Edge Intelligence
Real-Time AI with Cloud-Edge Collaboration
Edge intelligence with cloud-edge collaboration is an emerging technology that combines artificial intelligence (AI) and edge computing. It deploys AI algorithms at the edge of the network to achieve real-time data processing and intelligent decision-making, thereby overcoming the challenges of latency and data privacy in traditional cloud computing architecture. The edge intelligence solution aims to create an efficient, intelligent, and collaborative cloud-edge integrated architecture, making full use of the AI intelligent computing platform and its edge capabilities to provide a cloud-edge collaborative AI infrastructure. Whether in smart transportation, smart cities, industrial manufacturing, smart retail, smart healthcare, or other smart fields, it can achieve real-time data processing, intelligent analysis, and rapid decision-making while ensuring data privacy and low processing latency.
Challenges
Data transfer bottleneck
In edge application scenarios like smart manufacturing, smart cities, telemedicine, and smart transportation, exponential data growth leads to transmission delays and packet loss. Real-time data processing is crucial for business outcomes and user experience.
Traditional model is costly
The widespread distribution of heterogeneous edge devices makes tasks such as configuration, monitoring, and upgrading challenging. Decentralized operation and maintenance models significantly increase costs and complexity.
Difficulty in dynamic edge deployment
Varying resource conditions at edge nodes and evolving business scenarios make it challenging to dynamically adjust algorithm orchestration strategies for flexible scheduling and on-demand resource allocation.
Data security and privacy protection
Edge devices often collect sensitive data, making security and privacy protection during transmission and storage critical challenges that must be addressed.
Complex organizational structure management
Multi-level, multi-objective, multi-standard, and multi-regional organizational structures hinder unified management, limit resource sharing, and complicate efficient operations.
Capabilities
Cloud-edge collaborative computing capabilities
Seamlessly integrates cloud and edge computing to optimize AI model deployment and real-time data processing, ensuring efficient and intelligent operations across diverse scenarios.
Intelligent edge management
A one-stop operation and maintenance platform that manages edge devices, reduces total cost of ownership (TCO), and leverages AI to predict and proactively address maintenance needs.
Strong adaptability to heterogeneous environments
Ensures compatibility with various hardware resources, builds a dynamic computing power pool, and maintains stable operation across platforms for diverse deployment needs.
Flexible deployment and expansion
Supports agile deployment and horizontal expansion to meet evolving business flexibility needs, enabling rapid scaling and adaptation to changing requirements.
Efficient and secure data transmission
Implements advanced compression, caching technologies, and end-to-end encryption to ensure data transmission efficiency and robust security, even in high-demand environments.