Recommended Solutions
Industry Trends
Business Challenges
Business Challenges
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Heavy Assets, High OPEX, Slow Construction
Constructing a data center is costly, involving equipment rooms, power supply, cooling, fire fighting, and system management outlays. Centers must be able to handle the highest peaks in traffic, which means a vast majority of the investment underutilized during normal hours. Construction is slow and cannot meet service development requirements.Constructing a data center is costly, involving equipment rooms, power supply, cooling, fire fighting, and system management outlays. Centers must be able to handle the highest peaks in traffic, which means a vast majority of the investment underutilized during normal hours. Construction is slow and cannot meet service development requirements. -
Ineffective Content-Data Integration
Automobile companies build separate content and management systems, forming data silos. Moreover, data models are not interoperable. Therefore, capturing customer profiles or implementing precision marketing is difficult. Automobile companies also need to purchase vertical medium resources at a huge cost, without any data quality assurance.Automobile companies build separate content and management systems, forming data silos. Moreover, data models are not interoperable. Therefore, capturing customer profiles or implementing precision marketing is difficult. Automobile companies also need to purchase vertical medium resources at a huge cost, without any data quality assurance.
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Challenging Data Assets Management
Traditional IoV construction emphasizes content accessed over the in-vehicle infotainment system. As more and more vehicles access the network, more data is amassed. The new generation of IoV platforms should focus on extracting IoV data value to provide drivers with a richer and more personalized service experience.Traditional IoV construction emphasizes content accessed over the in-vehicle infotainment system. As more and more vehicles access the network, more data is amassed. The new generation of IoV platforms should focus on extracting IoV data value to provide drivers with a richer and more personalized service experience. -
Arduous App Development
To develop and deploy an automated driving system, a company must gather, store, and manage masses of data. Tools integrating AI and using an advanced learning framework with high-performance computing capabilities help minimize costs of transferring data to the cloud, accelerate model training, and streamline development efforts.To develop and deploy an automated driving system, a company must gather, store, and manage masses of data. Tools integrating AI and using an advanced learning framework with high-performance computing capabilities help minimize costs of transferring data to the cloud, accelerate model training, and streamline development efforts.
Typical Scenarios
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Simulation Analysis
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Digital Marketing
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Connected Car
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Autonomous Vehicle
Simulation analysis, improving R&D efficiency
In automobile R&D, CAE is used to simulate and analyze rigidity, strength, modes, collision, and NVH.
Benifits
Digital marketing, driving car sales growth
Streamlines the service process, establishes data specifications, and integrates online and offline marketing, improving customer experience and promoting automobile sales.
Benifits
Allocates marketing resources to activities based on vehicle owner profiles by using Huawei AI algorithms, improving the proportion of self-owned channels and utilization of vertical media resources.
Related Services
Internet of vehicles, mining data value
Provides richer, and personalized services for vehicle owners, improving customer experience and loyalty.
Benefits
Autonomous vehicle development platform, accelerating the driverless car commercialization
Provides highly scalable storage, high-performance computing, and an advanced one-stop AI development platform. Enables users to collect, receive, store, and analyze automated driving vehicle data, supporting the field's comprehensive development.
Benifits
Performs end-to-end management of the data required for automated driving development. Imports masses of drive test data to the platform offline. Parses, filters, and marks the data, then simulates the realistic scenarios to model driving decision making and route planning, and then trains the model repeatedly.
Success Stories
Success Stories
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PSA uses HUAWEI CLOUD to support its global Connected Car platform, driving digital service innovation and providing high-quality connected cars for enterprises and individuals. -
JAC Motors uses HUAWEI CLOUD Connected Car solution to build a unified, flexible Connected Car platform, connecting a large number of vehicles to the platform while ensuring service security.