Developing Advanced Context Aware Tools for Mobile Maintenance

P. Pistofidis, C. Emmanouilidis
<span title="">2012</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/p3wtlm3j2fedxitkuu4bs3scau" style="color: black;">IFAC Proceedings Volumes</a> </i> &nbsp;
The rapid technological progress in the domains of wireless sensor networks, mobile application development and artificial intelligence has fueled the construction of "smart" environments in both domestic and industrial environments. Such environments are equipped with a wide range of sensors, identification tags and interaction devices, capable of sensing, recording, interpreting and reacting to human activity and presence. Context-awareness constitutes a major challenge for developers of
more &raquo; ... services, since both design and implementation are increasingly supported by widely adopted frameworks and well-structured tools. The value adding features of context-based services find their way into many industrial systems through the adoption of mobile computing and its state-of-the-art devices. Acting as a constant context monitoring agent, a tablet or a smartphone can expand the capacity of a shoop floor system actor to carry out asset management tasks. Context interpretation and system adaptation are highly specialized processes that essentially use predefined or dynamically build semantics to filter and configure the mobile actor's access session. In this paper we discuss the context semantics for an IT infrastructure that serves engineering asset management and specifically supports maintenance practice and planning. Evaluating the available software methodologies that can drive the implementation of such an infrastructure, we perform a suitability study for the development of a maintenance management and a condition monitoring portable console. Our goal is to identify and assess the weighted significance for a domain-focused set of functional parameters, used to define a context-based mobile tool scaled for industrial shop-floors complexity.
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