Practical Development of IoT Platforms

Platforms are divided into layers like device access, data processing, and business applications to enhance scalability and maintainability.

• Device Access Layer
• Data Processing Layer
• Business Application Layer

Utilizing cloud-native technologies like containers and Kubernetes, microservices enable elastic scaling and high availability.

• Containerized Deployment
• Service Elastic Scaling
• Automatic Fault Recovery

Supports multi-level collaboration between cloud, edge, and devices to meet real-time and local intelligence requirements.

• Edge Computing Nodes
• Local Data Processing
• Offline Autonomy

Open APIs and support for multiple protocols facilitate integration with third-party systems and industry applications.

• RESTful/MQTT APIs
• Multi-Protocol Adaptation
• Ecosystem Integration

Large-scale device registration, grouping, remote control, and firmware updates.

• Batch Registration/Grouping
• Remote Control
• Firmware Upgrades

High-concurrency data ingestion, stream processing, and storage.

• Kafka/MQTT Ingestion
• Stream Processing
• Time-Series/NoSQL Storage

Condition-based triggering, data routing, and automated actions.

• Conditional Triggering
• Data Routing
• Automated Linkage

Multi-dimensional data dashboards and real-time alert notifications.

• Data Dashboards
• Real-time Alerts
• Multi-terminal Display

End-to-end encryption using TLS/DTLS to ensure data transmission security.

• Encrypted Transmission
• Data Tamper-proofing
• Privacy Protection

Multiple authentication mechanisms including OAuth2, certificates, and SIM cards.

• Multi-factor Authentication
• Trusted Device Access
• Access Control

Active-standby, load balancing, and automatic failover to ensure stable platform operation.

• Active-Standby Switchover
• Load Balancing
• Automatic Recovery

Real-time log auditing, anomaly alerts, and rapid response to security incidents.

• Log Auditing
• Anomaly Detection
• Automatic Alerting

Unified access for multiple systems, intelligent linkage, and energy efficiency optimization.

• Integrated Access Control/Security/Energy Consumption
• Automated Linkage via Rules Engine
• Energy Efficiency Analysis & Optimization

Remote device monitoring, fault alerts, and intelligent maintenance.

• Multi-protocol Device Access
• Remote Operations & Maintenance
• Predictive Maintenance

Distributed energy monitoring and intelligent scheduling.

• Energy Consumption Data Collection
• Intelligent Scheduling
• Carbon Emission Analysis

AI empowers the platform, enabling intelligent analysis and automated decision-making.

• Edge AI Inference
• Intelligent Alerting
• Adaptive Optimization

Optimizing energy efficiency to support carbon neutrality goals.

• Energy Consumption Monitoring
• Intelligent Scheduling
• Carbon Emission Analysis

Deep integration of platform APIs with industry ecosystems.

• Open APIs
• Cross-Industry Integration
• Ecosystem Co-creation