Future manufacturing processes have to be highly adaptive and transformable in order to support short product life cycles and highly customized products. For an implementation of such a flexible, so-called smart factory, which is driven by a massive proliferation and usage of tiny embedded, context-aware information and communication technologies, many challenges - technical and social ones - have to be addressed. We identify major problems and focus on the location of objects and persons within manufacturing environments as an enabling key technology. Existing methods and possible solutions are evaluated and discussed. Thereby, we focus on the crucial aspect of privacy for workers when location systems are utilized. We also present a semi-automatic positioning approach that solves the discrepancy of guaranteeing the privacy of persons and highly accurate location tracking
Privacy and security issues within geospatial information systems are of growing public and scientific interest. Especially with the launch of Google Street View and Google Earth, geospatial data has come to the attention of the public, thereby not only raising support for these technologies, but also massive concerns. It is the duty of science to pick up today"s uprising debates and to help structuring them, providing clarifications and different solutions. Thus, the aim of this paper is to contribute in form of an interdisciplinary discussion about privacy issues, both from a philosophical and an engineering point of view. Privacy and its importance are outlined as well as different privacy issues raised concerning the nowadays so popular 3D city models. In addition, technical solutions are shown which allow data providers to preserve privacy, but that won"t interfere with the advancements of these technologies.
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