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The increasing adoption of artificial intelligence (AI) is transforming engineering practices for urban infrastructure and public space development. Despite these advances, many smart engineering solutions remain technology-oriented and often overlook human behavior, user experience, and social interaction. This presentation introduces an AI-driven smart engineering framework that integrates human-centered design principles with intelligent technologies to support the planning and management of urban public spaces. The proposed framework combines behavioral observation, environmental data, and AI-based analytics to evaluate how people interact with urban micro-spaces. By utilizing machine learning techniques and data-driven decision support, the framework enables engineers and urban planners to identify user needs, optimize spatial layouts, and improve the functionality, accessibility, and sustainability of public environments. The presentation also discusses the potential integration of smart sensing technologies and digital engineering tools to support continuous monitoring and adaptive management of public spaces. A conceptual case based on urban micro-space design is presented to demonstrate how AI-assisted engineering can enhance evidence-based decision-making and create more responsive urban environments. The proposed framework contributes to smart engineering by bridging artificial intelligence, behavioral science, and sustainable urban design, offering a practical approach for future smart city development. The findings are expected to provide valuable insights for engineers, urban planners, designers, and policymakers seeking to develop intelligent, inclusive, and sustainable public spaces through AI-enabled engineering solutions.
