Affiliation:
1. Tecnológico de Monterrey, Mexico
2. University of North Texas, USA
3. University of Florida, USA
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.
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