Mr Tarek Elsaleh

Research Fellow

Email:

Further information

Publications

Journal articles

  • Enshaeifar S , Barnaghi P , Skillman SM, Markides A , Elsaleh T , Acton T, Nilforooshan R, Rostill H. (2017) 'Internet of Things for Dementia Care'. IEEE Internet Computing,
    [ Status: Accepted ]

    Abstract

    In this paper we discuss a technical design and an ongoing trial that is being conducted in the UK, called Technology Integrated Health Management (TIHM). TIHM uses Internet of Things (IoT) enabled solutions provided by various companies in a collaborative project. The IoT devices and solutions are integrated in a common platform that supports interoperable and open standards. A set of machine learning and data analytics algorithms generate notifications regarding the well-being of the patients. The information is monitored around the clock by a group of healthcare practitioners who take appropriate decisions according to the collected data and generated notifications. In this paper we discuss the design principles and the lessons that we have learned by co-designing this system with patients, their carers, clinicians, and also our industry partners. We discuss the technical design of TIHM and explain why user-centred and human-experience should be an integral part of the technological design.

  • Bermudez-Edo M, Elsaleh T , Barnaghi P , Taylor K. (2017) 'IoT-Lite: A Lightweight Semantic Model for the Internet of Things and its Use with Dynamic Semantics'. Personal and Ubiquitous Computing,

    Abstract

    Over the past few years the semantics community has developed several ontologies to describe concepts and relationships for Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time and therefore they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis, and assess IoT-Lite against another solution in terms of round trip time (RTT) performance for query-response times. We have linked IoTLite with Stream Annotation Ontology (SAO), to allow queries over stream data annotations and we have also added dynamic semantics in the form of MathML annotations to IoT-Lite. Dynamic semantics allows the annotation of spatio-temporal values, reducing storage requirements and therefore the response time for queries. Dynamic semantics stores mathematical formulas to recover estimated values when actual values are missing.

  • Lanza J, Sanchez L, Gomez D, Elsaleh T, Steinke R, Cirillo F. (2016) 'A Proof-of-Concept for Semantically Interoperable Federation of IoT Experimentation Facilities'. SENSORS, 16 (7) Article number ARTN 1006
  • De S, Elsaleh T, Barnaghi P, Meissner S. (2012) 'An Internet of Things Platform for Real-World and Digital Objects'. Scalable Computing: Practice and Experience, 13 (1), pp. 45-57.

    Abstract

    The vision of the Internet of Things (IoT) relies on the provisioning of real-world services, which are provided by smart objects that are directly related to the physical world. A structured, machine-processible approach to provision such real-world services is needed to make heterogeneous physical objects accessible on a large scale and to integrate them with the digital world. The incorporation of observation and measurement data obtained from the physical objects with the Web data, using information processing and knowledge engineering methods, enables the construction of ”intelligent and interconnected things”. The current research mostly focuses on the communication and networking aspects between the devices that are used for sensing amd measurement of the real world objects. There is, however, relatively less effort concentrated on creating dynamic infrastructures to support integration of the data into the Web and provide unified access to such data on service and application levels. This paper presents a semantic modelling and linked data approach to create an information framework for IoT. The paper describes a platform to publish instances of the IoT related resources and entities and to link them to existing resources on the Web. The developed platform supports publication of extensible and interoperable descriptions in the form of linked data.

Conference papers

  • Ahrabian A , Elsaleh T , Fathy Y, Barnaghi P . (2017) 'Detecting Changes in the Variance of Multi-Sensory Accelerometer Data Using MCMC'. IEEE Proceedings of IEEE Sensors 2017, Glasgow, Scotland: IEEE Sensors 2017
    [ Status: Accepted ]

    Abstract

    An important field in exploratory sensory data analysis is the segmentation of time-series data to identify activities of interest. In this work, we analyse the performance of univariate and multi-sensor Bayesian change detection algorithms in segmenting accelerometer data. In particular, we provide theoretical analysis and also performance evaluation on synthetic data and real-world data. The results illustrate the advantages of using multi-sensory variance change detection in the segmentation of dynamic data (e.g. accelerometer data).

  • Carrez FD, Elsaleh T , Gomez D, Sanchez L, Lanza J, Grace P. (2017) 'A reference architecture for federating IoT infrastructures supporting semantic interoperability'. IEEE European Conference on Networks and Communications 2017, Oulu, Finland: 2017 European Conference on Networks and Communications (EuCNC)

    Abstract

    : The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming vertical silos. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potential of smart applications in terms of size, scope and targeted business context. This paper describes the system architecture for the FIESTA-IoT platform, whose main aim is to federate a large number of testbeds across the planet, in order to offer experimenters the unique experience of dealing with a large number of semantically interoperable data sources. This system architecture was developed by following the Architectural Reference Model (ARM) methodology promoted by the IoT-A project (FP7 “light house” project on Architecture for the Internet of Things). Through this process, the FIESTAIoT architecture is composed of a set of Views that deals with a “logical” functional decomposition (Functional View, FV) and data structuring and annotation, data flows and inter-functional component interactions (Information View, IV).

  • Agarwal R, Gomez Fernandez D, Elsaleh T , Gyrard A, Lanza J, Sanchez L, Georgantas N, Issarny V. (2017) 'Unified IoT ontology to enable interoperability and federation of testbeds'. IEEE 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), Reston, VA, USA: 2016 3rd IEEE World Forum on Internet of Things, pp. pp. 70-75.

    Abstract

    After a thorough analysis of existing Internet of Things (IoT) related ontologies, in this paper we propose a solution that aims to achieve semantic interoperability among heterogeneous testbeds. Our model is framed within the EU H2020's FIESTA-IoT project, that aims to seamlessly support the federation of testbeds through the usage of semantic-based technologies. Our proposed model (ontology) takes inspiration from the well-known Noy et al. methodology for reusing and interconnecting existing ontologies. To build the ontology, we leverage a number of core concepts from various mainstream ontologies and taxonomies, such as Semantic Sensor Network (SSN), M3-lite (a lite version of M3 and also an outcome of this study), WGS84, IoT-lite, Time, and DUL. In addition, we also introduce a set of tools that aims to help external testbeds adapt their respective datasets to the developed ontology.

  • Bermudez-Edo M, Elsaleh T , Barnaghi P , Taylor K. (2017) 'IoT-Lite: A Lightweight Semantic Model for the Internet of Things'. IEEE Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), 2016 Intl IEEE Conferences, Toulouse, France: 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, pp. pp. 90-97.

    Abstract

    Over the past few years the semantics community has developed ontologies to describe concepts and relationships between different entities in various application domains, including Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time and therefore they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis, and assess IoT-Lite against another solution in terms of round time trip (RTT) performance for query-response times.

  • Ramparany F, Marquez FG, Soriano J, Elsaleh T. (2015) 'Handling smart environment devices, data and services at the semantic level with the FI-WARE core platform'. Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014, , pp. 14-20.

    Abstract

    © 2014 IEEE.The development of IoT (Internet of Things) applications poses a number of scientific and technological challenges which stem from the characteristics of the IoT domain itself. These include the huge and increasing number of connected entities (devices, physical objects, people.,) populating the physical environment, the variety of their types which leads to heterogeneity of the data produced or consumed by those connected entities. In this paper we argue that semantic modeling takes up many of these challenges and explain how the core platform developed by the FI-WARE project supports IoT application developers. After a short introduction of the characteristics and requirements of IoT applications we identify the contribution of semantic technologies to address some of them. We describe the FI-WARE platform enablers which support these technologies and illustrate through a real application how these enablers help developers satisfy these requirements.

  • Kolozali Ş, Elsaleh T, Barnaghi P. (2014) 'A validation tool for the W3C SSN ontology based sensory semantic knowledge'. CEUR Workshop Proceedings, 1401, pp. 83-88.

    Abstract

    This paper describes an ontology validation tool that is designed for the W3C Semantic Sensor Networks Ontology (W3C SSN). The tool allows ontologies and linked-data descriptions to be validated against the concepts and properties used in the W3C SSN model. It generates validation reports and collects statistics regarding the most commonly used terms and concepts within the ontologies. An online version of the tool is available at: (http://iot.ee.Surrey.ac.uk/SSNValidation). This tool can be used as a checking and validation service for new ontology developments in the IoT domain. It can also be used to give feedback to W3C SSN and other similar ontology developers regarding the most commonly used concepts and properties from the reference ontology and this information can be used to create core ontologies that have higher level interoperability across different systems and various application domains.

  • Elsaleh T, Gluhak A, Moessner K. (2011) 'Service continuity for subscribers of the mobile real world Internet'. IEEE International Conference on Communications,

    Abstract

    The Real World Internet or the Web of Things has brought an approach to integrate wireless sensor devices in a manner that is natural to the Web, where sensors are exposed as addressable web resources like any other web resource. Although there is still a clear deficiency with regards to managing the mobility of the sensor devices in this approach, and how it affects the service and the users interacting with it. The work presented here addresses this issue and aims to provide an approach towards maintaining service continuity of migrating sensor devices in a framework that builds upon the concept of the 'Web of Things'. © 2011 IEEE.

Software

  • Ganz F, Enshaeifar S, Puschmann D, Ahrabian A, Elsaleh T. (2015) The Knowledge Acquisition Toolkit – KAT (Extracting knowledge from sensor data). ICS/University of Surrey

    Abstract

    Knowledge Acquisition Toolkit (KAT) is an open-source software that includes methods to process numerical sensory data. KAT is able to extract and represent human understandable and/or machine interpretable information from raw data. KAT includes a collection of algorithms for each step of the Internet of Things (IoT) data processing workflow ranging from data and signal pre-processing algorithms such as Frequency Filters, dimensionality reduction techniques such as Wavelet, FFT, SAX, and Feature Extraction and Abstraction and Inference methods such as Clustering. Figure 1 shows the steps of the process chain for processing cyber-physical data on the Web. KAT can be used to design and evaluate algorithms for sensor data that aim to extract and find new insights from the data.

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