zabbix-graphql-api/docs/use-cases/trade-fair-logistics-requirements.md

🏗️ 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 planned "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

• Analysis Document: docs/KI für Event- und Messelogistik.pdf
• Roadmap: roadmap.md