Spatial awareness in pervasive ecosystems

Dobson, Simon; Viroli, Mirko; Fernandez-Marquez, Jose-Luis; Zambonelli, Franco; Stevenson, Graeme; Serugendo, Giovanna Di Marzo; Montagna, Sara; Pianini, Danilo; Ye, Juan; Castelli, Gabriella; Rosi, Alberto

doi:10.1017/s0269888916000199

Cited by 3 publications

(1 citation statement)

References 103 publications

(189 reference statements)

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“…In the location-based approach, the focus is the location context (Dobson et al, 2016). The context modelling technique is the object-based model, in which data in the space model is used to describe the relationship between an entity and a space.…”

Section: Context-aware Approachesmentioning

confidence: 99%

A knowledge-based model for context-aware smart service systems

Dinh

Thi

Pham-Nguyen

et al. 2021

Journal of Information and Telecommunication

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The advancement of the Internet of Things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present the concept of a context-aware smart service system and propose a knowledge model for context-aware smart service systems. The proposed model organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system, and Network of service systems. The knowledge model for context-aware smart service systems integrates all the information and knowledge related to smart services, knowledge components, and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. In order to demonstrate the approach, two case studies about chatbot as context-aware smart services for customer support are presented.

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Section: Context-aware Approachesmentioning

confidence: 99%

A knowledge-based model for context-aware smart service systems

Dinh

Thi

Pham-Nguyen

et al. 2021

Journal of Information and Telecommunication

View full text Add to dashboard Cite

show abstract

Spatio-temporal model checking of vehicular movement in public transport systems

Ciancia

Gilmore

Grilletti

et al. 2018

Int J Softw Tools Technol Transfer

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We present the use of a novel spatio-temporal model-checker to detect problems in the data and operation of a collective adaptive system. Data correctness is important to ensure operational correctness in systems which adapt in response to data. We illustrate the theory with several concrete examples, addressing both the detection of errors in vehicle location data for buses in the city of Edinburgh and the undesirable phenomenon of "clumping" which occurs when there is not enough separation between subsequent buses serving the same route. Vehicle location data is visualised symbolically on a street map, and categories of problems identified by the spatial part of the model-checker are rendered by highlighting the symbols for vehicles or other objects that satisfy a property of interest. Behavioural correctness makes use of both the spatial and temporal aspects of the model-checker to determine from a series of observations of vehicle locations whether the system is failing to meet the expected quality of service demanded by system regulators.

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