Iot and Data Integration

Savitri enables real-time, tamper-proof integration of IoT data with blockchain through a modular architecture designed for both enterprise systems and emerging market applications. As businesses and governments increasingly rely on sensor-based infrastructure, the need for secure, interoperable, and autonomous data pipelines has become mission-critical.

Integrating IoT data with blockchain infrastructure presents massive potential—but also immense challenges. With over 17 billion IoT devices globally by late 2024, expected to reach 30 billion by 2025, the need for unified, secure, and efficient systems has never been greater.

Protocol Incompatibility & Interoperability

Legacy systems often rely on proprietary protocols incompatible with modern IoT standards (MQTT, CoAP, OPC-UA), causing communication barriers. 70% of organizations report struggling with device compatibility due to varied protocols.

Security Risks & Vulnerabilities

Connecting legacy systems lacking modern security increases attack surface. Gartner reports that by 2025 75% of IoT devices will be vulnerable to data breaches without end‑to‑end encryption.

Scalability & Data Volume Handling

IoT generates massive data streams which many legacy systems cannot support due to limited processing/scaling capacity. IDC estimates that by 2025 over 50% of IoT data will require edge processing to reduce latency and bandwidth usage.

Data Format Heterogeneity & Synchronization

Disparate data formats (XML, JSON, raw sensor data) need ETL, mapping, and real-time event pipelines. A survey found 22% of IT decision-makers have data “trapped” in systems they don’t know how to move, and 79% have undocumented pipelines.

Data from IoT and legacy systems often collide with outdated formats, fragmented protocols, and growing security threats. Without scalable, interoperable solutions, critical data remains underused, siloed, or exposed — delaying transformation instead of enabling it.

Savitri introduces a blockchain-native IoT layer that streamlines connectivity, data flow, and automation through

Universal Integration Layer

Support for REST, MQTT, OPC-UA, and Modbus protocols, enabling seamless connection of industrial, consumer, and embedded devices.

Smart Contracts for Automation

Devices can trigger verifiable actions and logic directly on-chain — removing reliance on centralized control.

Decentralized Device Identity (DID)

Every IoT device is assigned a secure, verifiable on-chain ID, eliminating spoofing and enabling fine-grained access control.

Edge-Friendly Consensus

Savitri’s low-energy Proof of Unity allows edge devices and microcontrollers to participate in network validation, enabling more distributed IoT deployments.

AI-Powered Event Handling

On-chain machine learning agents can analyze telemetry data in real time, detecting anomalies, automating actions, and issuing alerts without third-party platforms.

Key Benefits

  • Interoperability Across Legacy Systems

    Connect SCADA systems, ERP databases, or API services directly into blockchain-based workflows.

  • Data Immutability + Access Control

    Immutable audit logs paired with encrypted, role-based access permissions — ideal for ESG, logistics, or compliance-based industries.

  • Energy-Efficient Architecture

    Optimized for edge computing — with minimal power draw, eliminating the need for energy-intensive gateways.

  • AI Integration for Predictive Analytics

    Run decentralized model inference or participate in federated learning directly on-chain using IoT telemetry.

  • Zero Middleware

    No need for cloud IoT hubs or SaaS tools — all logic, state, and event handling are processed through Savitri's programmable infrastructure.

Decentralized, real-time demand balancing with EPC-level audit trails

Edge analytics in manufacturing for early equipment failure detection​

Integrated air-quality, traffic, and resource metering with autonomous response

Federated diagnostics with privacy-preserving device analytics

Immutable cargo tracking and cold-chain monitoring