Innovation Series: Advanced Science (ISSN 2938-9933)

Experience Optimization of AI-Based Smart Kitchen Dietary Recommendation Systems from a Service Design Perspective

Jiaying Li^1,2, Younghwan Pan¹

¹ Department of Smart Experience Design, Kookmin University, Seoul 01706, Republic of Korea

² College of Furnishings and Art Design, Central South University of Forestry and Technology, Changsha 410004, China

Abstract: In practical applications, current AI-based smart kitchen dietary recommendation systems still face challenges such as insufficient personalization, inconvenient interaction, and a lack of user trust, making it difficult to effectively meet users’ diverse and health-oriented dietary management needs. From a service design perspective, this study adopts questionnaires and semi-structured interviews to identify and analyze user needs and pain points in the usage process. The findings reveal the main obstacles encountered by users and propose targeted optimization strategies. These strategies encompass strategic-level value positioning (clarifying the system’s role and positioning in household health management), mid-level process optimization (enhancing the coherence and efficiency of data collection, recommendation generation, and feedback), and presentation-level interface interaction (improving usability and accessibility through voice, image, and visualization design). The study aims to provide theoretical reference and practical insights for the improvement of smart kitchen products and services, and to promote the rational application and dissemination of AI in healthy eating and smart living contexts.

Keywords: Service Design; Smart Kitchen; AI Dietary Recommendation; User Experience; Optimization Strategies

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