Real-Time Embedded Data Infrastructure for AI-Driven Systems
ITTIA DB Lite AI Software for MCUs
As microcontrollers (MCUs) evolve from simple control units into intelligent edge computing platforms, the role of data has fundamentally changed. Modern MCU-based systems, across automotive, industrial automation, medical devices, energy, and AgTech, are no longer just executing logic; they are continuously capturing, structuring, processing, and learning from data in real time.
To enable this transformation, a new class of software is required: Data Infostructure Software for MCUs, powered by ITTIA DB Lite AI. Data infostructure software provides the foundation for managing and transforming data on-device, enabling raw signals to become meaningful, actionable intelligence.
Why MCUs Need ITTIA DB Lite AI
With a dedicated infostructure data layer, systems are reliable and development is greatly simplified. ITTIA DB Lite AI embeds a deterministic, AI-ready data infrastructure directly inside the MCU.
MCUs operate under strict constraints:
- Limited RAM and storage
- Real-time execution requirements
- Interrupt-driven workloads
- Safety and reliability expectations
At the same time, MCUs must:
- Capture high-frequency sensor data
- Prepare data for AI inference
- Operate independently of cloud connectivity
- Maintain full data traceability
Deterministic
Ensures consistent, time-aligned data collection, providing reliable input for AI inference and eliminating variability that can degrade model accuracy.
Edge Time-Series
Organizes sensor data into structured sequences required for AI models (e.g., LSTM, anomaly detection), enabling temporal analysis and pattern recognition.
Feature Engineering
On-device real-time data cleaning and feature engineering (LAG, sliding windows, aggregation, statistics) transform raw signals into AI-ready inputs.
Power-Fail Safe
Guarantees integrity and continuity of historical data, ensuring that AI models operate on complete and trustworthy datasets, even after resets or power loss.
Fast & Compact
Deterministic AI data pipelines run inference and capture output in real-time using only tens to hundreds of kilobytes of RAM, depending on model and configuration.
Edge AI Pipelines
Seamlessly feeds structured features into on-device models (TFLite Micro, ONNX, etc.) for real-time AI inference such as anomaly detection, prediction, and more.
ITTIA DB Lite AI
Clean and Process Data
Downsample, fuse, and filter to prepare sensor data for AI inference on intelligent embedded devices.
Manage AI Data Flow
Connect purpose-built AI models to clean sensor data and query inference results in device applications.
Data + Models = Intelligence
Combine data with AI models to transform raw signals into meaningful insights.
AI-Ready Data Processing
Clean & engineer raw data into structured, high-quality inputs for explainable AI.
Visualize AI Data Flow
Observe sensors, feature engineering, AI inference, and decision/event logs.
Data-Driven AI Safety
Reliable, clean, consistent, and traceable data ensures model decision accuracy.
ITTIA DB Lite AI
Core Capabilities of ITTIA DB Lite AI
Deterministic Data Ingestion
Captures sensor data (e.g., current, vibration, temperature, voltage) with bounded latency, ensuring no disruption to control loops or ISR execution. ITTIA DB Lite AI is designed specifically for flash media (NOR, NAND, eMMC).
Embedded Time-Series Management
Organizes data into structured time-series streams optimized for:
- Sequential writes
- Efficient reads
- Minimal fragmentation
Built-In Data Processing Functions
Supports real-time transformation of signals into AI-ready features:
- Data bounding, temporal context, sliding windows
- Aggregation (AVG, MIN, MAX)
- Statistical features (RMS, variance, standard deviation)
Real-Time Data Access
Provides immediate access to both recent and historical data without blocking real-time tasks.
Power-Fail-Safe Persistence
Ensures:
- Atomic commits
- Crash consistency
- Fast recovery
- No data corruption or duplication
Native Edge AI Integration
Delivers structured, high-quality data directly into AI models, enabling:
- Predictive maintenance
- Anomaly detection
- SoC / SoH estimation in BMS
- Intelligent control systems
Architecture of ITTIA DB Lite AI
Key Benefits
Deterministic Execution
- No garbage collection pauses
- No background compaction jitter
- Bounded latency across operations
Reliability and Safety
- Power-fail-safe storage
- Consistent and recoverable state
- Suitable for safety-critical systems
Efficiency for MCUs
- Minimal memory footprint
- Optimized for Cortex-M and similar architectures
- No dependency on external services
Faster Time to Production
- Eliminates need for custom data pipelines
- Reduces integration risk
- Enables production-ready Edge AI systems
Explainability
- Full data lineage: sensor → signal → feature → inference → action
Key Use Cases
- Motor health predictive maintenance
- Battery Management Systems (SoC / SoH estimation)
- Industrial automation and robotics
- Medical device monitoring
- Smart agriculture sensing and optimization
- Automotive ECUs and Software-Defined Vehicles (SDV)
Key Insight
AI models alone do not create intelligent systems, data does. With ITTIA DB Lite AI, MCUs gain a deterministic, reliable, and AI-ready data foundation, enabling true intelligence at the edge.
Demonstrations
Request an ITTIA DB Lite AI demonstration tailored to your target market and experience firsthand how it transforms MCUs from simple controllers into data-aware, self-observing, and intelligent systems capable of real-time decision-making. By combining deterministic data ingestion, embedded time-series management, on-device processing, power-fail-safe persistence, and seamless Edge AI integration, ITTIA DB Lite AI enables developers to build reliable, explainable, and production-grade Edge AI systems, directly on resource-constrained embedded platforms.
