TOWARDS HIGHER PERSONALIZATION: AN AI-DRIVEN CONTEXT-AWARE SMART PRODUCT-SERVICE SYSTEM DEVELOPMENT APPROACH COMBINED WITH MULTI- CRITERIA DECISION-MAKING
DS 136: Proceedings of the Asia Design and Innovation Conference (ADIC) 2024
Year: 2024
Editor: Yong Se Kim; Yutaka Nomaguchi; Chun-Hsien Chen; Xiangyang Xin; Linna Hu; Meng Wang
Author: Yuan, Wenyu; Chang, Danni
Series: Other endorsed
Institution: Shanghai Jiao Tong University
Page(s): 186-194
Abstract
Significant advancements in internet deployment, computational intelligence, and network technologies have driven the development of a new generation of data-driven SPSS. This study introduces a novel development approach for SPSS, integrating context-aware artificial intelligence (AI) with multi-criteria decision-making (MCDM) methods to enhance the system's ability to handle vast amounts of context data and generate personalized services. The system comprises three key components: multi-source context gathering, user modality reasoning, and service recommendation. It collects data from sensors, processes it via cloud computing, and infers users' physical and emotional states. The service recommendation component employs MCDM techniques to prioritize services based on user modalities, thereby optimizing resource allocation. Two case studies were conducted to validate the effectiveness of the proposed approach in real-world system.
Keywords: Smart PSS, Context-aware system, Artificial intelligence, Multi-criteria decision-making