Overview
Description
Reality AI Tools® allows engineers to generate and build TinyML/Edge AI models based on advanced signal processing. Users can automatically explore sensor data and generate optimized models. Reality AI Tools contains analytics to find the best sensor or combination of sensors, locations for sensor placement, and automatic generation of component specs and includes fully explainable model functions in terms of time/frequency domains, and optimized code for Arm® Cortex® M/A/R implementations.
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.
AI Explore
Automated Feature Exploration/Model Generation
BOM Optimization
Use AI to find the most cost-effective components
Data Readiness
Understand the state of training and testing
Edge AI/TinyML
Super-compact, efficient code for the smallest MCUs
OptionalTarget Devices
Documentation
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| Product Brief | PDF 416 KB | |
| Brochure |
PDF
4.06 MB
AI-generated Summary:
Artificial intelligence is transforming embedded systems by enabling devices to process data locally with low power and high performance. This ebook explores endpoint intelligence, machine learning for embedded systems, AI-as-a-service for signal processing, and best practices for edge data collection. It provides engineers, developers, and business leaders with practical guidance to simplify AI deployment from cloud to edge and endpoint, positioning Renesas solutions at the forefront of embedded AI innovation.
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| Quick Start Guide | Emergency Scream Detection for VOICE-RA6E1 - Quick Start Guide
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| Flyer | PDF 683 KB | |
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| White Paper |
PDF
2.20 MB
Artificial Intelligence transforms industries, homes, and safety systems by enabling complex machine learning on embedded devices. This paper explores trends driving decentralized intelligence, key applications that benefit from AI, and how Renesas simplifies AI/ML design and deployment to overcome common development challenges.
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| White Paper |
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655 KB
Adding machine learning to embedded systems presents challenges like data variation, real-time needs, and device constraints. Traditional methods often fall short, but modern tools can simplify the process. Learn how Reality AI software enables sophisticated, real-time analytics on microcontrollers by making efficient use of sensor data, cutting R&D cycles, and overcoming the limitations of embedded AI deployment.
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875 KB
日本語
Reality AI software provides advanced tools for creating classifiers, predictors, and detectors optimized for sensor and signal data. Its unique data-driven feature discovery enables powerful real-time analytics for applications in sound, vibration, and electrical signals. This paper details the technology's advantages over traditional methods and its suitability for power-constrained embedded systems and edge devices.
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717 KB
Data collection is the most expensive and critical part of any machine learning project. For Edge AI and TinyML applications using sensors, proper planning and execution are essential for success. This paper outlines a comprehensive approach, using Reality AI software, to streamline data collection, monitor data quality in real-time, and get the most from your data through iterative coverage and synthetic augmentation techniques.
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628 KB
日本語
, 简体中文
This case study shows how advanced signal processing and machine learning enable electric motors in household appliances to self-monitor and detect issues early. Proactive maintenance reduces downtime, avoids costly repairs, and extends appliance lifespan, offering manufacturers a powerful way to boost reliability and efficiency in consumer electronics.
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| Product Brief | PDF 560 KB | |
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Design & Development
Sample Code
Sample Code
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| Sample Code | Voice Kit RA6E1 Voice Application Combo (VAS, VCR) Project
[Software=RA Flexible Software Package|v]
ZIP
13.75 MB
Application:
Artificial Intelligence (AI), Automotive, Communications Infrastructure, Consumer Electronics, Human Machine Interface (HMI), Industrial
Compiler:
ARMCC
Function:
Application Example
IDE:
e2 studio
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| Sample Code | Emergency Scream Detection for VOICE-RA6E1 - Sample Code
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| Sample Code | AIK-RA4E1 Asset Movement Recognition Project
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| Sample Code | AIK-RA6M3 Asset Movement Recognition Project
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Related Boards & Kits
AI Kit Development Platform with RA8D1
The AIK-RA8D1 provides developers with multiple and reconfigurable connectivity functions to expedite AI/ML system development. This easy-to-use hardware platform for multimodal AI/ML solutions is based on the RA8D1 MCU from the RA family of 32-bit MCUs.
The hardware platform is intended for use... Read More
AI Kit Development Platform with RA6M3
Multiple and reconfigurable connectivity functions to expedite your AI/ML System. Easy-to-use hardware platform for multimodal AI/ML solutions based on the RA6M3 MCU from the RA Family of 32-bit MCUs.
The hardware platform is intended to be used for different kinds of AI/ML single or multimodal... Read More
AI Kit Development Platform with RA4E1
Multiple and reconfigurable connectivity functions to expedite your AI/ML system. Easy-to-use hardware platform for multimodal AI/ML solutions based on the RA4E1 MCU from the RA Family of 32-bit MCUs.
The hardware platform is intended to be used for different kinds of AI/ML single or multimodal... Read More
RA6E1 Voice User Demonstration Kit
Easy-to-use hardware platform for Voice User Interface (VUI) solutions based on the RA6E1 MCU.
This VUI partner-enabled solution is based on the RA family of 32-bit MCUs. The hardware platform is used for all VUI partner-enabled solutions provided by Renesas within the Renesas Ready Partner... Read More
Test This Board Remotely
RA8M1 Voice User Demonstration Kit
Easy-to-use hardware platform for Voice User Interface (VUI) solutions based on the RA8M1 MCU.
This VUI partner-enabled solution is based on the RA family of 32-bit MCUs. The hardware platform is used for all VUI partner-enabled solutions provided by Renesas within the Renesas Ready Partner... Read More
Explore
Videos & Training
Explore embedded AI with Saud as he reveals methods for optimizing models on low‑power MCUs and MPUs. Learn how quantization, heterogeneous computing, and advanced optimization techniques make real‑time analytics, vision, and voice possible at the edge. Saud also demonstrates how Renesas solutions like RUHMI and Reality AI Tools streamline deployment for developers working under tight resource constraints.
Events & Webinars
News & Blog Posts
AI-Driven Feature Discovery
Features are mathematical descriptions of "things that matter" for purposes of telling the difference between classes, predicting a variable, or detecting anomalies.
Features searched by Reality AI Tools® include:
- Common transforms on raw data, including logs, powers, derivatives, signs, and more
- Parametric statistical features and peak analysis
- Spectral features, including power, phase, spectral shape, periodicity, cepstral, wavelet, etc.
- Linear and non-linear dimensionality reduction
- Time-frequency sparse coding and time pattern analysis
- Binary pattern and texture analysis
Automatically Explores Sensor Data and Generates Optimized Models
AI Explore
AI Explore automatically finds alternative solutions and tells you what it found.
Additionally, the processing requirements for each possible solution can be shown so you can make necessary trade-offs.
Explainable AI
With Explainable AI, specific class signatures can be inspected in terms engineers understand.
Sensor Selection
Identify the best performing sensors, and the best, most cost-effective locations.
Setting Specifications
Use AI to set minimum component specifications.
Automated Monitoring
The cheapest problems to fix are the ones you catch early. Reduce the cost of data collection through automated monitoring for common pitfalls.
Easy Integration
Easily integrate Reality AI Tools with your firmware build. Reality AI Tools supports Arm® Cortex® M, R and A architectures from all major manufacturers, as well as Linux and Windows. Many non-Arm architectures are also supported. Ask us about your target processor.
Add-ons for Reality AI Tools
Reality AI for MATLAB
Read MATLAB data files, and use Reality AI to generate models for the MATLAB Signal Processing and Machine Learning toolboxes. Full transparency of MATLAB code - See the details of optimized feature computations and machine learning models generated by Reality AI.
Reality AI for Radar
Automatically select and optimize radar pre-processing options for greater model accuracy. For professional developers working with radar.
Use Cases
Reality Time Analysis
Use our analytics engine to support hardware design (not just algorithms and model building)
Anomaly Detection
Reality AI software helps you detect anomalies by learning normal behavior. You can use the built-in anomaly detection and condition monitoring dashboard, or create your own.
Predictive Maintenance & Remaining-Useful-Life
Predict the remaining useful life of components (filters, etc.), identify operational conditions, and detect abnormal conditions.
Sensorless Sensing with Motor Control
Develop predictive maintenance applications with no addition to the Bill of Materials - only a firmware upgrade to the motor control board.
Resources
Support
Support Communities
- Sign Up for Reality AI Tools Explorer Tier
I submitted an application for a Reality AI account through info.renesas.com/reality-ai some time ago, but I have not yet received any account information. Could you please let me know if it is still possible to apply for a Reality AI account and when I might ...
Aug 19, 2024 - Is the Reality Al Tools always on-line? Is there local version of the Reality AI Tools?
I just got the credential for 30 day trial Demo for the Reality AI. I can use the portal and it seems that I can define my projects and run different tools there. It seems that there is no local installation of the Reality AI tools. Is this always the ...
Sep 11, 2024 - Questions about Sign Up for Reality AI Tools Explorer Tier
hi，I submitted an application for a Reality AI account through Reality AI | Renesas Electronics some time ago, but I have not yet received any account information. Could you please let me know if it is still possible to apply for a Reality AI account and when I might expect ...
Aug 19, 2024
Knowledge Base
- Can I tune the models myself, or is Reality AI Tools® software a “black box”?
Reality AI Tools software offers many options for model tuning. At the start of the process, you have the option to adjust window size and stride, or to use energy-triggered segmentation based on a virtual-oscilloscope trigger (see our blog on segmenting real-time sensor data, and our presentation ...
Oct 27, 2022 - What kind of edge device will Reality AI Tools® software support?
Reality AI Tools software is an Edge AI platform that can generate code suitable for use with a wide range of edge devices. We can generate code for microcontrollers using the GCC toolchain, which includes most all ARM Cortex M-, A- and R- class MCUs. We also support a number ...
Oct 27, 2022 - What algorithms does Reality AI Tools® software support?
Our approach at Reality AI focuses on algorithmic feature discovery and optimization, using a proprietary AI-driven determining optimum features for a given machine learning problem. In most cases, this drastically simplifies the machine learning problem, allowing use of compact, simple and efficient learning algorithms. For classification problems, this is ...
Oct 27, 2022
Support Communities
