Zühlke’s “Smart Airport Digital Twin Discovery” is a tailored 2 to 8-week engagement to equip airport operators to build an accurate digital representation of their physical operations. The Smart Airport Digital Twin Discovery sets the foundation to create a real-time operational insights model that simulates and monitors key airport processes, empowering airports to become data-driven, efficient, and proactive organizations.

The digital twin integrates data from various sources, such as flight schedules, baggage handling, passenger flows, and resource management, providing a unified, dynamic view of airport operations. By leveraging AWS cloud technologies, a Smart Airport Digital Twin enhances situational awareness, enables predictive decision-making, reduces operational risks, and optimizes resource allocation. The goal is to boost passenger experience, minimize delays, and maintain security and operational standards.

This Discovery assesses existing data sources, challenges, and integration requirements, creating a customized roadmap to design, build, and scale an effective Smart Airport Digital Twin. The structured approach mitigates risks, ensures alignment with strategic business objectives, and prepares airports for future scalability.

Benefits of the Offering

• Tailored Visualization and Simulation: A digital replica that captures the unique characteristics of each airport, offering insights tailored to operational needs and objectives.
• Industry Expertise: Leverage Zühlke’s extensive experience in complex data-driven solutions and high-performance user experiences, built with cutting-edge technology.
• Scalability and Flexibility: A solution that grows with the airport’s needs, providing continuous value and adaptability in a dynamic environment.

Discovery Activities

This Discovery lasts 2-8 weeks, depending on the airport’s specific requirements and complexity.

Part 1: Strategic and Technical Alignment

• Business Outcome Definition: Align stakeholders around targeted business outcomes for a unified vision of the digital twin’s impact.
• Technical Systems Review: Analyze existing data sources, including IoT devices, operational systems, and cloud infrastructure.
• Operational Complexity Assessment: Identify potential challenges and key areas for optimization, setting realistic expectations for digital twin capabilities.

Part 2: In-Depth Data Exploration and Simulation Mapping

• Data Integration Assessment: Identify and prioritize data sources required for the digital twin, focusing on data quality and real-time availability.
• Collaborative Workshops: Conduct workshops with stakeholders to identify operational goals, data priorities, and any gaps in current infrastructure.
• Skills and Capacity Analysis: Determine the competencies required for digital twin management, covering data analysis, cloud technology, and IoT integration.

Part 3: User Experience and Journey Mapping

• Stakeholder Identification: Identify core user groups (e.g., operations, airlines, security) and their specific needs for enhanced decision-making using a digital twin.
• Interaction Modeling: Design user interactions with the digital twin, emphasizing ease of access to real-time insights.
• Operational Scenario Exploration: Address typical operational challenges like delay management, resource optimization, and passenger flow to provide actionable insights.

Outcomes and Deliverables

Following the Discovery, Zühlke delivers a comprehensive report that includes:

• Executive Summary: Clear, actionable insights for decision-makers, highlighting key findings and recommended next steps.
• Strategic Alignment Roadmap: A plan to build alignment among business and IT leaders on digital twin implementation, whether for a single ecosystem or multiple operational areas.
• User Experience Recommendations: Targeted insights user interactions and use cases for the digital twin.
• Digital Twin Architecture Proposal: A high-level architectural design for a digital twin solution tailored to the airport’s unique requirements.
• AWS Tools and Services Guide: Recommendations for AWS tools and services necessary to support the digital twin solution, including AWS IoT TwinMaker, AWS IoT Core, AWS Lambda, and the AWS Well-Architected Framework.
• Enhanced KPI Recommendations: A suite of performance-driven KPIs for monitoring the effectiveness of the digital twin.
• MVP and Cost Proposal: A clear proposal for an MVP, including a detailed cost breakdown to deliver your Smart Airport Digital Twin.

Next Steps

Upon completing the Discovery, Zühlke will advance to the MVP phase, validating core assumptions and refining the approach based on live data and operational insights. This approach ensures that the digital twin solution is effective and delivers optimal value.