Industrial equipment generates valuable data every second, from vibration, temperature, current, pressure, and RPM to operating cycles and machine events. With the ITTIA DB Platform, this data can be continuously collected, managed, processed, and transformed into AI-ready intelligence directly at…
Read More
With the #ITTIA DB Platform, #STM32 developers can add the data foundation needed for real-time ingestion, historical context, data processing, feature engineering, AI integration, security, traceability, validation, and system observability. STM32 + ITTIA DB Platform = Data-Centric Edge AI.
Read More
Can MCUs Manage the Data Edge AI Needs to Be Useful, Reliable, and Explainable? Running AI on an MCU is only the beginning. Production-ready Edge AI depends on how well the device can capture, organize, preserve, process, and trace the data surrounding inference.
Read More
Edge AI is ready. As an embedded developer, are you ready too? Running an AI model on an embedded system is only part of the challenge. Production-ready Edge AI also requires reliable data ingestion, historical context, real-time processing, feature engineering, deterministic access, and…
Read More
MCUs operate with limited memory, fewer cores, constrained flash, and strict real-time requirements. That means data ingestion, storage, processing, feature engineering, and AI inference must all compete for the same resources, without disrupting deterministic system behavior. The ITTIA DB Lite…
Read More
IAR Workbench + STM32Cube: Whether developers build with IAR Embedded Workbench or STM32Cube, intelligent embedded applications need more than an IDE, compiler, and AI model; they need a reliable data foundation inside the MCU. ITTIA DB Lite provides structured, persistent data management, while…
Read More
Whether developers choose IAR Embedded Workbench or the STM32Cube ecosystem, advanced Edge applications need more than an IDE and compiler; they need a reliable data foundation inside the MCU. The ITTIA DB Lite product family adds structured data management, historical context, feature…
Read More
With STM32H5 + ITTIA DB Lite and ITTIA DB Lite AI, developers can continuously capture motor data, maintain local time-series history, calculate meaningful features, and enable AI-based anomaly detection directly on the MCU.
Read More
By combining STM32H5 with ITTIA DB Lite and ITTIA DB Lite AI, developers can continuously manage battery data, analyze historical behavior, engineer meaningful features, and enable local AI inference for anomaly detection and battery-health monitoring.
Read More
Without a reliable ITTIA DB Platform data foundation, even a highly accurate model can fail when it encounters incomplete sensor data, inconsistent features, limited history, timing problems, or changing operating conditions. The ITTIA DB Platform helps close this deployment gap by connecting the…
Read More
From device data to the Edge intelligence, The ITTIA DB Platform creates a complete data path across intelligent devices. By addressing data architecture early, organizations can improve AI accuracy, reduce development risk, support future models, and build intelligent products ready for real-world…
Read More
The ITTIA DB Platform provides this foundation across microcontrollers, application processors, gateways, and higher-level systems. ITTIA DB Lite manages real-time and historical data directly on MCUs, while ITTIA DB Lite AI supports data preparation and feature engineering for embedded inference.…
Read More
Edge AI is often introduced through models, processors, and inference performance, but reliable intelligence begins with trusted device data. Sensors continuously generate temperature, vibration, voltage, current, pressure, images, and operational events that must be captured, cleaned, synchronized…
Read More
By combining NXP S32 processors with the ITTIA DB Platform, automotive developers can build mature Edge AI applications that go beyond running an AI model. Relational and time-series data management enables vehicle systems to ingest sensor and CAN data, preserve historical context, perform real-…
Read More
Edge AI collects and processes data locally with the help of feature engineering to clean and organize the raw data. The ITTIA DB Platform provides infrastructure to support feature engineering and data management, transforming raw data into meaningful and reliable features that enable traceable AI…
Read More
With STM32 devices and ITTIA DB Lite AI, developers can build intelligent motor health monitoring at the edge by capturing sensor data, preserving time-series history, generating AI-ready features, and logging inference results locally on the microcontroller. For robotics, cloud-only intelligence…
Read More
By combining STM32H7 with ITTIA DB Lite Product Family, developers can build high-performance, data-centric edge devices that reliably collect, manage, process, and transform sensor data into AI-ready insights directly on the microcontroller. From deterministic data management and time-series…
Read More
ITTIA DB Platform provides the deterministic Edge AI data infrastructure to acquire, manage, process, and preserve battery data, generate AI-ready features, and maintain complete operational history for predictive maintenance, Remaining Useful Life (RUL) estimation, and explainable AI. The result…
Read More
Learn how ITTIA DB Lite AI provides the deterministic data infrastructure for TensorFlow Lite and LiteRT, from real-time sensor acquisition and persistent time-series management to feature engineering, explainable AI, and production-ready Edge AI. Build intelligent embedded systems that are…
Read More
The ITTIA DB Platform provides the trusted data foundation for next-generation embedded systems, enabling devices to acquire, manage, process, and transform sensor data with accuracy, consistency, and determinism. By ensuring high-quality, AI-ready data pipelines, ITTIA helps vehicles, medical…
Read More
Discover how the ITTIA DB Platform enables next-generation Battery Management Systems (BMS) through deterministic data management, real-time analytics, AI-ready feature engineering, and Edge AI. Learn how battery telemetry can be transformed into actionable intelligence for accurate State of Health…
Read More
STM32H7 and the ITTIA DB Lite Product Family provide a powerful foundation for intelligent embedded systems with deterministic data management, time-series processing, power-fail-safe storage, and AI-ready data pipelines. Build smarter industrial, robotics, medical, and IoT applications faster by…
Read More
The combination of QNX RTOS and the ITTIA DB Platform provides a powerful foundation for intelligent robotics by combining deterministic real-time performance with deterministic data management. Together, they enable reliable data processing, historical analytics, AI-ready data pipelines, and…
Read More
By combining NXP S32 processors, eIQ Auto, and the ITTIA DB Platform, developers can transform raw vehicle data into actionable intelligence through deterministic data management, AI-ready feature engineering, real-time analytics, and secure data distribution. Together, they provide the foundation…
Read More
By combining STM32U5 with ITTIA DB Lite and ITTIA DB Lite AI, developers can build data-centric edge devices that reliably collect, manage, process, and transform sensor data into AI-ready insights directly on the microcontroller. From deterministic data management and time-series processing to…
Read More
As heavy construction equipment increasingly relies on embedded software, the ITTIA DB platform ensures secure data pathways and provides deterministic data management to support reliable decision-making. ITTIA Edge AI can improve outcomes in safety, efficiency, and cost for construction equipment…
Read More
With STM32 Sensor Fusion and ITTIA DB Lite AI, developers can collect, clean, synchronize, and manage real-time sensor data directly on microcontrollers to build reliable Edge AI pipelines for robotics applications. By transforming raw sensor streams into AI-ready insights, ITTIA DB Lite AI enables…
Read More
AI-Ready Robotics combines real-time hardware, deterministic software, sensor fusion, and explainable Edge AI to build intelligent autonomous systems at the edge. From Cortex-M control and Cortex-R safety processing to Cortex-A AI computing, modern robotics is becoming a distributed edge…
Read More
The EU Cyber Resilience Act (CRA) is reshaping cybersecurity requirements for connected vehicles and software-defined mobility. The ITTIA DB Platform helps automotive organizations build secure and resilient Edge AI systems through deterministic data management, power-fail-safe storage, secure…
Read More
As vehicles become software-defined, trusted edge data drives real intelligence. With relational models in ECUs, systems become deterministic, explainable, and real-time, enabling instant decisions without connectivity.
Read More
Are you ready for EU Cyber Resilience Act, CRA, as it is reshaping how intelligent connected devices are designed, secured, and maintained. The ITTIA DB Platform helps organizations address CRA requirements through deterministic and power-fail-safe data management, secure local processing, reliable…
Read More
The ITTIA DB Platform now supports the latest STM32N6, enabling developers to build data-centric Edge AI systems with deterministic on-device data management. Now STM32 devices can reliably capture and manage high-frequency sensor signals, structure time-series data, and prepare feature windows for…
Read More
FreeRTOS, STM32, and ITTIA DB Lite together form a production-grade platform for Edge AI data management, processing, and analytics. FreeRTOS guarantees real-time determinism, STM32 delivers scalable and capable hardware, and ITTIA DB Lite provides the reliable data foundation that AI systems…
Read More
ITTIA DB Platform achieves edge data cleaning and preparation by running directly on the device to turn raw sensors burst into structured, trustworthy, AI-ready records, deterministically. It timestamps and orders samples on ingest, enforces schemas and units, applies constraints and outlier rules…
Read More
ITTIA DB Lite is a purpose-built data engine engineered specifically for MCUs, delivering a tiny memory footprint, real-time responsiveness, crash-safe reliability, ISR/DMA-aware ingestion, deterministic operations, and a safety-ready design suitable for automotive, medical, and industrial…
Read More
Running ITTIA DB Lite on FreeRTOS lets MCU devices ingest, store, query, and learn from high-rate sensors deterministically, with crash safety, flash endurance, and built-in security.
Read More
ITTIA DB Lite and IAR Embedded Workbench together deliver a uniquely powerful foundation for MCU-based embedded systems by combining a compact, high-performance database engine with a world-class optimizing compiler and advanced debugging environment.
Read More
There’s a quiet moment in every embedded project when the team finally admits it: “We can’t keep building everything from scratch.” It usually happens somewhere between the third rewrite of the ring buffer, the second all-nighter debugging a corrupted flash log, and the uncomfortable realization…
Read More
The ITTIA DB Platform turns the STM32H7 from a fast controller into a smart, self-reliant data node by combining three components: ITTIA DB Lite for MCU-grade, power-fail-safe data management with deterministic ingestion, compact time-series/indexed storage (even vector support) and tiny footprint…
Read More
This is why developers are turning to ITTIA DB Lite for STM32 devices. It allows embedded systems to perform real-time data stream processing, ingesting, transforming, and analyzing data the moment it arrives. Unlike traditional approaches that rely on batch uploads and cloud-based workflows, ITTIA…
Read More
Drones and unmanned vehicles are moving into the work we don’t want humans to do: inspecting bridges and powerlines, monitoring crops and coastlines, detecting gas leaks, mapping disaster zones, supporting first responders, and streamlining site-to-site logistics. Even consumer use is growing,…
Read More
The future of embedded systems data management lies in integrating lightweight, real-time databases with AI-enabled edge processing, allowing devices to collect, analyze, and act on data autonomously.
Read More
In the evolving landscape of edge computing and intelligent devices, STM32-based systems running on RTOS platforms are no longer passive control units, they are now expected to act, adapt, and learn from real-time data.
Read More
Powerful STM32 devices sit at the edge with fast sensors, tiny RAM/flash, and real-time deadlines, so data management can’t be an afterthought. A time-ordered, deterministic data layer lets control loops hit worst-case timing, survives brownouts with crash-safe commits, and preserves media with…
Read More
Some folks say a blog should never mention a product; it sounds too salesy. I disagree. When a technology has been built over years, shaped by real customer feedback, and proven in the field, it deserves to be talked about clearly and proudly.
Read More
Artificial intelligence at the edge is transforming how devices collect, process, and act on data in real time. AI edge enablement relies on efficient data processing and management to deliver intelligent insights directly where data is generated, eliminating the need to constantly depend on cloud…
Read More
The IoT+AI combo is changing everything from smart homes and wearables to industrial automation and connected cars. But while everyone talks about big data and machine learning, the real game-changers often get overlooked: data management at the edge software, real-time operating systems, and…
Read More
The buzz around IoT and AI is loud—and for good reason. Smart devices are everywhere, and AI is the brain behind the scenes. But none of it works without three unglamorous but critical pieces: data management, RTOS (Real-Time Operating Systems), and microcontrollers. These are the plumbing, the…
Read More
Data management for microcontrollers such as STM32 devices play a crucial role in modern automation by enabling real-time data collection, processing, and control, which is essential for optimizing processes, improving efficiency, and ensuring safety at the place of origin. For the edge…
Read More
The future of embedded devices will be built on software and data management fundamentals. Embedded edge data management enables device applications to process and manage data locally, near the source, within embedded systems or edge devices. This approach offers benefits like reduced latency,…
Read More