ICOP: IoT-enabled policing processes

Francesco Schiliro, Amin Beheshti, Samira Ghodratnama, Farhad Amouzgar, Boualem Benatallah, Jian Yang, Quan Z. Sheng, Fabio Casati, Hamid Reza Motahari-Nezhad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationService-Oriented Computing – ICSOC 2018 Workshops - ADMS, ASOCA, ISYyCC, CloTS, DDBS, and NLS4IoT, Revised Selected Papers
EditorsXiao Liu, Antonio Bucchiarone, Michael Mrissa, Liang Zhang, Aditya Ghose, Djamal Benslimane, Qi Yu, Wei Zhang, Ying Zou, Zhongjie Wang
PublisherSpringer Verlag
Pages447-452
Number of pages6
ISBN (Print)9783030176419
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event16th International Conference on Service-Oriented Computing, ICSOC 2018 - Hangzhou, China
Duration: 12 Nov 201815 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11434 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Service-Oriented Computing, ICSOC 2018
CountryChina
CityHangzhou
Period12.11.1815.11.18

Keywords

  • Data Analytics
  • Internet of things
  • Knowledge Lake
  • Law enforcement
  • Policing
  • Process data science

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Schiliro, F., Beheshti, A., Ghodratnama, S., Amouzgar, F., Benatallah, B., Yang, J., Sheng, Q. Z., Casati, F., & Motahari-Nezhad, H. R. (2019). ICOP: IoT-enabled policing processes. In X. Liu, A. Bucchiarone, M. Mrissa, L. Zhang, A. Ghose, D. Benslimane, Q. Yu, W. Zhang, Y. Zou, & Z. Wang (Eds.), Service-Oriented Computing – ICSOC 2018 Workshops - ADMS, ASOCA, ISYyCC, CloTS, DDBS, and NLS4IoT, Revised Selected Papers (pp. 447-452). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11434 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-17642-6_42