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zabbix-graphql-api/docs/use-cases/trade-fair-logistics-requirements.md
Andreas Hilbig 97a0f70fd6 feat(query-optimization): implement GraphQL query optimization and enhance regression suite 
- **Optimization**: Implemented automatic Zabbix parameter optimization by analyzing GraphQL selection sets.

- **ZabbixRequest**: Added optimizeZabbixParams with support for skippable parameters and implied field dependencies (e.g., state -> items).

- **Resolvers**: Updated allHosts, allDevices, allHostGroups, and templates to pass requested fields to data sources.

- **Data Sources**: Optimized ZabbixQueryHostsGenericRequest and ZabbixQueryTemplatesRequest to skip unnecessary Zabbix API calls.

- **Regression Tests**: Enhanced RegressionTestExecutor with new tests for optimization (REG-OPT, REG-OPT-NEG), state retrieval (REG-STATE), dependent items (REG-DEP), and empty results (REG-EMPTY).

- **Documentation**: Created query_optimization.md How-To guide and updated roadmap.md, README.md, and tests.md.

- **Bug Fixes**: Fixed deviceType tag assignment during host import and corrected ZabbixCreateHostRequest to support tags.
2026-02-02 06:23:35 +01:00

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🏗️ Trade Fair Logistics Requirements

This document outlines the requirements for extending the Zabbix GraphQL API to support trade fair logistics, derived from the analysis of the "KI-gestützte Orchestrierung in der Messelogistik" (AI-supported orchestration in trade fair logistics) pilot at Koelnmesse.

📋 Project Context

The goal is to use the Virtual Control Room (VCR) as an orchestration platform to improve punctuality, throughput, and exception handling in trade fair logistics.

🛠️ Key Use Cases

  • Slot Risk Scoring & Proactive Rescheduling:

    • Description: Proactive detection of missed delivery slots using ETAs and historical data.
    • AI Function: Calculates slot-miss risk and suggests next best actions (e.g. shift slot, alternative gate).
    • Zabbix Role: Monitoring ETA vs. Slot time, triggering alerts on high risk.

  • Exception Copilot for Dispatch & Gate:

    • Description: Standardized workflows (Playbooks) for managing arrival deviations (e.g. no slot, wrong gate, missing documents).
    • AI Function: Classifies exceptions and provides communication templates.
    • Zabbix Role: Capturing exception events as triggers and managing the resolution state.

  • Multilingual Driver Assistant:

    • Description: Step-by-step instructions for drivers on-site to reduce misunderstandings and wrong turns.
    • Zabbix Role: Providing real-time status updates (e.g. "Gate 4 is ready for you") to external communication interfaces.

  • Handling Readiness (Stapler/Personal/Rampe):

    • Description: Coordinating truck arrivals with the availability of handling resources like forklifts and ramps.
    • Zabbix Role: Monitoring the status and capacity of logistics assets and personnel.

  • VCR Setup Copilot:

    • Description: Template-based configuration to scale the VCR for different venues (e.g. Koelnmesse, Düsseldorf) and varying event rules.
    • Zabbix Role: Management of venue-specific and event-specific host groups and templates.

⚙️ Technical Requirements for the API

  • Dynamic Device Modeling:

    • Support for complex Delivery entities as Zabbix hosts.
    • Inclusion of dynamic attributes such as Slot-ID, ETA, and Gate assignments.

  • Hierarchical Data Mapping:

    • Mapping nested logistics data (e.g. cargo details, handling status) to hierarchical Zabbix item structures.
    • Use of tags for classification and filtering of logistics tasks.

  • Real-time Telemetry Integration:

    • High-frequency ingestion of GPS and sensor data (e.g. temperature, shock) from mobile tracking devices.
    • Support for Zabbix trapper items to receive external push updates.

  • AI-Integration Hooks:

    • Enable external AI systems to push "Risk Scores" and "Next Best Actions" into Zabbix.
    • Use of Zabbix triggers to orchestrate AI-driven suggestions.

  • Workflow Orchestration:

    • Ability to trigger external actions (e.g. sending notifications to drivers, creating tickets) based on Zabbix triggers.
    • Integration with the Model Context Protocol (MCP) to allow AI agents to manage logistics exceptions.

  • Multi-Venue Templates:

    • Provision of reusable template structures for different exhibition centers and recurring events.
    • Support for bulk import/export of venue-specific configurations.

✅ KPIs for Success Measurement

  • Slot Hit Rate: Percentage of vehicles arriving within their booked time window.
  • P22-Quote: Frequency of vehicles needing to be redirected to waiting areas (P22).
  • Gate Waiting Time: Average time from arrival at the venue to successful check-in.
  • Throughput: Number of vehicles processed per gate/hour.
  • Average Handle Time (AHT): Mean time to resolve a logistics exception/ticket.
  • First Contact Resolution: Rate of exceptions resolved without further escalation.

🔗 References