Event Identification in Wireless Sensor Networks
Wireless sensor networks (WSNs) comprise a cornerstone to state-of-the-art and future CyberPhysical systems. Respective networking domain is characterized by a drastically different communication paradigm compared to typical wireless networks offering fle
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Event Identification in Wireless Sensor Networks Christos Antonopoulos, Sofia-Maria Dima, and Stavros Koubias
10.1 Introduction Based on various sources [1–4] an “event” is defined as an important phenomenon that occurs or may have occurred. Consequently, event identification is the procedure through which the respective phenomenon is accurately and reliably identified as well as recorded. Also an event is a specific case that stands out from an otherwise normal situation, exhibiting different data patterns compared to what is expected for a particular scenario. This chapter focuses on such procedures and algorithms specifically designed for or applied to wireless sensor networks (WSNs). Event identification in WSNs is a rapidly evolving research area attracting active interest from both the research and the industrial domains [2, 5–9]. The former is mainly due to its challenges as well as restrictions while the latter can be attributed to the fact that respective implementation is expected to drastically enhance WSNs practical applicability, usefulness, and widespread while at the same time mitigate notorious shortcomings of such networks. This is also indicated by the increasing number of prestigious publications and projects focusing on this objective. In this context the chapter’s main objective is to offer a comprehensive survey and classification or different approaches, techniques, and methodologies currently comprising state of the art in event detection targeting WSNs. Respective functionality is of cornerstone importance in a wide range of applications varying from medical, environmental, mechanical, and virtually any practical scenario [12, 15]. In the context of such scenarios instead of acquiring a complete knowledge and notion of the particular application, through event detection algorithms, the objective is to identify the occurrence or the possible occurrence of a type or set of types of events. The initial, though simplistic, idea of event detection
C. Antonopoulos () • S.-M. Dima • S. Koubias Department of Electrical and Computer Engineering, University of Patras, Patras, Greece e-mail: [email protected] © Springer International Publishing Switzerland 2017 G. Keramidas et al. (eds.), Components and Services for IoT Platforms, DOI 10.1007/978-3-319-42304-3_10
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assumes the existence of a specific threshold value, with respect to which and based on the deviation of a particular measurement to that threshold an event can be defined. Temperature is a characteristic example since exceeding a specific level (e.g., 40 ı C) can be categorized as an event. However, even in simplistic application scenarios it is identified that such approaches are inadequate to capture complex events depending on multiple inputs. Based on this deficiency a new even detection algorithmic trend is developed utilizing techniques based on pattern recognitions since all events can be represented as specific patterns. Respective techniques’ presentation, analysis, and classification are
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