scholarly journals Context-Aware Multi-layered Ontology for Composite Situation Model in Pervasive Computing

2020 ◽  
Vol 25 (5) ◽  
pp. 543-558
Author(s):  
Abderrahim Lakehal ◽  
Adel Alti ◽  
Philippe Roose
Keyword(s):  
Pervasive Computing ◽  
Real Life ◽  
Situation Model ◽  
Context Information ◽  
Mobile Service ◽  
Context Aware ◽  
Smart Systems ◽  
Services Delivery ◽  
Iot Devices ◽  
Smart Mobile

With the rapid advancement of technologies and analysis tools in the smart systems, enabling real-time context monitoring of user's living conditions and quality services delivery is increasing. Current studies in this area are focused on developing mobile applications with specific services, based on toolkit that allow developers to obtain context information from sensors. However, there exists a notable lack of ontology able to represent all the necessary context information starting from distributed users, and constantly changing environment. The modeling of user’s domains to represent diverse mobile and IoT devices, and finalizing with the description of user’s composite situations in smart-*(health, home, cities, car, office, etc.) domains. Considering interoperability, reusability, and flexibility, a new context composite situation ontology for smart systems is proposed with better representation of heterogeneous context. The ontology enables to sense, reason, and infer composite situations in various smart domains, prioritizes critical situations and facilitates the delivery of smart mobile service. Proposed ontology is formalized and validated on different smart environments with different user’s situations. Several experiments were carried out with a real-life motivating scenario. Experimental results showed that the proposed approach has reduced queries times and improved flexibility.

Service Selection with Uncertain Context Information

2012 ◽  
pp. 192-215 ◽  
Author(s):  
Yves Vanrompay ◽  
Manuele Kirsch-Pinheiro ◽  
Yolande Berbers
Keyword(s):  
Real Life ◽  
Similarity Measures ◽  
Service Selection ◽  
Context Information ◽  
Context Aware ◽  
Functional Requirements ◽  
Selection Algorithm ◽  
Service Description ◽  
Inexact Matching ◽  
Service Ranking

The current evolution of Service-Oriented Computing in ubiquitous systems is leading to the development of context-aware services. Context-aware services are services of which the description is enriched with context information related to non-functional requirements, describing the service execution environment or its adaptation capabilities. This information is often used for discovery and adaptation purposes. However, in real-life systems, context information is naturally dynamic, uncertain, and incomplete, which represents an important issue when comparing the service description with user requirements. Uncertainty of context information may lead to an inexact match between provided and required service capabilities, and consequently to the non-selection of services. In this chapter, we focus on how to handle uncertain and incomplete context information for service selection. We consider this issue by presenting a service ranking and selection algorithm, inspired by graph-based matching algorithms. This graph-based service selection algorithm compares contextual service descriptions using similarity measures that allow inexact matching. The service description and non-functional requirements are compared using two kinds of similarity measures: local measures, which compare individually required and provided properties, and global measures, which take into account the context description as a whole.

Resolving and Mediating Ambiguous Contexts in Pervasive Environments

2011 ◽  
pp. 122-147 ◽  
Author(s):  
Nirmalya Roy ◽  
Sajal K. Das ◽  
Christine Julien
Keyword(s):  
State Estimation ◽  
Pervasive Computing ◽  
Independent Living ◽  
Vital Signs ◽  
Context Information ◽  
Context Aware ◽  
Information Theoretic ◽  
Significant Challenge ◽  
Environmental Measures ◽  
Optimal State Estimation

Pervasive computing applications envision sensor rich computing and networking environments that can capture various types of contexts of inhabitants of the environment, such as their locations, activities, vital signs, and environmental measures. Such context information is useful in a variety of applications, for example to manage health information to promote independent living in “aging-in-place” scenarios. In reality, both sensed and interpreted contexts are often ambiguous, leading to potentially dangerous decisions if not properly handled. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this chapter, the authors discuss a resource optimized quality assured ontology-driven context mediation framework for resource constrained sensor networks based on efficient context-aware data fusion and information theoretic sensor parameter selection for optimal state estimation. It has the ability to represent contexts according to the applications’ ontology and easily composable ontological rules to mediate ambiguous contexts.

scholarly journals A Novel Framework of an IOT-Blockchain-Based Intelligent System

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Aliaa M. Alabdali
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Security ◽  
Intelligent System ◽  
Security And Privacy ◽  
Self Monitoring ◽  
Smart Systems ◽  
Blockchain Technology ◽  
Iot Devices ◽  
Smart Mobile

With the growing need of technology into varied fields, dependency is getting directly proportional to ease of user-friendly smart systems. The advent of artificial intelligence in these smart systems has made our lives easier. Several Internet of Things- (IoT-) based smart refrigerator systems are emerging which support self-monitoring of contents, but the systems lack to achieve the optimized run time and data security. Therefore, in this research, a novel design is implemented with the hardware level of integration of equipment with a more sophisticated software design. It was attempted to design a new smart refrigerator system, which has the capability of automatic self-checking and self-purchasing, by integrating smart mobile device applications and IoT technology with minimal human intervention carried through Blynk application on a mobile phone. The proposed system automatically makes periodic checks and then waits for the owner’s decision to either allow the system to repurchase these products via Ethernet or reject the purchase option. The paper also discussed the machine level integration with artificial intelligence by considering several features and implemented state-of-the-art machine learning classifiers to give automatic decisions. The blockchain technology is cohesively combined to store and propagate data for the sake of data security and privacy concerns. In combination with IoT devices, machine learning, and blockchain technology, the proposed model of the paper can provide a more comprehensive and valuable feedback-driven system. The experiments have been performed and evaluated using several information retrieval metrics using visualization tools. Therefore, our proposed intelligent system will save effort, time, and money which helps us to have an easier, faster, and healthier lifestyle.

Research on Proactive Services Based on Context Rules in Virtual Environment

2014 ◽  
Vol 10 (02) ◽  
pp. 177-185
Author(s):  
Ming-Zhi Chen ◽  
Bo-Gang Lin ◽  
Shui-Li Chen
Keyword(s):  
Virtual Environment ◽  
Pervasive Computing ◽  
Context Information ◽  
Context Aware ◽  
Decision Tree Algorithm ◽  
Context Aware Computing ◽  
Ontology Language ◽  
Research Findings ◽  
Machine Interface ◽  
Application Requirements

The issues of Human–Machine Interface (HMI) of Virtual Environment (VE) are discussed in view of users' potential application requirements in VE. The Human-centered HMI containing rich context information is proposed by taking the advantage of the abundant research findings of artificial intelligence and pervasive computing. The technology of context-aware computing is introduced in this study for providing initiative services mode as well. First, in view of the characteristics of VE, the Web Ontology Language (OWL) is adopted to model the context information. Second, the modified ID3 decision-tree algorithm is applied to automatically generate the context rules of VE. Third, the polymorphic proactive services model based on context rules is designed. Finally, an example is given to illustrate how to apply context rule-inference to realize proactive services. The experiment demonstrates the correctness and effectiveness of the above mentioned algorithm and model.

Personalized Mobile Catering Recommender System Based on Context Ontology Model and Rule Inference

2013 ◽  
Vol 717 ◽  
pp. 708-713 ◽  
Author(s):  
Dan Xiang Ai ◽  
Hui Zuo ◽  
Jun Yang
Keyword(s):  
Pervasive Computing ◽  
Recommender System ◽  
Personalized Recommendation ◽  
Context Aware ◽  
Rule Generation ◽  
Context Model ◽  
Ontology Modeling ◽  
Ontology Model ◽  
Smart Mobile ◽  
Rule Inference

With the development of smart mobile terminals and pervasive computing, mobile recommender systems are proposed to realize context-aware personalized recommendation services. A context model plays a key role in a mobile recommender. We discussed the context ontology modeling approach specific for mobile recommendation, and developed a two-level context model including a upper ontology and a domain ontology. We also designed a personalized mobile catering recommender system based on the context ontology model and rule inference. The framework of the system is depicted. And the process of rule generation and rule inference based on the context ontologies is demonstrated.

scholarly journals SETUCOM: Secure and Trustworthy Context Management for Context-Aware Security and Privacy in the Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Tidiane Sylla ◽  
Mohamed Aymen Chalouf ◽  
Francine Krief ◽  
Karim Samaké
Keyword(s):  
Pervasive Computing ◽  
Smart City ◽  
Information Exchange ◽  
Trust Management ◽  
Security And Privacy ◽  
Context Aware ◽  
Service Architecture ◽  
Context Management ◽  
Iot Devices ◽  
The Internet Of Things

IoT technologies facilitate the development and the improvement of pervasive computing by enabling effective context-awareness features. These features enable the IoT applications to detect the user’s situation and adapt their behavior. They also enable context-aware security and privacy, which consist in adapting security and privacy mechanisms’ deployment to the user’s situation. Research studies on context-aware security and privacy focus on security and privacy mechanisms’ implementation but do not consider the secure and trustworthy context management. In this paper, we introduce a new secure and trustworthy context management system for context-aware security and privacy in the smart city: “SETUCOM.” SETUCOM is the implementation of the DTM (Device Trust Management) module of the CASPaaS (Context-Aware Security and Privacy as a Service) architecture. It secures context information exchange by using a lightweight hybrid encryption system adapted to IoT devices and manages trust through artificial intelligence techniques such as Bayesian networks and fuzzy logic. A detailed description of the proposed system is provided, and its main performances are evaluated. The results prove SETUCOM feasibility in context-aware security and privacy for the smart city.

Resolving and Mediating Ambiguous Contexts in Pervasive Environments

2012 ◽  
pp. 630-654
Author(s):  
Nirmalya Roy ◽  
Sajal K. Das ◽  
Christine Julien
Keyword(s):  
State Estimation ◽  
Pervasive Computing ◽  
Independent Living ◽  
Vital Signs ◽  
Context Information ◽  
Context Aware ◽  
Information Theoretic ◽  
Significant Challenge ◽  
Environmental Measures ◽  
Optimal State Estimation

Pervasive computing applications envision sensor rich computing and networking environments that can capture various types of contexts of inhabitants of the environment, such as their locations, activities, vital signs, and environmental measures. Such context information is useful in a variety of applications, for example to manage health information to promote independent living in “aging-in-place” scenarios. In reality, both sensed and interpreted contexts are often ambiguous, leading to potentially dangerous decisions if not properly handled. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this chapter, the authors discuss a resource optimized quality assured ontology-driven context mediation framework for resource constrained sensor networks based on efficient context-aware data fusion and information theoretic sensor parameter selection for optimal state estimation. It has the ability to represent contexts according to the applications’ ontology and easily composable ontological rules to mediate ambiguous contexts.

Meta Model Context Based Space for Ubiquitous Computing

2015 ◽  
Vol 7 (2) ◽  
pp. 51-66
Author(s):  
Mohammed Fethi Khalfi ◽  
Sidi Mohamed Benslimane
Keyword(s):  
Pervasive Computing ◽  
Situation Awareness ◽  
Context Awareness ◽  
Real Life ◽  
Context Aware ◽  
Context Modeling ◽  
Context Model ◽  
Meta Model ◽  
Domain Specific ◽  
Model Context

Pervasive computing is a paradigm that focuses on the availability of computer resources anytime anywhere for any application and supports integration of computing services into everyday life. Context awareness is the core feature of pervasive computing. High-level context awareness can be enhanced by situation awareness that represents the ability to detect and reason about the real-life situations. In this paper, in order to deal with the problem in context-aware modeling in pervasive computing environments, the authors present a comprehensive and integrated approach for context modeling. They first propose a Meta model context based on ontology for Pervasive Computing aiming firstly to overcome the limitations of the existing ontologies, and secondly extend its capabilities by adding new environmental aspects. They divide the context model into Meta Ontology level and Domain-specific Ontology level according to the abstraction hierarchy. The Meta Ontology is the high abstract level which extracting the basic elements of the context knowledge. The Domain-specific Ontology is the lower abstract lever which focusing on different domains knowledge, directed by the Meta Ontology. The advantage is that it can provide a flexible modeling mechanism for multiple applications of context-aware pervasive computing. A case study of HealthCare domain is given to illustrate the practicality of the authors' Model.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

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