Foundations of Spatial Computing

This unit introduces the evolution, core concepts, and contemporary business significance of spatial computing driven by AI, including historical milestones (photography, film, television), VR/AR origins, and related enabling technologies. Students will explore real-world use cases, beneficiaries, UX revolutions, risks, and initial strategic planning to prepare for deeper technical and applied units later in the pathway.

Learning Objectives

• Analyze key historical milestones and user-experience revolutions (e.g., first photo, film, television, VR/AR) and synthesize their influence on the emergence and adoption of spatial computing by producing a timeline with annotated impacts.
• Demonstrate knowledge of spatial computing by defining core concepts and categorizing related technologies (AI, sensors, AR/VR, spatial mapping, cloud/edge systems) and mapping each to example applications.
• Evaluate business opportunities, stakeholder beneficiaries, and potential value propositions of AI-driven spatial computing by creating brief use-case assessments that include target users and measurable benefits.
• Apply strategic planning and risk-assessment methods to propose an initial organizational adoption outline that identifies key ethical, privacy, and safety risks and recommends mitigation strategies.