@article {Ismaili-Alaoui2022900,
	title = {IoDEP: Towards an IoT-Data Analysis and Event Processing Architecture for Business Process Incident Management},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {13},
	number = {4},
	year = {2022},
	note = {cited By 0},
	pages = {900-915},
	abstract = {IoT is becoming a hot spot area of technological innovations and economic development promises for many industries and services. This new paradigm shift affects all the enterprise architecture layers from infrastructure to business. Business Process Management (BPM) is a field among others that is affected by this new technology. To assist data and events explosion resulting, among others, from IoT, data analytic processes combined with event processing techniques, examine large data sets to uncover hidden patterns, unknown correlations between collected events, either at a very technical level (incident/anomaly detection, predictive maintenance) or at business level (customer preferences, market trends, revenue opportunities) to provide improved operational efficiency, better customer service and competitive advantages over rival organizations. In order to capitalize the business value of data and events generated by IoT sensors, IoT, Data Analytics and BPM need to meet in the middle. In this paper, we propose an end-to-end IoT-BPM integration architecture (IoDEP: IoT-Data-Event-Process) for a proactive business process incident management. A case study is presented and the obtained results from our experimentations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions. {\textcopyright} 2022. All Rights Reserved.},
	keywords = {Big data, Business Process, Competition, Complex event processing, Complex events, Data Analytics, Data handling, Economic development, Efficiency, Enterprise resource management, Event Processing, Event processing architectures, Hot spot area, Incident Management, Information management, Internet of things, Machine learning, Technological innovation},
	doi = {10.14569/IJACSA.2022.01304104},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130098329\&doi=10.14569\%2fIJACSA.2022.01304104\&partnerID=40\&md5=af3b2fd1443242906731e18007ed61ab},
	author = {Ismaili-Alaoui, A. and Baina, K. and Benali, K.}
}
@article {Ismaili-Alaoui2018457,
	title = {Towards smart incident management under human resource constraints for an IoT-BPM hybrid architecture},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {10966 LNCS},
	year = {2018},
	pages = {457-471},
	doi = {10.1007/978-3-319-94289-6_29},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049367708\&doi=10.1007\%2f978-3-319-94289-6_29\&partnerID=40\&md5=8891163e3850dfdbdb3ce8aae9713f4e},
	author = {Ismaili-Alaoui, A. and Baina, K. and Benali, K. and Ba{\"\i}na, J.}
}
