2018
[4]
A. Elsts, X. Fafoutis, P. Woznowski, E. Tonkin, G. Oikonomou, R. Piechocki, I. Craddock, "Enabling Healthcare in Smart Homes: The SPHERE IoT Network Infrastructure", IEEE Communications Magazine, IEEE, 56(12), pp. 164-170, 2018
@article{Fafoutis-2018-commag, title = {Enabling Healthcare in Smart Homes: The SPHERE IoT Network Infrastructure}, author = {Atis Elsts and Xenofon Fafoutis and Woznowski, {Przemyslaw R.} and Tonkin, {Emma L.} and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2018}, month = dec, volume = {56}, number = {12}, pages = {164--170}, doi = {10.1109/MCOM.2017.1700791}, journal = {IEEE Communications Magazine}, publisher = {IEEE}, gsid = {14036256930428349798}, oa-url = {https://research-information.bristol.ac.uk/en/publications/enabling-healthcare-in-smart-homes(efc41bd8-5805-4108-b5ff-39d232fa9477).html}, abstract = {Healthcare professionals currently lack the means to gather unbiased and quantitative multi-modal data about the long-term behaviors of patients in their home environments. SPHERE is a multi-modal platform of non-medical sensors for behavior monitoring in residential environments that aims to overcome this major limitation of healthcare provision through using the inherently cost-efficient and scalable technologies of the Internet of Things (IoT). One of SPHERE’s key tasks is to help to bring the next-generation low-power wireless networking and sensing technologies from the lab to the field by applying them in real-world environments. In this article we describe the highlights of SPHERE’s system requirements, architecture, practical challenges, as well as of the design and deployment lessons learned. By leveraging novel IoT technologies such as the IEEE 802.15.4 TSCH network protocol, SPHERE has achieved successful initial deployments in twelve volunteer houses at the time of writing.}, }
Healthcare professionals currently lack the means to gather unbiased and quantitative multi-modal data about the long-term behaviors of patients in their home environments. SPHERE is a multi-modal platform of non-medical sensors for behavior monitoring in residential environments that aims to overcome this major limitation of healthcare provision through using the inherently cost-efficient and scalable technologies of the Internet of Things (IoT). One of SPHERE’s key tasks is to help to bring the next-generation low-power wireless networking and sensing technologies from the lab to the field by applying them in real-world environments. In this article we describe the highlights of SPHERE’s system requirements, architecture, practical challenges, as well as of the design and deployment lessons learned. By leveraging novel IoT technologies such as the IEEE 802.15.4 TSCH network protocol, SPHERE has achieved successful initial deployments in twelve volunteer houses at the time of writing.
2017
[3]
P. Woznowski, A. Burrows, T. Diethe, X. Fafoutis, J. Hall, S. Hannuna, M. Camplani, N. Twomey, M. Kozlowski, B. Tan, N. Zhu, A. Elsts, A. Vafeas, A. Paiement, L. Tao, M. Mirmehdi, T. Burghardt, D. Damen, P. Flach, R. Piechocki, I. Craddock, G. Oikonomou, "SPHERE: A sensor platform for healthcare in a residential environment", in Designing, Developing, and Facilitating Smart Cities, Springer, pp. 315-333, 2017
@INCOLLECTION{Woznowski-2017-sphere, title = {SPHERE: A sensor platform for healthcare in a residential environment}, author = {Woznowski, {Przemyslaw R.} and Burrows, Alison and Diethe, Tom and Fafoutis, Xenofon and Hall, Jake and Hannuna, Sion and Camplani, Massimo and Twomey, Niall and Kozlowski, Michal and Tan, Bo and Zhu, Ni and Elsts, Atis and Vafeas, Antonis and Paiement, Adeline and Tao, Lili and Mirmehdi, Majid and Burghardt, Tilo and Damen, Dima and Flach, Peter and Piechocki, Robert and Craddock, Ian and Oikonomou, George}, editor = {Angelakis, Vangelis and Tragos, Elias and P{\"o}hls, Henrich C. and Kapovits, Adam and Bassi, Alessandro}, booktitle = {Designing, Developing, and Facilitating Smart Cities}, publisher = {Springer}, gsid = {18162269616817626173}, pages = {315--333}, isbn = {978-3-319-44924-1}, doi = {10.1007/978-3-319-44924-1_14}, year = {2017}, abstract = {It can be tempting to think about smart homes like one thinks about smart cities. On the surface, smart homes and smart cities comprise coherent systems enabled by similar sensing and interactive technologies. It can also be argued that both are broadly underpinned by shared goals of sustainable development, inclusive user engagement and improved service delivery. However, the home possesses unique characteristics that must be considered in order to develop effective smart home systems that are adopted in the real world.}, }
It can be tempting to think about smart homes like one thinks about smart cities. On the surface, smart homes and smart cities comprise coherent systems enabled by similar sensing and interactive technologies. It can also be argued that both are broadly underpinned by shared goals of sustainable development, inclusive user engagement and improved service delivery. However, the home possesses unique characteristics that must be considered in order to develop effective smart home systems that are adopted in the real world.
2016
[2]
P. Woznowski, D. Kaleshi, G. Oikonomou, I. Craddock, "Classification and Suitability of Sensing Technologies for Activity Recognition", Computer Communications, 89-90, pp. 34-50, 2016
@ARTICLE{Woznowski-2016-comcom, title = {Classification and Suitability of Sensing Technologies for Activity Recognition}, keywords = {activity recognition, sensors, ADL}, author = {Woznowski, {Przemyslaw R.} and Dritan Kaleshi and George Oikonomou and Ian Craddock}, year = {2016}, month = sep, doi = {10.1016/j.comcom.2016.03.006}, journal = {Computer Communications}, volume = {89-90}, pages = {34--50}, gsid = {2120913581950507169}, oa-url = {https://research-information.bristol.ac.uk/en/publications/classification-and-suitability-of-sensing-technologies-for-activity-recognition(3ec963e5-7f84-4490-8181-fcfc6aec2d05).html}, abstract = {Wider availability of sensors and sensing systems has pushed research in the direction of automatic activity recognition (AR) either for medical or other personal benefits e.g. wellness or fitness monitoring. Researchers apply different AR techniques/algorithms and use a wide range of sensors to discover home activities. However, it seems that the AR algorithms are purely technology-driven rather than informing studies on the type and quality of input required. There is an expectation to over-instrument the environment or the subjects and then develop AR algorithms, where instead the problem should be approached from a different angle i.e. what sensors (type, quality and quantity) a given algorithm requires to infer particular activities with a certain confidence? This paper introduces the concept of activity recognition, its taxonomy and familiarises the reader with sub-classes of sensor-based AR. Furthermore, it presents an overview of existing health services Telecare and Telehealth solutions, and introduces the hierarchical taxonomy of human behaviour analysis tasks. This work is a result of a systematic literature review and it presents the reader with a comprehensive set of home-based activities of daily living (ADL) and sensors proven to recognise these activities. Apart from reviewing usefulness of various sensing technologies for home-based AR algorithms, it highlights the problem of technology-driven cycle of development in this area.} }
Wider availability of sensors and sensing systems has pushed research in the direction of automatic activity recognition (AR) either for medical or other personal benefits e.g. wellness or fitness monitoring. Researchers apply different AR techniques/algorithms and use a wide range of sensors to discover home activities. However, it seems that the AR algorithms are purely technology-driven rather than informing studies on the type and quality of input required. There is an expectation to over-instrument the environment or the subjects and then develop AR algorithms, where instead the problem should be approached from a different angle i.e. what sensors (type, quality and quantity) a given algorithm requires to infer particular activities with a certain confidence? This paper introduces the concept of activity recognition, its taxonomy and familiarises the reader with sub-classes of sensor-based AR. Furthermore, it presents an overview of existing health services Telecare and Telehealth solutions, and introduces the hierarchical taxonomy of human behaviour analysis tasks. This work is a result of a systematic literature review and it presents the reader with a comprehensive set of home-based activities of daily living (ADL) and sensors proven to recognise these activities. Apart from reviewing usefulness of various sensing technologies for home-based AR algorithms, it highlights the problem of technology-driven cycle of development in this area.
2015
[1]
M. Haghighi, K. Maraslis, T. Tryfonas, G. Oikonomou, A. Burrows, P. Woznowski, "Game Theoretic Approach Towards Optimal Multi-tasking and Data-distribution in IoT", in Proc. IEEE World Forum on Internet of Things (WF-IoT), pp. 406-411, 2015
@INPROCEEDINGS{Haghighi-2015-wf-iot, title = {Game Theoretic Approach Towards Optimal Multi-tasking and Data-distribution in IoT}, author = {Mo Haghighi and Konstantinos Maraslis and Theo Tryfonas and George Oikonomou and Alison Burrows and Woznowski, {Przemyslaw R.}}, publisher = {IEEE}, year = {2015}, month = dec, booktitle = {Proc. IEEE World Forum on Internet of Things (WF-IoT)}, pages = {406--411}, doi = {10.1109/WF-IoT.2015.7389089}, oa-url = {http://research-information.bristol.ac.uk/en/publications/game-theoretic-approach-towards-optimal-multitasking-and-datadistribution-in-iot(b712d5cf-feb7-4576-9f43-49e5db8cecb1).html}, gsid = {13613663511745904563}, abstract = {Current applications of Internet of Things (IoT) often require nodes to implement logical decision-making on aggregated data, which involves more processing and wider interactions amongst network peers, resulting in higher energy consumption and shorter node lifetime. This paper presents a game theoretic approach used in Sensomax, an agent-based WSN middleware that facilitates seamless integration of mathematical functions in large-scale wireless sensor networks. In this context, we investigate game theoretic and auction-based techniques to optimise task distribution and energy consumption in IoT networks of multiple concurrent WSNs. We also demonstrate how our proposed game theoretic approach affects the performance of WSN applications with different operational paradigms.}, }
Current applications of Internet of Things (IoT) often require nodes to implement logical decision-making on aggregated data, which involves more processing and wider interactions amongst network peers, resulting in higher energy consumption and shorter node lifetime. This paper presents a game theoretic approach used in Sensomax, an agent-based WSN middleware that facilitates seamless integration of mathematical functions in large-scale wireless sensor networks. In this context, we investigate game theoretic and auction-based techniques to optimise task distribution and energy consumption in IoT networks of multiple concurrent WSNs. We also demonstrate how our proposed game theoretic approach affects the performance of WSN applications with different operational paradigms.
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