H19-619_V1.0 HCSP-Presales-Government Public Services V1.0 Questions and Answers

When AI is used across many government and urban domains, it becomes inefficient to build isolated islands. Instead, cities tend to buildunified AI platforms and shared compute resources, centrally coordinated.

Information integration and sharing eliminate data silos and enable cross-department decision-making, the foundation of smart governance.

A Smart City IOC is designed as a comprehensive command, monitoring, decision-support, and joint-enforcement center, integrating these functions to support urban governance from real-time monitoring to coordinated enforcement and decision-making.

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The Opinions assign urban-management departments responsibilities for municipal public facilities, city appearance & sanitation, garden and greening, urban-management law enforcement, and public-service–related management.

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A water IOC coverssituation awareness(monitoring),decision analysis(models & forecasting),linked command(coordination), and also interfaces strongly withemergency-rescue functions, so all four options are included here.

Phytium processors are developed based on theARM instruction set(e.g., Phytium 2000 series based on ARMv8). Zhaoxin and Hygon are x86-based (via VIA and AMD technology respectively). Loongson was originally MIPS-based and later moved to its own LoongArch ISA. Therefore, only Phytium is ARM-based.

Urban operations platforms typically design afive-unifiedclosed loop:

unified intake,

unified dispatch,

unified processing,

unified closure,

unified supervision/assessment.

Linked command spans frommunicipaltop-level down todistrict,county, andstreet/sub-districtlevels, ensuring a full vertical chain for coordination and response.

One-Network Collaboration is defined bylayered architecture (A),core scenarios (B),“five-cross” collaborative positioning (C), andconvenience–security–efficiency goals (D).

“Four Realities” refer toactual population, houses, units, and facilitieswithin a jurisdiction, providing the foundation for grassroots governance and grid management.

Foundational government data libraries usually includepopulation,legal-person,geospatial, ande-certificatedatabases as the core shared resources supporting government services and supervision.

The State Council’s institutional reform established theMinistry of Emergency Management, integrating multiple previously scattered functions, and explicitly aiming at anall-hazard, whole-processemergency management system.

An IOC (Intelligent Operation Center) solution’score capabilitiesinclude:

multi-source data integration,

real-time monitoring, and

cross-department linked command.

Linked command is akey IOC scenario, enabling unified resource dispatch and emergency response, so saying it is “not” an IOC function is incorrect.

The statement describes Huawei’s participation across multipleemergency-management sub-domainsand levels, not just pure technical delivery but also top-level design and standards involvement.

Huawei’s platform providescommunication + AI capabilities, and together with partners can indeed buildduty systems, emergency “one-map” command, etc., forming complete, competitive solutions.

Core competitive strengths includevideo command collaboration,5G multimedia calling, andvideo–network linkageto integrate conferencing, command, and communication. The other items are more product/scene add-ons, not the core strengths listed here.

“City One Cloud” is acomprehensive city/ government cloud architectureintegratinghybrid cloud,base cloud (regional nodes),DR cloudfor continuity, andXC cloud(domestic tech stack). Private cloud as a separate, stand-alone silo is not counted as a core “One Cloud” component here.

Policy documents clearly state thatdigital infrastructure(networks, data centers, etc.) is thebaseof the digital economy.

At the tPaaS (telecom PaaS/communication PaaS) layer, core supports areconverged communication(unified messaging/voice/video) andvideo conference/consultation; Wi-Fi 6 and video cloud are more infrastructure/service-level capabilities beneath or beside tPaaS.

CCE does supportmulti-AZ active-activefor control and data planes, enhancinghigh availability and continuityfor critical workloads.

OBU (On-Board Unit) is anin-vehicledevice, not a roadside sensor; all others are road-side or perception devices.

Different official architectures define the “three enablements” slightly differently (e.g., data, AI, application; or data, AI, integration). Saying it isspecifically and only“data, AI, IoT enablement” does not match the standard definition in this context, so this statement is considered inaccurate.

OCR (Optical Character Recognition) extracts text from images and documents, providing structured input for classification and recommendation engines.

Policies clearly define “One-Network Handling / Collaboration” as part of the “Internet + Government Services” reform, focusing specifically ongovernment-service digitalization—standardizing service items, optimizing processes, and enabling online integrated handling.

Policies clearly encouragecross-level, cross-department collaborative office networks, emphasizingcentralized construction, security, mobility, intelligence, and platformization.

From a value perspective, One-Network Unified Management is positioned toaddress governance bottlenecks and raise satisfaction (B)andbuild a unified digital foundation for city governance (D). AI mining and process re-engineering (A, C) are more like methods and tools than the top-level value statements adopted here.

Many references divide digital transformation into stages such asbasic informatization(traditional digitization of processes),application intelligence(using AI and big data to enhance decision-making and automation), andsmart/ecologicalization(building open, collaborative digital ecosystems). Here, “smart/ecologicalization” appears twice (B and D), but all options A–D together reflect the typical staged evolution path.

“One Matter” systems aim foronline integrated handlingof full processes, withzero in-person visits and no face-to-face, through process re-engineering and data sharing.

The four dimensions areone screen to view all,one network for monitoring & early warning,integrated linked command, andone-click analysis & decision. “One network to manage everything” overlaps conceptually and is not a separate defined dimension here.

The hub architecture consists ofcomputing infrastructure (A),AI platform (D), andecosystem algorithms (B). Smart applications (C) are built on top of these three and are not themselves the core architecture layers.

A city IOC servesmultiple roles and departments—operations centers, emergency command, specialized bureaus, as well as city leadership. It is not exclusive to the mayor.

Data modeling usually proceeds fromconceptual(business entities and relationships) tological(structures and rules) tophysical(actual storage structures). Data-quality reports belong to monitoring and assessment, not the modeling process itself.

TheNew Generation AI Development PlanandGuiding Opinions on Accelerating Digital Government Constructionboth stress building unified AI platforms thatintegrate computing, algorithms, and servicesto drive intelligent transformation in government.

City cloud construction stressesapplication interconnection,data sharing,resource pooling,unified management/O&M, andcross-region DR coordinationfor resilient operation.

“Code Recording” (trajectory tracking) is not a defined stage of the One-Code Access framework; the other steps reflect its official progression.

NB-IoT (Low-Power Wide-Area Network) is designed for end-device access, not backhaul communication. Water-network poles typically use 4G/5G or microwave links for data return; “service efficiency” is not a technical method.

This solution enforcesstrict separation of networkson a single device, preventing different security domains from being accessed simultaneously. This aligns with government network security and isolation principles inGB/T 22239-2019 (Cybersecurity Classified Protection Requirements), where boundary protection and cross-network isolation are key controls.

The solution builds on self-research, open ecosystems, and broad terminal integration; “5G priority” is not a listed pillar technology.

City “One Cloud” emphasizes shared hybrid architectures; a private cloud is exclusive and not part of the shared framework.

By proactivelypushing reminders and servicesto eligible users (instead of waiting for them to search and apply), the system reduces friction and missed opportunities, which improves perceived convenience and satisfaction.

The solutionnot onlymoves services online, it alsosupports and drives process optimization and re-engineeringto truly improve efficiency and experience. It isnotlimited to a simple “offline → online” move.

City perception focuses on real-time sensing of running status via IoT and sensors. Typical scenes areintelligent connected transport(A) andurban lifeline monitoring(water, power, gas, etc.) (C). OA and project approval (B, D) are process/office systems rather than direct sensing scenarios.

Urban sensing-network standards emphasizereal-time or minute-level responsefor security threats. “Hour-level closed loop” is too slow and does not meet industry requirements. The other options align with principles such as SLA guarantees, intensive construction, and trusted access.

GB50838-2015 specifies that thedesign service life of the main structure of an urban utility tunnel is 100 years. Full-lifecycle investment should therefore be calculated on this 100-year basis.

Ablockchain platformprovides distributed ledgers, immutability, and traceability, creating a trusted environment for cross-department data sharing. Big data, cloud, and AI support storage, analysis, and intelligence but do not themselves guarantee multi-party trust and tamper resistance.

Tidal scheduling dynamically allocates system resources by time or load conditions. In intelligent transportation systems, cameras can switch algorithms (e.g., congestion detection vs. illegal parking) based on time windows or context — a key feature of adaptive resource scheduling.

A comprehensive governance system must coverstandard processes,resource保障,dispute-resolution mechanisms,clear responsibility for key data, andstable IT principles—aligning with multi-dimensional governance frameworks (organization, process, technology, and responsibility).

IOC decision-support often includeseconomic-operation analysistopics andtransport / last-mile mobilitytopics, using integrated data to support policy decisions in these areas.

IoTDA provides device access, device management, message communication, and data routing/flow for connected devices. Industry applications (D) are built on top of these capabilities but are not themselves a core function of IoTDA.

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Global Perception refers to using IoT, sensors, and other technologies to collect city-operation data in real time, forming a dynamic monitoring network. “Intelligent discovery + proactive early warning” requires real-time, multi-source data collection and analysis, which matches the characteristics of Global Perception. Knowledge computing focuses on reasoning over data, elastic scheduling on resource allocation, and robots on process automation, none of which are the core capability forproactive sensingitself.

AI “root” tech refers tofoundational components:chips(hardware compute),frameworks(development platforms), andAI enablement layers(toolchains, runtime, acceleration). AI applications sit on top and are not part of the root layer.

The solution’s core strengths include5G multimedia calling (VoLTE),video–network linkage (integrating meeting and network resources), andvideo command collaboration. Party-building tools and emergency all-in-one machines are separate scenarios/products.

Machine learning optimizes recognition and comparison algorithms to enhance system accuracy; other options refer to procedural or peripheral functions.

Following theNational Government Informatization Project Management Measures, unified resource planning and sharing avoid waste and fragmentation. Amulti-tenant AI resource poolenables logical separation via virtualization while achieving centralized governance and efficient resource utilization.

The Mobile Trusted Office solution involvesEMM,5G dual-domain private networks, anddesktop-cloud tablet adaptationas solution components and technologies. “Honor mobile phone” is a specific hardware brand/model, not a conceptual component of the solution architecture itself.

Policy guidance defines the core of “One-Network Management” asefficient and collaborative handling of individual eventsthrough cross-department digital coordination. Cost, overall “digital government” status, and rigid organizational reform are not its core definition.

Object, time, evaluation, and process centers have all been implemented at scale as key business middle-platform modules supporting city governance scenarios.

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A Smart Water IOC normally includessituation awareness(real-time monitoring),decision analysis(big-data & model-based decision support), andlinked command(cross-department collaboration and emergency response).

The official vision emphasizes creating asmart and accessible governance experience—“easy to handle and smart to handle”—reflecting Huawei’s user-centered digital government philosophy.

Government Connect focuses onbasic security,office collaboration, andintegration capabilities.Joint commandfunctions belong to emergency/IOC solutions, andleadership cockpitsare usually separate BI/IOC components, not core Government Connect capabilities.

The solution covers the entire chain:data aggregation (A),development & governance (B),service-ization and secure exposure-control (C), andvisualization & applications (D).

One-Network Handling typically servesdata authorities,approval bureaus, and often links withcity operation centersto share data and services.

V2X and intelligent-traffic applications bringreal-time optimization, global coordination across regions, and more precise control strategies, often improving efficiency without massive new physical infrastructure.

Dual-middle-platform architecture (typically business + data) with pre-built standard modules greatly improves development efficiency. Real cases show the go-live cycle moving frommonths to weeks. Hours or minutes are unrealistic for such integrated government services; weeks is the reasonable scale.

Central planning explicitly emphasizesenhancing government-service efficiencyas a key task in the14th Five-Yearperiod.

For AICC (urban intelligent command/operation center) construction, the key basis is thenational integrated government big data systemguidance, which clearly specifies data-platform and system-construction requirements—making option C the most directly relevant.

The “three middle platforms” for government services are:Business Middle Platform,Data Middle Platform, andAI Middle Platform. The Technology Middle Platform is more about underlying technical architecture and is not counted as one of the three core government-service middle platforms.

Modern systems employForward Error Correction (FEC)andpacket retransmissiontechnologies to maintain basic audio-video performance even with substantial packet loss. 30% video and 80% audio loss degrade quality but do not make communication impossible.

Full-process efficiency analysis focuses on analyzing responsibilities, dispatch efficiency, and blame-shifting issueswithinthe process.Repeated complaintsare more of a service-quality outcome metric than a direct internal process-efficiency analysis dimension.

One-Network Handling requires collaboration in management (systems & rules), resources (infrastructure & platforms), data (standards & sharing), applications (system interconnection), and disaster recovery (continuity) to build an integrated online government-service platform.

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The business middle platform aims to tacklefragmented standards,duplication of systems,unshared development,data silos, andpoor interconnection, enabling unified standards, shared capabilities, and integrated data and services.

TheGuiding Opinionsemphasize institutional coordination, digital empowerment, and service optimization rather than relying solely on process-based assessments. Process supervision is only one of several mechanisms for ensuring progress; the continuous development of digital government depends primarily on innovation, standardization, and integrated governance.

Roadside sensing devices includeradar,RSU (Road Side Unit), andcamerasfor environment perception and car–road communication.OBU (On-Board Unit)is installed in the vehicle and is a vehicle-side device, not a roadside sensing device.

TheGovernment Connectsystem utilizesKooSearchtechnology for integrated document retrieval, supportingboth intelligent fuzzy and exact searches. Official technical documentation confirms that KooSearch enables multi-mode retrieval through keyword matching and semantic analysis, matching the described functionality.

Zero-trust emphasizesdynamic access policy per context (A),multi-dimensional continuous environment awareness and graded access (C), andrich fine-grained rules (E). Chip latency (B) and sandbox/watermark (D) are useful security features but not the distinctive zero-trust highlights emphasized here.

When building an IOC, common pitfalls are:overly broad “big and all” topic scopes (B),delayed physical site/screen construction lagging behind systems (C), andplatform components without real application scenarios (D). Standard components (A) are beneficial, not a problem.

“One machine for dual use” uses dual NICs, virtualization, or physical switching to createindependent network environments on a single device, thereby isolating networks and blocking cross-network paths that could be used for jump-board attacks. Terminal environment awareness, permission control, and sandboxes improve security but do not by themselves guarantee strict network-boundary isolation.

Manual dispatch often suffers fromdepartmental buck-passing (A),experience-based assignment errors (B),duplicate work orders (C), andunanswered hotlines (D), all of which reduce efficiency and service quality.

In the intelligent-connected cloud-control platform, theV2X Serverhandles vehicle–road collaboration, including perception and standardized distribution of road events (such as accidents or road works). High-precision maps and 3D GIS provide spatial/base data, while information security protects the system but does not manage events.

Mainstream large models includescientific-computing,NLP,CV, andmultimodalmodels, corresponding to key AI research and application domains.

Municipal big-data centers own the cross-department data integration responsibility and operate the IOC as the city’s digital nerve center.

“Seconds-level approval” relies onautomatic e-signatureson standardized digital forms and commitment letters, via integration with existing e-seal/e-signature platforms, to close the approval loop electronically.

The 12345 hotline focuses on citizen-appeal data analysis; disaster response is a separate emergency-management function.

Speech recognition supports hotlines and voice input, OCR text recognition extracts data from forms and certificates, and RPA automates repetitive approval and data-entry steps, together enabling full-process intelligent online services.

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It ensures public safety through rapid incident response and multi-agency coordination to protect citizens and assets.

A comprehensive data-governance blueprint must addressprocesses, quality mechanisms, architecture, organization, and policies. All listed items are necessary components.

A dispatch center mainly needs integrated platforms, middle-platform support, and intelligent dispatch algorithms to coordinate resources and tasks.Video intelligent analysisis more related to monitoring and security scenarios, not a core requirement of the dispatch center’s own scheduling capability.

CBR provides full machine and disk-level scheduled backups and rapid restoration. Other services do not handle data backup tasks.

As defined in theUrban Operation Management Service Platform Technical Standard, the monitoring and early-warning mechanism includesdiscovery, handling, supervision, and feedback, forming a closed loop and supporting the promotion of pilot standardization.

CDM performs large-scale, scheduled batch migrations between local and cloud environments; it is not a real-time sync tool.

In the framework, “2” stands for digital foundations and enabling platforms, not application entry points; hence A is incorrect.

The IoT platform connects sensors and devices to collect and control facility data in real time, achieving digital management of municipal assets.

AI in cities is challenged bylong-term sustainability (operation/maintenance) risks(A),rapidly emerging new scenariosthat require constant model iteration (C), andhigh local adaptation costsdue to differing infrastructure and data (D). Funding is a real concern but is not listed here as a core technical/implementation challenge.

These four pillars—interconnection, 4K video, unified management, and AI-powered meeting spaces—form the foundation of secure, modern meeting environments, consistent with theIntelligent Conference System Technical Specification.

The solution is built onroadside sensing,communication networks,cloud platformsfor scheduling and analytics, andon-board systems, forming an end–edge–cloud architecture.

Huawei’s grassroots governance emphasizes “seeing clearly, operating efficiently, coordinating well, and enforcing effectively.”

Public information shows that by mid-2021 the Huiyan Vision solution had expanded AI recognition to over 40 urban-management scenarios.

DGC offersindustry-knowledge reuse,end-to-end governance,multiple development modes,centralized asset management, andvisualized operations, helping enterprises quickly build robust data-running capabilities.

Intelligent approval servicesverify material substance, useOCRto extract and compare text,extract key approval elements, and performformal completeness and format checks, enabling automated or semi-automated approvals.

Medium-confidentiality data must not be exposed in plaintext.Ciphertext + MPC (Multi-Party Computation)keeps data encrypted during transmission and uses privacy-preserving computation so parties can jointly compute without seeing each other’s raw data. Plaintext schemes cannot meet the confidentiality requirement.

Hard cases usually arise fromperception and information limitationsof stand-alone vehicles (e.g., beyond line-of-sight perception, blind spots, and limited self-only information). These require cooperation via vehicle–road/cloud collaboration. Failure to recognize white vehicles is more of asensor and algorithm robustness issuethat can be improved on the vehicle side itself and is not a typical scenario requiring V2X/Intelligent-Connected enhancement.

A video conference management platform mainly coversconference scheduling, control, and management—such as unified control, unified reservation, unified O&M, and unified access. Monitoring retrieval (E) typically belongs to security or IT monitoring systems (for surveillance and log review), not a core function of the conference management platform.

The “three-layer block data model” divides data intospatial, basic, and business layersto support modular governance and topic-based analytics. The description aligns with standard data-governance frameworks.

Standard work-order intelligent algorithms mainly coverclassification and dispatch. “Similar-case” is more typically treated ascase retrieval/knowledge-base functionality, not a core algorithm type itself. “Difficult-case identification” also depends heavily on implementation details. Some technical references on intelligent customer-service systems focus on intelligentclassification and routingas the main algorithms and donotclearly list “similar-case” as an algorithm category. Therefore, the taxonomy in the statement is considered inaccurate.

A data standard normally includes a name, type, length, allowed values/range, and intended usage, ensuring consistent understanding, storage, and application of data across the organization.

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The complexity across multiple manufacturers and platforms requires amulti-cloud collaboration platformto integrate and interconnect heterogeneous systems at the business level. Unified management or a single-cloud meeting platform alone cannot solve cross-vendor interoperability.

Policy documents (e.g., State Council guidance on “Internet + Government Services”) position “One-Network Handling/Collaboration” as a key measure ofgovernment-service digitalization, focusing on process re-engineering, data sharing, and cross-department collaboration in approval and supervision.

Data architecture typically includes a data-asset catalog (organizes and classifies assets), data distribution (where data resides and how it flows), data models (structure and relationships), and data standards (definitions, formats, and conventions). Together they ensure data is consistent, findable, and supports the business.

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High-capacity vision models trained on large datasets generalize better, reducing overfitting and improving accuracy across event-detection tasks. Empirical results (e.g., ImageNet pretrained models) support measurable accuracy gains of around 5% in multi-scene recognition.

The plan sets goals aroundinnovation,ecosystem,application scale, andsupport systems(standards, security, etc.), to deeply integrate IoT with the economy and society.

Events are commonly reported via:professional systems(A),official online channels(B),new-media platforms(C), andgovernment hotlines(D). All four are standard, recognized channels for collecting public issues and appeals.

This metaphor illustrates thedemand–supply–coordination modelin “Internet + Government Services.” Citizens express service needs, the integrated platform allocates resources, and departments deliver execution—an exact reflection of the “Central Kitchen” governance concept.

The core modules areDiscovery,Dispatch,Handling, andAnalysiscenters, forming a closed loop; Evaluation is more of a performance layer, not a core run-time module.

The performance of pretrained models heavily depends on thequantity and quality of available data. Small models have fewer parameters and limited representational capacity, so with insufficient data, they struggle to learn generalized features. This often leads to underfitting or overfitting. As noted in technical documentation (e.g., Hugging Face), local adaptation typically requires large, diverse datasets—something small models handle poorly.

City vital-sign applications supportconfiguring indicators,monitoring and early warning,generating reports, andforwarding alarmsfor coordinated handling.

Intelligent approval relies on AI models and rules. In practice there are handwriting issues, non-standard forms, edge cases, and logic conflicts. Current AI cannot reliably handle100%of cases, so human review is still needed.