Applied Spatial Computing and AI

This unit examines how AI and spatial computing transition from research and science fiction into business-ready solutions. Students explore technology evolution, real-world use cases, business and human benefits, UX implications, technology selection and integration, and near-term trends including autonomous systems.

Learning Objectives

• Analyze the evolution of AI and spatial computing technologies by creating a timeline that links key research milestones to current commercial applications and autonomous systems
• Evaluate business and human benefits, risks, and challenges of AR/AI deployments by assessing at least three real-world company case studies and estimating potential ROI or user-impact metrics
• Apply technology-selection and integration criteria to propose a system architecture for a specified business scenario, specifying appropriate AI software categories, 3D asset needs, sensors, and integration steps
• Demonstrate principles of enhanced user experience and customer engagement by designing a simple workflow or prototype specification that outlines interaction models, UX components, and future trends considerations