An Ontology-based Context-aware IoT Framework for Smart Surveillance
10 Oct 2018-pp 69
TL;DR: Continuous video stream of data captured by CCTV cameras can be processed on the fly to give real-time alerts to concerned authorities and these alerts can be disseminated using e-mail, text messaging, on-screen alerts and alarms.
Abstract: In this paper, we have proposed an ontology-based context-aware framework for providing intelligent services such as smart surveillance, which employ IoT technologies to ensure better quality of life in a smart city. An IoT network such as a smart surveillance system combines the working of Closed-circuit television (CCTV) cameras and various sensors to perform real-time computation for identifying threats and critical situations with the help of valuable context information. This information is perceptual in nature and needs to be converted into higher-level abstractions that can further be used for reasoning to recognize situations. Semantic abstractions for perceptual inputs are possible with the use of a multimedia ontology encoded using Multimedia Web Ontology Language (MOWL) that helps to define concepts, properties and structure of a possible environment. MOWL also allows for a dynamic modeling of real-time situations by employing Dynamic Bayesian networks (DBN), which suits the requirements of a intelligent IoT system. In this paper, we show the application of this framework in a smart surveillance system. Surveillance is enhanced by not only helping to analyze past events, but by predicting dangerous situations for which preventive actions can be taken. In our proposed approach, continuous video stream of data captured by CCTV cameras can be processed on the fly to give real-time alerts to concerned authorities. These alerts can be disseminated using e-mail, text messaging, on-screen alerts and alarms.
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TL;DR: A surveillance system, named as Multi-Level Video Security (MuLViS) for privacy-protected cameras, which can be made General Data Protection Regulation (GDPR) compliant, ensuring that lawful data access respects individuals’ privacy rights.
Abstract: Video Surveillance (VS) systems are commonly deployed for real-time abnormal event detection and autonomous video analytics. Video captured by surveillance cameras in real-time often contains identifiable personal information, which must be privacy protected, sometimes along with the locations of the surveillance and other sensitive information. Within the Surveillance System, these videos are processed and stored on a variety of devices. The processing and storage heterogeneity of those devices, together with their network requirements, make real-time surveillance systems complex and challenging. This paper proposes a surveillance system, named as Multi-Level Video Security (MuLViS) for privacy-protected cameras. Firstly, a Smart Surveillance Security Ontology (SSSO) is integrated within the MuLViS, with the aim of autonomously selecting the privacy level matching the operating device’s hardware specifications and network capabilities. Overall, along with its device-specific security, the system leads to relatively fast indexing and retrieval of surveillance video. Secondly, information within the videos are protected at the times of capturing, streaming, and storage by means of differing encryption levels. An extensive evaluation of the system, through visual inspection and statistical analysis of experimental video results, such as by the Encryption Space Ratio (ESR), has demonstrated the aptness of the security level assignments. The system is suitable for surveillance footage protection, which can be made General Data Protection Regulation (GDPR) compliant, ensuring that lawful data access respects individuals’ privacy rights.
14 citations
Cites background from "An Ontology-based Context-aware IoT..."
...also presented [23] an ontologybased system for situation tracking in a smart surveillance environment using Dynamic Bayesian Networks (DBNs)....
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01 Jan 2021
TL;DR: In this article, the authors discuss the emergence of context-aware computing and some use cases of contextaware IoT applications, focusing on some crucial and open problems in the practical implementation of context aware IoT applications.
Abstract: The new Internet of Things (IoT) technology has the potential to generate breakthrough opportunities in real-life applications. The merger of IoT with other technologies like context-aware computing, big data, artificial intelligence, machine learning, etc. will give rise to new services that will improve the quality of life. The article discusses the emergence of context-aware computing and some use cases of context-aware IoT applications. The study presented in this article focuses on some crucial and open problems in the practical implementation of context-aware IoT applications.
10 citations
01 Jan 2020
TL;DR: The focus of this paper is to address the challenge of adding value to raw sensor data in ITS with a context—aware model and the effectiveness of context-aware in ITS is illustrated by discussing different real time scenarios.
Abstract: IoT-based transportation system is getting smarter and smarter to provide quick, safe and reliable services to the user. This smarter transportation system is called Intelligent Transportation System (ITS). ITS incorporates wired and wireless communication, electronic technologies, computational technologies, cloud platforms, GPS and sensor to assist user to be informed on road safety and make safer, coordinated, comfort and ‘smarter’ use of transportation medium. ITS is an advanced IOT application that connects huge number of objects to communicate with each other. As number of objects connected to ITS application increases, we face with a challenge of adding value to raw sensor data. The focus of this paper is to address this challenge with a context—aware model. Also, the effectiveness of context—aware in ITS is illustrated by discussing different real time scenarios.
9 citations
01 Jan 2021
TL;DR: In this article, the authors reviewed the current state of the art in the context of IoT application requirements and related cellular communication technologies and incorporated use cases with a case study on 5G enabled IoT.
Abstract: The Internet of Things (IoT) is quickly spreading, arriving at a large number of various areas, including home automation, personal health care, environmental monitoring, smart mobility, smart vehicles, and Industry 4.0. It has the potential to provide unified, efficient machine to human and machine to machine (M2M) communication and connectivity. The communication needed among many heterogeneous devices demands high data rates, low latency, and high connectivity for designing special applications to assist the IoT. Also, current cellular technology standards available for mobile are not suitable for IoT devices belonging to a low power wide area (LPWA) technology. 5G wireless technologies have become the most challenging and exciting topic in IoT as they will be game-changers in the future generation. Though, there is no single technology of 5G that can fulfill the requirements of IoT. The aggregation of various communication technologies could help to achieve the determined goals of 5G enabled IoT. The key enabling technologies such as Cloud Computing, Heterogeneous Network (HetNet), Device to Device (D2D) Communication, and Software Defined Networking (SDN) is presented in this chapter which has become essential technologies to achieve better efficiency. The current state of the art in the context of IoT application requirements and related cellular communication technologies is reviewed. The comparative analysis of various communication technologies is presented along with emerging IoT applications. We have also incorporated use cases with a case study on 5G enabled IoT. At last, the challenges and future research trends for the deployment of various IoT services and applications are discussed.
7 citations
24 Jul 2021
TL;DR: In this article, the authors present the results of investigating existing categories of human computer interaction (HCI) to make sense of these interactions and the inherent heterogeneity they carry in cyber physical-embedded environments.
Abstract: When looking at the way in which humans choose to participate in and interact with cyber physical-embedded environments such as Internet of Things (IoT), one could assume that such environments are permeated with ‘ad hoc’, ‘heterogeneous’ and ‘dynamic’ interactions in them. Existing literature on human to computer interactions, their types and definitions fail to provide a concrete understanding of these dimensions in cyber physical-embedded environments. Therefore, this paper presents the results of investigating existing categories of Human Computer Interaction (HCI) to make sense of these interactions and the inherent heterogeneity they carry. An integrative literature review using the PRISMA model to locate, select, and include 120 relevant articles has been carried out. The main finding of this review is a semantic classification of possible Human-to-Environment Interactions (HEI). The classification plays an important role as a starting point when looking at the current and future offerings of the HEI in the IoT. The classification also serves input as formal knowledge representations, such as Ontology Web Language (OWL) ontologies, which could assist in creating explicit representations of interaction.
1 citations
References
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TL;DR: This paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
Abstract: The Internet of Things (IoT) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous end systems, while providing open access to selected subsets of data for the development of a plethora of digital services. Building a general architecture for the IoT is hence a very complex task, mainly because of the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we focus specifically to an urban IoT system that, while still being quite a broad category, are characterized by their specific application domain. Urban IoTs, in fact, are designed to support the Smart City vision, which aims at exploiting the most advanced communication technologies to support added-value services for the administration of the city and for the citizens. This paper hence provides a comprehensive survey of the enabling technologies, protocols, and architecture for an urban IoT. Furthermore, the paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
4,335 citations
"An Ontology-based Context-aware IoT..." refers background in this paper
...al in [10] presented a comprehensive survey of the enabling technologies, protocols, and architecture for an urban IoT....
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Journal Article•
106 citations
02 Sep 2009
TL;DR: An ontology for representing the prior knowledge related to video event analysis is proposed, specialized for the Underground video-surveillance domain showing some results that demonstrate the usability and effectiveness of the proposed ontology.
Abstract: In this paper, we propose an ontology for representing the prior knowledge related to video event analysis. It is composed of two types of knowledge related to the application domain and the analysis system. Domain knowledge involves all the high level semantic concepts in the context of each examined domain (objects, events, context...) whilst system knowledge involves the capabilities of the analysis system (algorithms, reactions to events...). The proposed ontology has been structured in two parts: the basic ontology (composed of the basic concepts and their specializations) and the domain-specific extensions. Additionally, a video analysis framework based on the proposed ontology is defined for the analysis of different application domains showing the potential use of the proposed ontology. In order to show the real applicability of the proposed ontology, it is specialized for the Underground video-surveillance domain showing some results that demonstrate the usability and effectiveness of the proposed ontology.
53 citations
"An Ontology-based Context-aware IoT..." refers background in this paper
...The authors in [8] integrated different types of knowledge in an ontology for detecting the objects and events in a video scene....
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06 Jun 2011
TL;DR: Concept Reply context awareness solution is described, based on a hybrid framework that integrates a semantic reasoning module and multiple processing agents for specialized / optimized processing tasks.
Abstract: The Internet of Things (IoT) paradigm, extending the computing and communicating capabilities to virtually every object, raises many new challenges to IoT-enabling systems. At the middleware layer, a context aware adaptive component has to fit the requirements and constraints for different applications, deal with heterogeneous data, be scalable to large scenarios and to resource constrained devices, and manage interoperability. This paper describes Concept Reply context awareness solution, based on a hybrid framework that integrates a semantic reasoning module and multiple processing agents for specialized / optimized processing tasks. Combining different reasoning approaches and adopting proper design choices we developed an extensible and configurable module. We show the advantages of this flexible approach in two case studies that benefit from two different tailorings of the reasoning framework.
26 citations
"An Ontology-based Context-aware IoT..." refers methods in this paper
...Ontology based frameworks in IoT applications have been used in [1, 4]....
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TL;DR: An ontology-based data preprocessing scheme, which is composed of two main phases: (i) session identification and (ii) error detection, which can find out not only relationships between sensor streams but also temporal dynamics of a data stream.
Abstract: ? A number of heterogeneous sensor streams have been efficiently pre-processed for better services. Many studies have tried to employ data mining methods to discover useful patterns and knowledge from data streams on sensor networks. However, it is difficult to apply such data mining methods to the sensor streams intermixed from heterogeneous sensor networks. In this paper, to improve the performance of conventional data mining methods, we propose an ontology-based data preprocessing scheme, which is composed of two main phases: (i) session identification and (ii) error detection. The ontology can provide and describe semantics of data measured by each sensor. Thus, by comparing the semantics, we can find out not only relationships between sensor streams but also temporal dynamics of a data stream. To evaluate the proposed method, we have collected sensor streams from in our building during 30days. By using two well-known data mining methods (i.e., co-occurrence pattern and sequential pattern), the results from raw sensor streams and ones from sensor streams with preprocessing were compared with respect to two measurements recall and precision.
18 citations
Additional excerpts
...Jung [3] proposed an ontology-based data pre-processing scheme...
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