Context-Aware Pervasive Services for Smart Cities

2011 ◽  
pp. 1-16 ◽  
Author(s):  
René Meier ◽  
Deirdre Lee
Keyword(s):  
Intelligent Transportation Systems ◽  
Data Model ◽  
Programming Model ◽  
Smart Cities ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Transportation Systems ◽  
Context Aware ◽  
Transportation Services ◽  
Context Modelling

Smart environments support the activities of individuals by enabling context-aware access to pervasive information and services. This article presents the iTransIT framework for building such context-aware pervasive services in Smart Cities. The iTransIT framework provides an architecture for conceptually integrating the independent systems underlying Smart Cities and a data model for capturing the contextual information generated by these systems. The data model is based on a hybrid approach to context-modelling that incorporates the management and communication benefits of traditional object-based context modelling with the semantic and inference advantages of ontology-based context modelling. The iTransIT framework furthermore supports a programming model designed to provide a standardised way to access and correlate contextual information from systems and ultimately, to build context-aware pervasive services for Smart Cities. The framework has been assessed based on a prototypical realisation of an architecture for integrating diverse intelligent transportation systems in Dublin and by building context-aware pervasive transportation services for urban journey planning and for visualising traffic congestion.

Context-Aware Pervasive Services for Smart Cities

2012 ◽  
pp. 880-896
Author(s):  
René Meier ◽  
Deirdre Lee
Keyword(s):  
Intelligent Transportation Systems ◽  
Data Model ◽  
Programming Model ◽  
Smart Cities ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Transportation Systems ◽  
Context Aware ◽  
Transportation Services ◽  
Context Modelling

Smart environments support the activities of individuals by enabling context-aware access to pervasive information and services. This article presents the iTransIT framework for building such context-aware pervasive services in Smart Cities. The iTransIT framework provides an architecture for conceptually integrating the independent systems underlying Smart Cities and a data model for capturing the contextual information generated by these systems. The data model is based on a hybrid approach to context-modelling that incorporates the management and communication benefits of traditional object-based context modelling with the semantic and inference advantages of ontology-based context modelling. The iTransIT framework furthermore supports a programming model designed to provide a standardised way to access and correlate contextual information from systems and ultimately, to build context-aware pervasive services for Smart Cities. The framework has been assessed based on a prototypical realisation of an architecture for integrating diverse intelligent transportation systems in Dublin and by building context-aware pervasive transportation services for urban journey planning and for visualising traffic congestion.

Context-Aware Services for Ambient Environments

2010 ◽  
pp. 488-501
Author(s):  
René Meier ◽  
Deirdre Lee
Keyword(s):  
Intelligent Transportation Systems ◽  
Data Model ◽  
Large Scale ◽  
Programming Model ◽  
Hybrid Approach ◽  
Transportation Systems ◽  
Context Aware ◽  
Context Modeling ◽  
Transportation Services ◽  
Ambient Services

This article presents the iTransIT framework for building context-aware pervasive services in large-scale ambient environments. The iTransIT framework provides an architecture for conceptually integrating the independent systems underlying an ambient environment and a data model for capturing the contextual information generated by these systems. The data model is based on a hybrid approach to context-modeling that incorporates the management and communication benefits of traditional object-based-context modeling with the semantic and inference advantages of ontology-based context modeling. The iTransIT framework furthermore supports a programming model designed to provide a standardized way to access and correlate information from systems and their devices based on context and ultimately, to build context-aware ambient services. The framework has been assessed based on a prototypical realization of an architecture for integrating diverse intelligent transportation systems in Dublin and by building context-aware ambient transportation services for urban journey planning and for visualizing traffic congestion.

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

A Hybrid Context Aware Recommender System with Combined Pre and Post-Filter Approach

2019 ◽  
Vol 10 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Mugdha Sharma ◽  
Laxmi Ahuja ◽  
Vinay Kumar
Keyword(s):  
Performance Improvement ◽  
Recommender System ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Experimental Setup ◽  
Context Aware ◽  
Contextual Modeling ◽  
Filter Approach ◽  
Post Filter

The domain of context aware recommender approaches has made substantial advancement over the last decade, but many applications still do not include contextual information while providing recommendations. Contextual information is crucial for various application areas and should not be ignored. There are generally three algorithms which can be used to include context and those are: pre-filter approach, post-filter approach, and contextual modeling. Each of the algorithms has their own drawbacks. The proposed approach modifies the post filter approach to rectify its shortcomings and combines it with the pre-filter approach based on the importance of contextual attribute provided by the user. The results of experimental setup also demonstrate that the proposed system improves the precision and ranking of the recommendations provided to user. With the help of this hybrid approach, the proposed system eliminates the problem of sparsity which is present in the pre-filter algorithm, and has performance improvement over the traditional post-filter approach.

scholarly journals A Survey of Context-Aware Messaging-Addressing for Sustainable Internet of Things (IoT)

2020 ◽  
Vol 12 (10) ◽  
pp. 4105
Author(s):  
Alaa Omran Almagrabi ◽  
Yasser D. Al-Otaibi
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Contextual Information ◽  
Spatial Models ◽  
Context Aware ◽  
Engineering Technology ◽  
Smart Transportation ◽  
Context Aware Computing ◽  
Iot Applications ◽  
Smart Healthcare

Nowadays, communication engineering technology is merging with the Internet of Things (IoT), which consists of numerous connected devices (referred to as things) around the world. Many researchers have shown significant growth of sensor deployments for multiple smart engineering technologies, such as smart-healthcare, smart-industries, smart-cities, and smart-transportation, etc. In such intelligent engineering technologies, sensors continuously generate a bunch of messages in the network. To enhance the value of the data in the messages, we must know the actuality of the data embedded inside the messages. For this purpose, the contextual information of the data creates a vital challenge. Recently, context-aware computing has emerged to be fruitful in dealing with sensor information. In the ubiquitous computing domain, location is commonly considered one of the most essential sources of context. However, whenever users or applications are concerned with objects, and their site or spatial relationships, location models or spatial models are necessary to form a model of the environment. This paper investigates the area of context-aware messaging and addressing services in diverse IoT applications. The paper examines the notion of context and the use of context within the data exchanged by the sensors in an IoT application for messaging and addressing purposes. Based on the importance and need for context of the information, we identify three critical categories of new IoT applications for context-aware messaging and addressing services: emergency applications, applications for guiding and reminding, and social networking applications. For this purpose, a representative range of systems is reviewed according to the application type, the technology being used, their architecture, the context information, and the services they provide. This survey assists the work of defining an approach for context-aware messaging services domain by discovering the area of context-aware messaging.

scholarly journals Eco-Efficient Mobility in Smart City Scenarios

2020 ◽  
Vol 12 (20) ◽  
pp. 8443
Author(s):  
Ramon Sanchez-Iborra ◽  
Luis Bernal-Escobedo ◽  
José Santa
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart City ◽  
Smart Cities ◽  
Low Cost ◽  
Transportation Systems ◽  
Area Network ◽  
Wide Area Network ◽  
Fully Integrated ◽  
Personal Mobility ◽  
Traffic Efficiency

Cooperative-Intelligent Transportation Systems (C-ITS) have brought a technological revolution, especially for ground vehicles, in terms of road safety, traffic efficiency, as well as in the experience of drivers and passengers. So far, these advances have been focused on traditional transportation means, leaving aside the new generation of personal vehicles that are nowadays flooding our streets. Together with bicycles and motorcycles, personal mobility devices such as segways or electric scooters are firm sustainable alternatives that represent the future to achieve eco-friendly personal mobility in urban settings. In a near future, smart cities will become hyper-connected spaces where these vehicles should be integrated within the underlying C-ITS ecosystem. In this paper, we provide a wide overview of the opportunities and challenges related to this necessary integration as well as the communication solutions that are already in the market to provide these moving devices with low-cost and efficient connectivity. We also present an On-Board Unit (OBU) prototype with different communication options based on the Low Power Wide Area Network (LPWAN) paradigm and several sensors to gather environmental information to facilitate eco-efficiency services. As the attained results suggest, this module allows personal vehicles to be fully integrated in smart city environments, presenting the possibilities of LoRaWAN and Narrow Band-Internet of Things (NB-IoT) communication technologies to provide vehicle connectivity and enable mobile urban sensing.

scholarly journals Improving Driver Assistance in Intelligent Transportation Systems: An Agent-Based Evidential Reasoning Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
M. Benalla ◽  
B. Achchab ◽  
H. Hrimech
Keyword(s):  
Intelligent Transportation Systems ◽  
Contextual Information ◽  
Sensory Information ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Evidential Reasoning ◽  
Traffic Information ◽  
Driver Assistance ◽  
Agent Based ◽  
Reasoning System

Providing accurate real-time traffic information is an inherent problem for intelligent transportation systems (ITS). In order to improve the knowledge base of advanced driver assistance systems (ADAS), ITS are strongly concerned with data fusion techniques of all kinds of sensors deployed over the traffic network. Driver assistance is devoid of a comprehensive evidential reasoning system on contextual information, more specifically when a combination involves inside and outside sensory information of the driving environment. In this paper, we propose a novel agent-based evidential reasoning system using contextual information. Based on a series of information handling techniques, specifically, the belief functions theory and heuristic inference operations to achieve a consensus about daily driving activity in automatically inferring. That is quite different from other existing proposals, as it deals jointly with the driving behavior and the driving environment conditions. A case study including various scenarios of experiments is introduced to estimate behavioral information based on synthetic data for prediction, prescription, and policy analysis. Our experiments show promising, thought-provoking results encouraging further research.

scholarly journals Blockchain for the Internet of Vehicles: A Decentralized IoT Solution for Vehicles Communication Using Ethereum

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3928 ◽  
Author(s):  
Rateb Jabbar ◽  
Mohamed Kharbeche ◽  
Khalifa Al-Khalifa ◽  
Moez Krichen ◽  
Kamel Barkaoui
Keyword(s):  
Intelligent Transportation Systems ◽  
Secure Communication ◽  
Data Exchange ◽  
Smart Cities ◽  
Transportation Systems ◽  
Smart Devices ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Computing Platform ◽  
Blockchain Technology

The concept of smart cities has become prominent in modern metropolises due to the emergence of embedded and connected smart devices, systems, and technologies. They have enabled the connection of every “thing” to the Internet. Therefore, in the upcoming era of the Internet of Things, the Internet of Vehicles (IoV) will play a crucial role in newly developed smart cities. The IoV has the potential to solve various traffic and road safety problems effectively in order to prevent fatal crashes. However, a particular challenge in the IoV, especially in Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, is to ensure fast, secure transmission and accurate recording of the data. In order to overcome these challenges, this work is adapting Blockchain technology for real time application (RTA) to solve Vehicle-to-Everything (V2X) communications problems. Therefore, the main novelty of this paper is to develop a Blockchain-based IoT system in order to establish secure communication and create an entirely decentralized cloud computing platform. Moreover, the authors qualitatively tested the performance and resilience of the proposed system against common security attacks. Computational tests showed that the proposed solution solved the main challenges of Vehicle-to-X (V2X) communications such as security, centralization, and lack of privacy. In addition, it guaranteed an easy data exchange between different actors of intelligent transportation systems.

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