Huawei H12-521_V1.0 Exam With Confidence Using Practice Dumps

The correct answers are A, C, and D because the documents prepared before IVS low-level design are the input materials used for design, deployment generation, and parameter definition, while the LLD report is an output of the LLD activity itself. The material emphasizes that network planning must be completed in advance, and the deployment process requires predefined addressing and parameter information. This is consistent with statements such as determining the network segment and IP address range for each network plane before deployment, and with the repeated use of fixed external service and management IP planning in domain and cluster configuration workflows .

From an engineering workflow perspective, the network plan file is required because network segments, IP ranges, and live-network planning must be decided in advance. A project configuration file is also needed because it carries deployment-specific parameters for the project. A JSON file is typically used as a structured import or export artifact generated by design tools and then consumed during planning or deployment preparation. However, the LLD report is not a prerequisite input document; it is the design deliverable produced after engineers complete the LLD work. Therefore, the required pre-LLD preparation documents are A, C, and D .

The correct answer is B. FALSE . Behavior analysis, video synopsis, and video search are not isolated single-function outputs. They are built on a chain of capabilities that includes moving-object extraction, trajectory processing, segmentation, indexing, and structured retrieval. The material shows this dependency very clearly. For synopsis, it states that “Moving object detection involves algorithms such as background modeling, scene segmentation, and moving object extraction” , then “Object trajectory extraction involves object tracking algorithms” , and finally the system “Generate[s] a compact video” by fusing trajectories and background frames . For video search, the document further explains that indexed features and structured search conditions are required to browse and retrieve target information efficiently .

Because these services involve both intelligent analysis and media-content handling or structured-search capability, treating them as requiring only the VA algorithm is too narrow. In practical deployment, the MCS-related capability is also needed to support the complete algorithm service chain. Therefore, the statement that only the VA algorithm is required is false.

The Cloud Service Platform (CSP) is the underlying infrastructure that manages containers, resources, and services for the intelligent vision platform. Routine maintenance and health checks are essential to ensure the continuous availability of video surveillance services. A comprehensive routine check of the CSP encompasses multiple layers of the system architecture.

First, the License status must be verified to ensure that all intelligent functions and channel capacities remain authorized and active. Second, monitoring CPU and memory usage is critical to identify potential resource bottlenecks that could lead to service instability or video stuttering. Third, for systems deployed in high-availability environments, the Cluster running status (including two-node cluster heartbeat and synchronization) must be checked to ensure failover capabilities are intact. Finally, since the platform utilizes a microservice architecture, checking the CSP and container running status is mandatory to verify that all functional modules (like the VCNAPI or BMU) are active and isolated as intended. By performing these checks regularly, administrators can proactively address issues before they trigger critical system alarms or data loss.