Ambient-Intelligent Decision Support System (Am-IDSS) for Smart Manufacturing

Abstract

Ambient Intelligence (AmI) is built using sensors and actuators connected through real-time networks for smart systems. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to translate data and signals into a language understandable by human users and to transform an operational setting from machine-centered to human-centered. However, the implementation of AI technology into an ambient environment requires quantitative modeling approaches to emphasize system requirements. This article aims to give a clear snapshot of the design and structure of advanced AmI technology for an AmI-based decision support system (Am-IDSS). The proposed approach explores the basic principles of an Am-IDSS structure concerning the role of the Internet, data, Industrial robotics, and other AI technologies for smart manufacturing. To supplement this research, the study is concluded by proposing managerial suggestions for systems development and observations about future trends in implementing Am-IDSS.

Knowledge Management in Society 5.0: A Sustainability Perspective

“…It is, therefore, important for the organization to subscribe to active knowledge management and effective representations of operational information, as well as experience-based information [111,112]. KM techniques should focus on enhancing existing methods of knowledge acquisition and design by overlaying the data, big data and information layers with a knowledge layer [113][114][115]. Big data, in this con-…”

“…It is, therefore, important for the organization to subscribe to active knowledge management and effective representations of operational information, as well as experience-based information [111,112]. KM techniques should focus on enhancing existing methods of knowledge acquisition and design by overlaying the data, big data and information layers with a knowledge layer [113][114][115]. Big data, in this context, presents great potential for organizations as it promotes data-driven decision making, generates higher revenue, improves productivity, provides a competitive edge and informs customer-relevant product design [107,116].…”

“…This includes at least two distinct sources of sensing, deciding and acting: knowledge in people and knowledge in machines [31,62,144]. The evolution of human-technology interaction as a result of new devices or questions about the increase in complexity in autonomous programs through the use of AI services and conversational interfaces (e.g., chatbots, virtual reality and augmented reality) can enable new conclusions about optimized KM systems in the age of digital transformation for organizations [115,125,136]. Furthermore, added value to organizations is created by obtaining essential information from different platforms at the point of delivery of products and services based on the required information delivery process.…”