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Mobile Data Mining for Intelligent Healthcare Support
2009
2009 42nd Hawaii International Conference on System Sciences
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In this paper we propose a novel approach for Situation-Aware Adaptive Processing (SAAP) of data streams for smart and real-time analysis of data. ...
The implementation and evaluation of the framework for a health monitoring application is described. ...
In addition to basic concepts and techniques for situation modeling and reasoning, the CS model provides heuristics developed specifically for addressing context-awareness under uncertainty. ...
doi:10.1109/hicss.2009.309
dblp:conf/hicss/HaghighiZKG09
fatcat:rvbruiibofab5ftgyacja2mac4
Data Fusion and Type-2 Fuzzy Inference in Contextual Data Stream Monitoring
2017
IEEE Transactions on Systems, Man & Cybernetics. Systems
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Data stream monitoring provides the basis for building intelligent context-aware applications over contextual data streams. ...
The Type-2 inference process offers reasoning capabilities under the uncertainty of the phenomena identification. ...
Sensor monitoring systems Contextual data streams monitoring mechanisms are adopted to support the creation of intelligent applications on top of the observed data. ...
doi:10.1109/tsmc.2016.2560533
fatcat:ofaxiuzkubha5huebir2taihfe
MediAlly: A provenance-aware remote health monitoring middleware
2010
2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)
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The resulting provenance stream provides valuable insight while interpreting the 'episodic' sensor data streams. ...
The key to MediAlly's energy efficient operations lies in the adoption of an Activity Triggered Deep Monitoring (ATDM) paradigm, where data collection episodes are triggered only when the subject is determined ...
In our design we distinguish between the medical sensor data and the explanatory contextual data for two practical reasons. ...
doi:10.1109/percom.2010.5466985
dblp:conf/percom/ChowdhuryFM10
fatcat:xuythkv23fft3d5gkluoessjxi
Distributed Localized Contextual Event Reasoning under Uncertainty
2016
IEEE Internet of Things Journal
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., an unmanned vehicle or an autonomous device) captures context from data streams and reasons on the presence of an event. ...
We propose a distributed predictive analytics scheme for localized context reasoning under uncertainty. ...
Acknowledgement This work is funded by the European Commission (FIRE+ challenge, H2020) that aims to provide research, technological development and demonstration under the grant agreement no 645220 (RAWFIE ...
doi:10.1109/jiot.2016.2638119
fatcat:zjxukve26bb3pjdh27xquunhqq
Reasoning about Context in Uncertain Pervasive Computing Environments
[chapter]
2008
Lecture Notes in Computer Science
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An implementation and evaluation of the FSI model are presented to highlight the benefits of the FSI technique for context reasoning under uncertainty. ...
Addressing uncertainty is one of the major issues in contextbased situation modeling and reasoning approaches. Uncertainty can be caused by inaccuracy, ambiguity or incompleteness of sensed context. ...
In this project, we use the results of FSI for gradual tuning of parameters of data stream mining algorithms and perform intelligent and real-time analysis of data stream generated from sensors on mobile ...
doi:10.1007/978-3-540-88793-5_9
fatcat:qu66lxpu3fbkvfzeh5fijgxdbm
Semantic web technologies in pervasive computing: A survey and research roadmap
2015
Pervasive and Mobile Computing
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This article reviews the application of the Semantic Web to pervasive and sensor-driven systems with a focus on information modelling and reasoning along with streaming data and uncertainty handling. ...
Data streams coming from sensors are inherently noisy, imprecise and inaccurate, with di↵ering sampling rates and complex correlations with each other. ...
Sensor-driven systems impose the necessity to embrace the noise and errors inherent in data streams, and to make decisions that propagate this uncertainty throughout the system. ...
doi:10.1016/j.pmcj.2014.12.009
fatcat:dehfs5inkbexpagk265co5tvxi
Towards a Scalable and Optimised Context Broker for Seamless Interoperability within IoT Systems
2016
Procedia Computer Science
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The complexity of handling large volumes of streaming data increases in the presence of uncertainty caused by incomplete, altered, noisy and/or unstructured information. ...
The original VOs often need to be semantically enriched with more contextual details as they interact with applications and other reasoning engines, where they often evolve into composite virtual objects ...
Acknowledgements This work is partially funded by the French South African Technology Institute (F'SATI) at the Tshwane University of Technology (TUT), in Pretoria, Republic of South Africa. ...
doi:10.1016/j.procs.2016.08.016
fatcat:r5mfwxyayrdsviv5mutkdyurzi
Situation-Aware Adaptive Processing (SAAP) of Data Streams
[chapter]
2009
Computer Communications and Networks
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This approach uses fuzzy logic principles for modeling and reasoning about uncertain situations and performs gradual adaptation of parameters of data stream mining algorithms in real-time according to ...
streams that are generated by the various sensors. ...
(CS) model [5] , a general and formal approach for reasoning about context under uncertainty. ...
doi:10.1007/978-1-84882-599-4_14
dblp:series/ccn/HaghighiGKZ10
fatcat:vanwapzbsvbjfir6ycgauvizcm
Monitoring of Underwater Critical Infrastructures: the Nord Stream and Other Recent Case Studies
[article]
2023
arXiv
pre-print
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Specifically, we provide analyses of the available data, from Automatic Identification System (AIS) and satellite data, integrated with possible contextual information, e.g., bathymetry, weather conditions ...
To illustrate the capabilities and importance of S3A, we consider three events that occurred in the second half of 2022: the aforementioned Nord Stream explosions, the cutoff of the underwater communication ...
Alvarez for his hints and the useful discussions about the operational problem, and MarineTraffic for providing the real-world AIS data set used in Figs. 9-10. ...
arXiv:2302.01817v1
fatcat:zzwqxx6nmzdlfadbiimxtmbnim
CityPulse: Large Scale Data Analytics Framework for Smart Cities
2016
IEEE Access
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data and social media data streams. ...
detection, quality assessment, contextual filtering, and decision support. ...
reasoning is still under investigation [39] , [40] . ...
doi:10.1109/access.2016.2541999
fatcat:zpqzmyli7rdz7gktmedbvwovb4
Context-aware adaptive data stream mining
2009
Intelligent Data Analysis
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We perform intelligent and real-time analysis of data streams generated from sensors that is under-pinned using context-aware adaptation. ...
This paper presents a general approach for context-aware adaptive mining of data streams that aims to dynamically and autonomously adjust data stream mining parameters according to changes in context and ...
of data streams to factor in contextual/situational information. ...
doi:10.3233/ida-2009-0374
fatcat:gq6xtkhkkvfyxdrc5exafu6s5u
A Context-Aware Middleware for Context Modeling and Reasoning: A Case-Study in Smart Cultural Spaces
2021
Applied Sciences
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Context modeling and reasoning are two important aspects of context-aware computing, since they enable the representation of contextual data and inference of high-level, meaningful information. ...
Context-awareness middleware systems integrate context modeling and reasoning, providing abstraction and supporting heterogeneous context streams. ...
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ...
doi:10.3390/app11135770
fatcat:xh26qu3sizeghhlpjwjkhrjaju
Stream-Based Reasoning Support for Autonomous Systems
2010
European Conference on Artificial Intelligence
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By using streams, DyKnow captures the incremental nature of sensor data and supports the continuous reasoning necessary to react to rapid changes in the environment. ...
This includes a systematic stream-based method for handling the sensereasoning gap, caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic ...
An important problem, especially when bridging the sense-reasoning gap, is therefore to detect objects in streams of sensor data and to reason about their identities. ...
dblp:conf/ecai/HeintzKD10
fatcat:iatwpdjdyfbklbju5t2w5kicde
AfCAI systems: Affective Computing with Context Awareness for Ambient Intelligence. Research proposal
2016
Workshop on Affective Computing and Context Awareness in Ambient Intelligence
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Uncertainty handling Improvement of knowledge management methods for imperfect or incomplete context that allow for modelling dynamics of the uncertainty and provide ecient reasoning under incomplete or ...
Assuring these requirements is a major challenge for systems that operate in dynamic environment, where contextual information is constantly delivered in a streaming manner. ...
dblp:conf/afcai/NalepaKBL16
fatcat:ubegejwth5alrhhu7hv3tj4u64
Multimodality in Pervasive Environment
[chapter]
2010
Smart Innovation, Systems and Technologies
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In this paper we discuss some short-term research goals, including advanced techniques for joining and correlating multiple data flows, each with its own approximations and uncertainty models. ...
Future pervasive environments are expected to immerse users in a consistent world of probes, sensors and actuators. ...
In this paper, we described a simple Use Case. supporting the idea of using W3C Ontology of Uncertainty to write meta-assertions guiding hybrid reasoning strategies on sensor data. ...
doi:10.1007/978-3-642-14619-0_24
fatcat:aetz5njidzha5gol2lyq4w3mne
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