Over the past few years, the artifact-centric approach to workflow modeling has been beneficially evidenced for both academic and industrial researches. This approach not only provides a rich insight to key business data and their evolution through business processes, but also allows business and IT stakeholders to have a single unified view of the processes. There are several studies on the modeling and its theoretical aspects; however, the possible realization of this approach in a particular technology is still in its fancy stage. Recently, there exist proposals to achieve such realization by converting from artifact-centric model to activity-centric model that can be implemented on existing workflow management systems. We argue that this approach has several drawbacks as the transformation, which is unidirectional, poses loss of information. In this paper, we propose a framework for the realization of artifact-centric business processes in service-oriented architecture achieving a fully automated mechanism that can realize the artifact-centric model without performing model transformation. A comprehensive discussion and comparison of our framework and other existing works are also presented.

Indoor device-free localization and tracking can bring both convenience and privacy to users compared with traditional solutions such as camera-based surveillance and RFID tag-based tracking. Technologies such as Wi-Fi, wireless sensor, and infrared have been used to localize and track people living in care homes and office buildings. However, the presence of multiple residents introduces further challenges, such as the ambiguity in sensor measurements and target identity, to localization and tracking. In this article, we survey the latest development of device-free indoor localization and tracking in the multi-resident environment. We first present the fundamentals of device-free localization and tracking. Then, we discuss and compare the technologies used in device-free indoor localization and tracking. After discussing the steps involved in multi-resident localization and tracking including target detection, target counting, target identification, localization, and tracking, the techniques related to each step are classified and discussed in detail along with the performance metrics. Finally, we identify the research gap and point out future research directions. To the best of our knowledge, this survey is the most comprehensive work that covers a wide spectrum of the research area of device-free indoor localization and tracking.

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