Mapping for Activity Recognition in the Context-Aware Systems Using Software Sensors

Pathan, Kamran Taj; Reiff-Marganiec, Stephan; Hong, Yi

doi:10.1109/dasc.2011.56

Cited by 4 publications

(5 citation statements)

References 9 publications

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“…Several significant studies were developed to handle the uncertainty of information and context reasoning through fuzzy logic reasoning [38], [39], knowledge graph [80] and heuristic search modelling [81]. Other studies used combinations of approaches such as semantic language and keyword mapping [41], [42] semantic language and probabilistic reasoning [4], [6], [36], [7], and semantic language and data extraction or annotation [43], [44]. These applications existed from 2010 to 2014 and they were the third generation of context-aware applications.…”

Section: Results and Findingsmentioning

confidence: 99%

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A Robust Mechanism for Categorizing Context-Aware Applications into Generations

Opoku

2021

EJECE

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The hunt to categorize context-aware applications has been a prevalent issue to developers of context-aware applications. The previous categorizations were based on the functions of the applications. These mechanisms yielded limited results since many applications could not be categorized. This paper categorizes applications into four generations based on developmental trends through a literature survey. The first generation applications focused on data acquisition and used hardware sensors. The second generation applications focused on knowledge acquisition and used software sensors, semantic language and ontology-based modelling languages. The third generation applications focused on intelligent reasoning and used mechanisms to handle information uncertainty. The fourth generation applications deprecate cumbersome ruleset implementations and focus on artificial intelligence whilst taking into consideration the effect of the dynamics of users’ background and preference on contextual information. The study demonstrated that when applications, methods or technologies can be categorized over some time, it is better to classify them into generations.

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Section: Results and Findingsmentioning

confidence: 99%

“…Pathan et al developed applications to track users' activities using software sensors and keyword mapping to reduce noise [41], [42]. Users' activities were automatically tracked using software sensors based on semantic language.…”

Section: Developmental Trends Of the Applicationsmentioning

confidence: 99%

A Robust Mechanism for Categorizing Context-Aware Applications into Generations

Opoku

2021

EJECE

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“…We have presented a solution to the problem of associating data from SOAP messages with elements in the context model -thus allowing the generation of knowledge to be used in the context aware system. This technique which maps data from the XML payload in SOAP messages into an existing OWL model which then allows further reasoning rules to use that data to answer user queries and is a revised version from that presented in [8].…”

Section: Discussionmentioning

confidence: 99%

State of the Art of Service-Level Agreements in Cloud Computing

Alhamad¹

2017

Distributed Networks

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Context-aware systems are an instance of the ubiquitous or pervasive computing vision. They sense the users' physical and virtual surrounding to identify the best system support for that user and adapt the system behaviour accordingly. The overall architecture of a context aware system can be broken into a number of logical aspects: gathering context data, storing the data, deriving knowledge through reasoning and mining and retrieving that knowledge to finally adapting system behaviours. Context is anything characterizing the environment of the user -their location, the ambient temperature, the people they are with, their current activity and some even consider the user's mood. Traditionally context information has been gathered through the use of hardware sensors, such as GPS sensors or smart badges for locations and there has been work to track user's eye movements at their desk to see which application they are using. However, determining the activity of a user has shown to be elusive to being sensed with hardware sensors. As users use web services more frequently they are exchanging messages with the services through the SOAP protocol. SOAP messages contain data, which is valuable if gathered and interpreted right -especially as this data can be shedding information on the activity of a user that goes beyond "sitting at the computer and typing". We propose a complimentary sensor technology through the use of software sensors. The software sensors are essentially based on monitoring SOAP messages and inserting data for further reasoning and querying into a semantic context model. In this paper we consider details of extracting the data from SOAP messages in a non-obstructive way and show a solution to map the data from a SOAP message to our OWL ontology model automatically. On the latter, we specifically explain the methodology to map from SOAP messages to an existing structure of knowledge.

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“…However, there is growing acknowledgement amongst researchers that a pluggable approach offers a better engineering solution. Pathan et al [37] propose a generic approach to context aware modelling through the use of a separate component for context reasoning. Garlan et al [36] state that the use of external control mechanisms for self‐adaptivity is a more effective engineering solution than localising the solution.…”

Section: Factors That Influence Adaptationmentioning

confidence: 99%

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Mutanu

Kotonya

2019

IET softw.

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Software as a Service reflects a "service-oriented" approach to software development that is based on the notion of composing applications by discovering and invoking network-available services to accomplish some task. However, as more business organizations adopt service-oriented solutions and the demands on them grow, the problem of ensuring that the software systems can adapt fast and effectively to changing business needs, changes in their runtime environment and failures in provided services has become an increasingly important research problem. Dynamic adaptation has been proposed as a way to address the problem. However, for adaptation to be effective several other factors need to be considered. This paper identifies the key factors that influence runtime adaptation in service-oriented systems, and examines how well they are addressed in 29 adaptation approaches intended to support service-oriented systems.

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Mapping for Activity Recognition in the Context-Aware Systems Using Software Sensors

Cited by 4 publications

References 9 publications

A Robust Mechanism for Categorizing Context-Aware Applications into Generations

A Robust Mechanism for Categorizing Context-Aware Applications into Generations

State of the Art of Service-Level Agreements in Cloud Computing

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

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