Information and communication technology (ICT) is impacting our daily lives more than ever before. Many existing applications guide users in their daily activities (e.g., navigation through traffic, health monitoring, managing home comfort, socializing with others). Although these applications are different in terms of purpose and application domain, they all detect events and propose actions and decision making aid to users. However, there is no usage of a common backbone for event detection that can be instantiated, re-used, and reconfigured in different use cases. In this paper, we propose eVM, a generic event Virtual Machine able to detect events in different contexts while allowing domain experts to model and define the targeted events prior to detection. eVM simultaneously considers the various features of the defined events (e.g., temporal, geographical), and uses the latter to detect different featurecentric events (e.g., time-centric, location-centric). eVM is based on different components (an event query language, a query compiler, an event detection core, etc.), but mainly the event detection modules are detailed here. We show that eVM is re-usable in different contexts and that the performance of our prototype is quasi-linear in most cases. Our experimental results showed that the detection accuracy is improved when, besides spatio-temporal information, other features are considered.
Semantic web techniques (e.g., ontologies) have been recently adopted for sensor network modeling. However, existing works do not fully address these challenges: (i) representing different sensor types (e.g., mobile/static sensors) to enrich the network with different data and ensure better coverage; (ii) representing a variety of platforms (e.g., environments, devices) for sensor deployment, thus, integrating new components (e.g., mobile phones); (iii) representing the diverse data (scalar/multimedia) needed for various applications (e.g., event detection); and (iv) proposing a generic model to allow re-usability in various application domains. In this paper, we propose HSSN, an ontology that extends the Semantic Sensor Network (SSN) ontology which is already re-usable and considers various platforms. We extend the representation of sensors, sensed data, and deployment environments to cope with these challenges. We evaluate the consistency, accuracy, clarity, and performance of HSSN.
In the context of social media, existent works offer socialevent-based organization of multimedia objects (e.g., photos, videos) by mainly considering spatio-temporal data, while neglecting other userrelated information (e.g., people, user interests). In this paper we propose an automated, extensible, and incremental Feature-centric Social Event Detection (F-SED) approach, based on Formal Concept Analysis (FCA), to organize shared multimedia objects on social media platforms and sharing applications. F-SED simultaneously considers various event features (e.g., temporal, geographical, social (user related)), and uses the latter to detect different feature-centric events (e.g., user-centric, location-centric). Our experimental results show that detection accuracy is improved when, besides spatio-temporal information, other features, such as social, are considered. We also show that the performance of our prototype is quasi-linear in most cases.
Recent technological advances have fueled the rise of connected environments (e.g., smart buildings and cities). Event Query Languages (EQL) have been used to define (and later detect) events in these environments. However, existing languages are limited to the definition of event patterns. They share the following limitations: (i) lack of consideration of the environment, sensor network, and application domain in their queries; (ii) lack of provided query types for the definition/handling of components/component instances; (iii) lack of considered data and datatypes (e.g., scalar, multimedia) needed for the definition of specific events; and (iv) difficulty in coping with the dynamicity of the environments. To address the aforementioned limitations, we propose here an EQL specifically designed for connected environments, denoted EQL-CE. We describe its framework, detail the used language, syntax, and queries. Finally, we illustrate the usage of EQL-CE in a smart mall example. CCS CONCEPTS• General and reference → General conference proceedings; • Information systems → Query representation; • Theory of computation → Grammars and context-free languages;• Computer systems organization → Sensor networks.
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