Forest & Wildlife Research Center Publications and Scholarship

Abstract

Ambient Intelligence (AmI) refers to a networked environment of computing devices for implementing a "smart" system. AmI is built using sensors and actuators connected through real-time networks. 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 can help 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 analysis and more detailed design specifications. This article tries to give a clear snapshot of the design and structure of advanced AmI technology for an ambient-intelligent decision support system (Am-IDSS) for augmenting and extending the smart manufacturing landscape. Our approach is to explore the basic principles of an Am-IDSS architecture and structure concerning the role of the Internet, data, Industrial robotics, and other AI technologies. The structure of an Am-IDSS includes components for collaboration, an architecture for human-centered decision support, components for knowledge management, decision-making process support, and user-interface innovations. Therefore, having a system engineering design of an Am-IDSS is necessary for exploring and merging advanced manufacturing processes, rapid prototyping, collaborative virtual factory platforms, and open manufacturing into smart manufacturing landscape. To supplement this research, we concluded the study by proposing managerial suggestions for systems development and observations about future trends in implementing Am-IDSS.

Publisher

IGI Global: International Publisher of Information Science and Technology Research

Publication Date

7-1-2019

College

James Worth Bagley College of Engineering

Department

Department of Industrial and Systems Engineering

Keywords

Ambient Intelligence, decision support system, human-centered operation, smart manufacturing, artificial intelligence

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