Abstract
Analyzing data-driven and knowledge intensive business processes is a key endeavor for today’s enterprises. Recently, the Internet of Things (IoT) has been widely adopted for the implementation and integration of data-driven business processes within and across enterprises. For example, in law enforcement agencies, various IoT devices such as CCTVs, police cars and drones are augmented with Internet-enabled computing devices to sense the real world. This in turn, has the potential to change the nature of data-driven and knowledge intensive processes, such as criminal investigation, in policing. In this paper, we present a framework and a set of techniques to assist knowledge workers (e.g., a criminal investigator) in knowledge intensive processes (e.g., criminal investigation) to benefit from IoT-enabled processes, collect large amounts of evidences and dig for the facts in an easy way. We focus on a motivating scenario in policing, where a criminal investigator will be augmented by smart devices to collect data and to identify devices around the investigation location and communicate with them to understand and analyze evidences. We present iCOP, IoT-enabled COP assistant system, to enable IoT in policing and to accelerate the investigation process.
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References
Allen, D., Wilson, T., Norman, A., Knight, C.: Information on the move: the use of mobile information systems by UK police forces. Inf. Res. 13(4), 13–14 (2008)
Bandyopadhyay, D., Sen, J.: Internet of things: applications and challenges in technology and standardization. Wireless Pers. Commun. 58(1), 49–69 (2011)
Beheshti, A., Benatallah, B., Motahari-Nezhad, H.R.: Processatlas: a scalable and extensible platform for business process analytics. Softw. Pract. Exper. 48(4), 842–866 (2018)
Beheshti, A., Benatallah, B., Nouri, R., Chhieng, V.M., Xiong, H., Zhao, X.: Coredb: a data lake service. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM, pp. 2451–2454 (2017)
Beheshti, A., Benatallah, B., Nouri, R., Tabebordbar, A.: Corekg: a knowledge lake service. PVLDB 11(12), 1942–1945 (2018)
Beheshti, A., et al.: iProcess: enabling IoT platforms in data-driven knowledge-intensive processes. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNBIP, vol. 329, pp. 108–126. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98651-7_7
Beheshti, S.M.: Organizing, querying, and analyzing ad-hoc processes’ data. Ph.D. thesis, University of New South Wales, Sydney, Australia (2012)
Beheshti, S., Benatallah, B., Motahari-Nezhad, H.R.: Galaxy: a platform for explorative analysis of open data sources. In: Proceedings of the 19th International Conference on Extending Database Technology, EDBT, pp. 640–643 (2016)
Beheshti, S., et al.: Process Analytics - Concepts and Techniques for Querying and Analyzing Process Data. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-25037-3
Beheshti, S.M.R., Venugopal, S., Ryu, S.H., Benatallah, B., Wang, W.: Big data and cross-document coreference resolution: Current state and future opportunities. arXiv preprint arXiv:1311.3987 (2013)
Dustdar, S., Nastic, S., Scekic, O.: Smart Cities - The Internet of Things People and Systems. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60030-7
Maamar, Z., Sakr, S., Barnawi, A., Beheshti, S.-M.-R.: A framework of enriching business processes life-cycle with tagging information. In: Sharaf, M.A., Cheema, M.A., Qi, J. (eds.) ADC 2015. LNCS, vol. 9093, pp. 309–313. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19548-3_25
Schiliro, F., et al.: The role of mobile devices in enhancing the policing system to improve efficiency and effectiveness. In: Au, M.H., Choo, K.K.R. (eds.) Mobile Security and Privacy. Elsevier, Amsterdam (2016)
Singhal, A.: Introducing the knowledge graph. Google Blog (2012)
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Schiliro, F. et al. (2019). iCOP: IoT-Enabled Policing Processes. In: Liu, X., et al. Service-Oriented Computing – ICSOC 2018 Workshops. ICSOC 2018. Lecture Notes in Computer Science(), vol 11434. Springer, Cham. https://doi.org/10.1007/978-3-030-17642-6_42
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DOI: https://doi.org/10.1007/978-3-030-17642-6_42
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