@article {Guermah2021110,
	title = {Dealing with context awareness for service-oriented systems: An ontology-based approach},
	journal = {International Journal of Service Science, Management, Engineering, and Technology},
	volume = {12},
	number = {4},
	year = {2021},
	note = {cited By 1},
	pages = {110-131},
	abstract = {In recent years, rapid advances in the enabling technologies for mobile and ubiquitous computing, software paradigms, embedded sensor technologies, and wide range of wired and wireless protocols have been witnessed. Specifically, context-aware services-oriented applications are emerging as the next computing paradigm in which infrastructure and services are seamlessly available. Contextawareness, being an important ingredient, plays a vital role in enabling such interactive smart environments. More recently, the increasing popularity of ontologies has led to new ontology-based models of context because of their potential to support sophisticated ontology-based reasoning methods. This paper presents an architecture for the development of context-aware services based on ontologies. The authors highlight the context metamodel and discuss about reasoning process. This research also presents the semantic approach for service adaptation in context aware environment. Copyright {\textcopyright} 2021, IGI Global.},
	doi = {10.4018/IJSSMET.2021070107},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108948717\&doi=10.4018\%2fIJSSMET.2021070107\&partnerID=40\&md5=57712a52da5717426a70263e22f08eea},
	author = {Guermah, H. and Guermah, B. and Fissaa, T. and Hafiddi, H. and Nassar, M.}
}
@article {Guermah2020300,
	title = {How can reasoning improve ontology-based context-aware system?},
	journal = {International Journal of Advanced Intelligence Paradigms},
	volume = {15},
	number = {3},
	year = {2020},
	note = {cited By 1},
	pages = {300-316},
	abstract = {Over the past two decades, the large evolution of software engineering, telecommunication and pervasive devices has lead to emergence of a new vision of development aiming at building systems to meet more complex and personalised needs known as context-aware systems. This type of systems is becoming the next computing paradigm in which infrastructure and services are sensitive to any change of the context, so that plays a crucial role to provide interactive intelligent environments. In parallel, contextual situation refers to a higher level of information inferred from different context data flow that can be extracted from physical and virtual sensors. The power of using situation is lies in their ability to provide a simple and comprehensible representation of context property, which preserve the services that manipulate them from the complexity of sensor readings, data transmission errors and inferencing activities. In this work, we aim to explore the added value of using ontology-based reasoning, focusing on first-order logic and fuzzy logic, to produce contextual situations. Copyright {\textcopyright} 2020 Inderscience Enterprises Ltd.},
	doi = {10.1504/IJAIP.2020.105824},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082202504\&doi=10.1504\%2fIJAIP.2020.105824\&partnerID=40\&md5=202a3b83c6a307a1c364213895e826ba},
	author = {Guermah, H. and Fissaa, T. and Guermah, B. and Hafiddi, H. and Nassar, M. and Kriouile, A.}
}
@article {Gryech2020,
	title = {Moreair: A low-cost urban air pollution monitoring system},
	journal = {Sensors (Switzerland)},
	volume = {20},
	number = {4},
	year = {2020},
	note = {cited By 25},
	abstract = {MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children{\textquoteright}s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution. {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
	keywords = {Agile deployments, Agile manufacturing systems, Air quality, Costs, Decision trees, Geographic information systems, Information systems, Information use, Learning systems, Machine learning, Mobile sensing, Monitoring, Particles (particulate matter), Particulate Matter, Pollution detection, Pollution monitoring, Random forests, Real-time information, Sensor deployment, Urban air pollution, Urban pollutions},
	doi = {10.3390/s20040998},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079609813\&doi=10.3390\%2fs20040998\&partnerID=40\&md5=dc90b4357fcdc64d82d12f57a45f971f},
	author = {Gryech, I. and Ben-Aboud, Y. and Guermah, B. and Sbihi, N. and Ghogho, M. and Kobbane, A.}
}
@conference {Guermah2018,
	title = {Using context ontology and linear SVM for chronic kidney disease prediction},
	booktitle = {ACM International Conference Proceeding Series},
	year = {2018},
	doi = {10.1145/3230905.3230941},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053485109\&doi=10.1145\%2f3230905.3230941\&partnerID=40\&md5=41a05c4c09330c364082c52d6546e08f},
	author = {Guermah, H. and Fissaa, T. and Guermah, B. and Hafiddi, H. and Nassar, M.}
}
