6.1 LORA Edge Cloud

The LORA Edge Cloud integrates blockchain, neural network engines, artificial intelligence deep learning, and Internet of Things (IoT) technologies. It merges three key computing paradigms—cloud computing, fog computing, and edge computing—to build an intelligent, autonomous, and secure edge digital ecosystem. This design aims to shift computing and storage resources from centralized data centers to the network edge, enabling low-latency local processing and intelligent decision-making, especially suited for real-time IoT applications.

The blockchain infrastructure of the LORA Edge Cloud consists of the following three components:

• LORA Chain — Serves as the decentralized computing and storage backbone of the ecosystem, functioning as the main chain that supports governance and value transfer;
• Distributed IoT — A foundational blockchain framework tailored for IoT, providing device identity management, secure communications, data ownership verification, and interoperability standards;
• Distributed AI — A blockchain module for decentralized training, validation, and deployment of AI models on private data, enhancing privacy, security, and data utilization efficiency.

This edge cloud system achieves a complete closed loop from on-chain data collection, encrypted processing, distributed training, to result feedback, greatly expanding the application of blockchain in edge intelligence and IoT domains.

6.2 LORA Data Value Network (L-DVN)

The LORA Data Value Network (L-DVN) is a decentralized data circulation and pricing platform built on the LORA main chain and its sub-chain architecture. It aims to address data supply-demand mismatches, value stagnation, and the challenge of data ownership verification.

The network is based on the following core components:

• Data Ownership Mechanism: Utilizes the immutability of blockchain to certify data sources and owners, preventing tampering and unauthorized use;
• Smart Contract Pricing Models: Enables suppliers and consumers to set algorithmic pricing rules based on data quality, scarcity, timeliness, and other factors for automated price discovery;
• Incentive Mechanism: Data providers are rewarded in LORA Tokens for uploading high-quality data and may opt-in for AI training usage;
• Data Validation Module: Incorporates AI models to perform multi-dimensional checks on data format, type, and range to ensure usability and security.

As the data hub of the LORA ecosystem, L-DVN supports upper-layer applications such as IoT devices, financial systems, and AI platforms, building a scalable “data-as-asset” network.

6.3 LORA Multi-Chain Collaborative Ecosystem

To overcome the performance and compatibility bottlenecks of a single-chain architecture, LORA adopts a "1+N" multi-chain design, enabling concurrent business processing and data isolation through a main chain plus multiple sub-chains. A flexible cross-chain mechanism further ensures efficient collaboration between ecosystem modules.

Key features include:

• Homogeneous Cross-Chain: Enables free flow of data and assets between LORA internal chains (e.g., between the main chain and AI sub-chain);