How Do You Make AI Explainable? Start with the Explanation ブログ 2022年8月29日
Bias Isn’t Always Bad ブログ 2022年8月26日
Want to Reduce the Cost of Data Collection for Edge AI with Sensors? Only Do It Once. ブログ 2022年8月25日
国内初!AIによる工場向け異常検知ソリューション「RealityCheck AD」の提供を開始 ブログ 2022年8月17日
What is a Sensor, Anyway ブログ 2022年8月17日
What’s Wrong with My Machine Learning Model? ブログ 2022年8月17日
Successful Data Collection for Machine Learning with Sensors ブログ 2022年8月16日
Embedded AI – Delivering Results, Managing Constraints ブログ 2022年8月16日
Edge AI – Difference Between a Project and a Product ブログ 2022年8月16日
Comprehensive AI Engineering Software for Making Smart Edge Devices with Sensors ブログ 2022年8月15日
3 Ways to Make Your Machine Learning Projects Successful ブログ 2022年8月12日
It’s All About the Features ブログ 2022年8月12日
Rich Data, Poor Data: Getting the Most Out of Sensors ブログ 2022年8月12日
5 Tips for Collecting Machine Learning Data from High-Sample-Rate Sensors ブログ 2022年8月11日

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