Free Huawei H12-521_V1.0 Practice Exam with Questions & Answers | Set: 2

In Huawei's intelligent video surveillance architecture, the IVS3800 and CloudIVS 3000 represent different tiers of the platform but share a compatible underlying software-defined framework. The IVS3800 is often deployed as a foundational or management node in smaller to medium-sized clusters, whereas the CloudIVS 3000 is designed for large-scale cloud-based environments. While the two systems are interoperable and can be integrated within a unified cluster environment to ensure resource sharing and centralized management, there are specific functional roles assigned to each.

Specifically, when these systems coexist in a hybrid cluster, the CloudIVS 3000 typically functions in a capacity-extension role. According to the technical deployment standards, the IVS3800 and CloudIVS 3000 can be deployed in the same cluster, but the CloudIVS 3000 can serve only as a service node . This means that while the IVS3800 can handle management tasks, database operations, and service logic, the CloudIVS 3000 nodes are primarily utilized for their heavy-duty media processing and storage capabilities (service tasks). This hierarchical arrangement allows for flexible scaling, where users can add CloudIVS nodes to increase the total channel count and storage capacity of an existing IVS3800 infrastructure without overcomplicating the management plane.

The physical design of a data center for intelligent vision systems involves strategic placement of network switches to optimize cabling and performance. Two common architectures are Top of Rack (TOR) and End of Row (EOR). In a TOR deployment, Top of Rack (TOR) switches are deployed on the top of each cabinet and used for communication between servers in each cabinet and the external network . This approach minimizes the length of copper cabling within the rack and simplifies the expansion of individual cabinets.

Conversely, the EOR architecture centralizes the switching infrastructure. In this setup, End of Row (EOR) switches are deployed in the last cabinet at each row, and servers in all cabinets at each row are connected to switches through horizontal cabling . While EOR can simplify management by centralizing hardware, it requires significant horizontal cabling across the row. Huawei’s IVS planning recommendations specify that the management port and service ports of hardware devices (like the Taishan 200) connect to these switches. Specifically, the "Management TOR" handles the management plane (often using CE5800 series), while the "Service TOR" handles the high-bandwidth 10 GE service plane (often using CE6800 series), with both eventually aggregating through the EOR switch to connect to the wider customer network.

The correct answer is A. TRUE . In IVS3800 and Lite Edge network construction, the service plane relies on TOR switching for high-bandwidth service traffic, and link bundling is a standard design approach to provide bandwidth aggregation and redundancy. The material identifies the service-plane access layer explicitly: “Service TOR: TOR access switch on the service plane. The 10 GE optical port or GE port on the service plane is connected to the switch. CE6800 series switches are recommended” . This directly confirms that service TOR switches are a required part of the service-plane topology.

In practical Huawei data-center-style deployment, when multiple service links are aggregated between servers and TOR switches, eth-trunk must be configured, and static LACP support is used to ensure the bundled links operate correctly and consistently. That requirement aligns with standard network design logic for service-plane access in container-based edge environments, where stability and predictable uplink behavior are essential. Because Lite Edge depends on reliable service-plane connectivity and TOR-based aggregation, the statement that service TOR switches need to support static LACP mode and require eth-trunk configuration is correct.

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 correct answers are A, B, C, and D because a proper solar PV module check must cover both the module condition and the mechanical support condition . A damaged panel can reduce charging efficiency or create safety risks. Dirt, oil stains, dust, or snow on the panel surface can block sunlight and reduce power-generation performance. At the same time, the support structure must be checked for corrosion, rust, and stability , because outdoor PV assemblies are continuously exposed to weather, vibration, and environmental aging.

This conclusion is also consistent with the overall site-power design described in the training material, where Huawei’s integrated site solution includes “PV modules: two PV modules” and uses “SolarMax, and GridMax technologies to maximize energy efficiency of solar energy and mains and provide secure and reliable power supply” . Since PV modules are part of the site power system, both energy-conversion efficiency and structural reliability must be maintained. In actual maintenance practice, a clean, intact, and firmly supported PV module is necessary for stable long-term operation. Therefore, all four listed checks are valid and should be included.

The correct answers are A, C, and D because camera upgrade operations in the intelligent vision environment include license-related activation , algorithm package upgrade , and software version upgrade , but do not include simply resetting a camera. The material explains that apps on the intelligent camera platform can be “installed, activated, upgraded, and uninstalled online” and that the App Manager “installs, activates, monitors, and upgrades intelligent apps” . It also states that end users can install RPM software packages on SDCs and that “users need to purchase a license file … and load the license file on the SDC” for chargeable apps. This directly supports license loading and algorithm package upgrade as part of operational upgrade handling.

In addition, software version upgrade is a standard maintenance activity, and the material explicitly references upgrade behavior, including “During upgrade within the power module” and version-upgrade scenarios that require recalibration after software changes. Resetting a camera, however, is a recovery or configuration action, not an upgrade action. Therefore, the valid upgrade operations are A, C, and D .

The correct answer is A because the IVS3800 requires dedicated AI accelerator hardware to perform intelligent target analysis and vehicle analysis workloads. These functions rely on inference acceleration, not simply on general-purpose storage hardware. The training content directly links IVS3800 intelligent analysis capability to accelerator-card deployment by stating “Insert a maximum of six Ascend accelerator cards in slots 1 to 6” and then listing service capacities such as “Vehicle analysis … 360 channels in video mode” and “Object classification … 360 channels” for the accelerator-enabled configuration . This clearly shows that intelligent analysis capability is enabled by the AI accelerator card.

The other options do not satisfy this requirement. NVMe cards and SAS disks are storage components used for data access, caching, or storage expansion, but they do not provide the AI computing capability needed for intelligent analysis. T4 GPU is not the hardware specified in the material for IVS3800 intelligent target or vehicle analysis. Huawei identifies the Ascend AI accelerator card as the required component. Therefore, A is the correct answer.

The correct answer is D because the statement itself is inconsistent with the standard IVS3800 plane naming logic. In IVS deployment, network design is performed per network plane , and the material distinguishes service and management connectivity, for example by referencing service TOR and management TOR , and by using terms such as external service IP address and external management floating IP address for upper-layer connection planning . This clearly supports standard plane naming such as Outer_Service , Inner_Service , and Outer_OM .

The option D uses “InnerJDM” , which does not match the naming pattern established by the rest of the network design terminology. In professional IVS planning, this is most likely a typographical corruption of Inner_OM . Since the question asks which statement is false, the incorrect plane name makes D the false statement as written. The other options are structurally consistent with IVS network-plane design principles, where core predefined service and OM address ranges are typically kept unchanged to avoid deployment and expansion issues. Therefore, D is the false statement.