2018
[10]
A. Elsts, X. Fafoutis, S. Duquennoy, G. Oikonomou, R. Piechocki, I. Craddock, "Temperature-Resilient Time Synchronization for the Internet of Things", IEEE Transactions on Industrial Informatics, IEEE, 14(5), pp. 2241-2250, 2018
@article{Elsts-2018-tii, title = {Temperature-Resilient Time Synchronization for the Internet of Things}, author = {Atis Elsts and Xenofon Fafoutis and Simon Duquennoy and George Oikonomou and Robert Piechocki and Ian Craddock}, journal = {IEEE Transactions on Industrial Informatics}, publisher = {IEEE}, doi = {10.1109/TII.2017.2778746}, pages = {2241-2250}, volume = {14}, number = {5}, year = {2018}, month = {May}, oa-url = {https://research-information.bristol.ac.uk/en/publications/temperatureresilient-time-synchronization-for-the-internet-of-things(429dd808-1364-40e3-9c88-085f68ab37c9).html}, gsid = {999822098705616907}, abstract = {Networks deployed in real-world conditions have to cope with dynamic, unpredictable environmental temperature changes. These changes affect the clock rate on network nodes, and can cause faster clock de-synchronization compared to situations where devices are operating under stable temperature conditions. Wireless network protocols such as Time-Slotted Channel Hopping (TSCH) from the IEEE 802.15.4-2015 standard are affected by this problem, since they require tight clock synchronization among all nodes for the network to remain operational. This paper proposes a method for autonomously compensating temperature-dependent clock rate changes. After a calibration stage, nodes continuously perform temperature measurements to compensate for clock drifts at run-time. The method is implemented on low-power IoT nodes and evaluated through experiments in a temperature chamber, indoor and outdoor environments, as well as with numerical simulations. The results show that applying the method reduces the maximum synchronization error more than 10 times. In this way, the method allows reduce the total energy spent for time synchronization, which is practically relevant concern for low data rate, low energy budget TSCH networks, especially those exposed to environments with changing temperature.} }
Networks deployed in real-world conditions have to cope with dynamic, unpredictable environmental temperature changes. These changes affect the clock rate on network nodes, and can cause faster clock de-synchronization compared to situations where devices are operating under stable temperature conditions. Wireless network protocols such as Time-Slotted Channel Hopping (TSCH) from the IEEE 802.15.4-2015 standard are affected by this problem, since they require tight clock synchronization among all nodes for the network to remain operational. This paper proposes a method for autonomously compensating temperature-dependent clock rate changes. After a calibration stage, nodes continuously perform temperature measurements to compensate for clock drifts at run-time. The method is implemented on low-power IoT nodes and evaluated through experiments in a temperature chamber, indoor and outdoor environments, as well as with numerical simulations. The results show that applying the method reduces the maximum synchronization error more than 10 times. In this way, the method allows reduce the total energy spent for time synchronization, which is practically relevant concern for low data rate, low energy budget TSCH networks, especially those exposed to environments with changing temperature.
[9]
X. Fafoutis, A. Elsts, G. Oikonomou, R. Piechocki, I. Craddock, "Adaptive Static Scheduling in IEEE 802.15.4 TSCH Networks", in Proc. IEEE WF-IoT, pp. 263-268, 2018
@INPROCEEDINGS{Fafoutis-2018-wfiot, author = {Xenofon Fafoutis and Atis Elsts and George Oikonomou and Robert Piechocki and Ian Craddock}, title = {Adaptive Static Scheduling in IEEE 802.15.4 TSCH Networks}, publisher = {IEEE}, booktitle = {Proc. IEEE WF-IoT}, month = feb, pages = {263-268}, year = {2018}, doi = {10.1109/WF-IoT.2018.8355114}, gsid = {12784464564427922876}, oa-url = {https://research-information.bristol.ac.uk/en/publications/adaptive-static-scheduling-in-ieee-802154-tsch-networks(bfafab3a-7f19-4ac6-80b3-b2090ce85a90).html}, abstract = {TSCH (Time-Slotted Channel Hopping) is a synchronous MAC (Medium Access Control) protocol, introduced with the recent amendments to the IEEE 802.15.4 standard. Due to its channel hopping nature, TSCH is a promising enabling technology for dependable IoT (Internet of Things) infrastructures that are deployed in environments that are prone to interference. In TSCH, medium access is orchestrated by a schedule that is distributed to all the nodes in the network. In this paper, we propose Adaptive Static Scheduling to improve the energy efficiency of TSCH networks. Adaptive Static Scheduling builds on top of static schedules and allows each pair of communicating nodes to adaptively activate a subset of their allocated slots, effectively reducing the idle listening overhead of unused slots. Moreover, the nodes can dynamically activate more slots when they need to support bursts of high traffic, without the need of redistributing new schedules. Simulation results demonstrate that Adaptive Static Scheduling outperforms static scheduling in dynamic environments, operating nearly as efficiently as an oracle with knowledge of the optimal schedule.}, }
TSCH (Time-Slotted Channel Hopping) is a synchronous MAC (Medium Access Control) protocol, introduced with the recent amendments to the IEEE 802.15.4 standard. Due to its channel hopping nature, TSCH is a promising enabling technology for dependable IoT (Internet of Things) infrastructures that are deployed in environments that are prone to interference. In TSCH, medium access is orchestrated by a schedule that is distributed to all the nodes in the network. In this paper, we propose Adaptive Static Scheduling to improve the energy efficiency of TSCH networks. Adaptive Static Scheduling builds on top of static schedules and allows each pair of communicating nodes to adaptively activate a subset of their allocated slots, effectively reducing the idle listening overhead of unused slots. Moreover, the nodes can dynamically activate more slots when they need to support bursts of high traffic, without the need of redistributing new schedules. Simulation results demonstrate that Adaptive Static Scheduling outperforms static scheduling in dynamic environments, operating nearly as efficiently as an oracle with knowledge of the optimal schedule.
[8]
A. Vafeas, A. Elsts, J. Pope, X. Fafoutis, G. Oikonomou, R. Piechocki, I. Craddock, "Energy-Efficient, Noninvasive Water Flow Sensor", in Proc. SMARTCOMP, pp. 139-146, 2018
@INPROCEEDINGS{Vafeas-2018-smartcomp, title = {Energy-Efficient, Noninvasive Water Flow Sensor}, author = {Antonis Vafeas and Atis Elsts and James Pope and Xenofon Fafoutis and George Oikonomou and Robert Piechocki and Ian Craddock}, booktitle = {Proc. SMARTCOMP}, year = {2018}, pages = {139-146}, doi = {10.1109/SMARTCOMP.2018.00084}, gsid = {1340752008608334172}, abstract = {We are interested in hot and cold water flow detection in domestic kitchen and bathroom taps for smart home environments. Water flow monitoring is particularly valuable for long-term behavioural monitoring systems for health-related applications, as it enables the collection of long-term data on the hydration levels of the house residents, and it is associated with several activities of daily life, such as cooking and cleaning. This paper presents a water flow sensing device that is based on sensing the vibrations on the pipe when water is flowing through them. The proposed solution is noninvasive and energyefficient, as it does not require cutting the water pipes or altering the plumbing system, and consumes less then 2 µA in continuous operation. The proposed water flow sensor has been integrated to SPHERE, a sensing platform of non-medical sensors for healthcare monitoring and behavioural analytics in a home environment, and deployed to more than 15 residential properties.}, }
We are interested in hot and cold water flow detection in domestic kitchen and bathroom taps for smart home environments. Water flow monitoring is particularly valuable for long-term behavioural monitoring systems for health-related applications, as it enables the collection of long-term data on the hydration levels of the house residents, and it is associated with several activities of daily life, such as cooking and cleaning. This paper presents a water flow sensing device that is based on sensing the vibrations on the pipe when water is flowing through them. The proposed solution is noninvasive and energyefficient, as it does not require cutting the water pipes or altering the plumbing system, and consumes less then 2 µA in continuous operation. The proposed water flow sensor has been integrated to SPHERE, a sensing platform of non-medical sensors for healthcare monitoring and behavioural analytics in a home environment, and deployed to more than 15 residential properties.
[7]
J. Pope, A. Vafeas, A. Elsts, G. Oikonomou, R. Piechocki, I. Craddock, "An Accelerometer Lossless Compression Algorithm and Energy Analysis for IoT Devices", in Proc. WCNC Workshops, pp. 396-401, 2018
@INPROCEEDINGS{Pope-2018-wcnc, title = {An Accelerometer Lossless Compression Algorithm and Energy Analysis for IoT Devices}, author = {James Pope and Antonis Vafeas and Atis Elsts and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2018}, booktitle = {Proc. WCNC Workshops}, publisher = {IEEE}, pages = {396-401}, doi = {10.1109/WCNCW.2018.8368985}, gsid = {4137926603080687766}, oa-url = {https://research-information.bristol.ac.uk/en/publications/an-accelerometer-lossless-compression-algorithm-and-energy-analysis-for-iot-devices(ba9c4c1b-a085-429d-a5db-d8010736b6fc).html}, abstract = {The Internet of Things promises to enable numerous future applications spanning many domains, including health care, and is comprised of devices that are constrained in terms of computational and energy resources. A specific health care application is to ascertain patients' activity of daily living while at home using accelerometer data from non-invasive wearables. It is often necessary to store this data on the device to be retrieved later for analysis. However, the devices typically store far more data than can be transmitted with commonly used low power radios. To mitigate the problem, this paper proposes an energy efficient, lossless compression algorithm that uses an offline frequency distribution to create a symbol-code lookup table. Using an extensive set of data from a previous study, an analysis of the entropy of activities of daily living accelerometer data is presented. The compression algorithm is compared against this estimated entropy. Energy being critical for IoT devices, the trade-off between energy cost for compression versus energy saved during transmission is also analysed.}, }
The Internet of Things promises to enable numerous future applications spanning many domains, including health care, and is comprised of devices that are constrained in terms of computational and energy resources. A specific health care application is to ascertain patients' activity of daily living while at home using accelerometer data from non-invasive wearables. It is often necessary to store this data on the device to be retrieved later for analysis. However, the devices typically store far more data than can be transmitted with commonly used low power radios. To mitigate the problem, this paper proposes an energy efficient, lossless compression algorithm that uses an offline frequency distribution to create a symbol-code lookup table. Using an extensive set of data from a previous study, an analysis of the entropy of activities of daily living accelerometer data is presented. The compression algorithm is compared against this estimated entropy. Energy being critical for IoT devices, the trade-off between energy cost for compression versus energy saved during transmission is also analysed.
2017
[6]
@INPROCEEDINGS{Elsts-2017-SenseApp, title = {Microsecond-accuracy time synchronization using the IEEE 802.15.4 TSCH Protocol}, author = {Atis Elsts and Simon Duquennoy and Xenofon Fafoutis and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2017}, month = {2}, doi = {10.1109/LCN.2016.042}, oa-url = {http://research-information.bristol.ac.uk/en/publications/microsecondaccuracy-time-synchronization-using-the-ieee-802154-tsch-protocol(2e47abe7-60e9-48a7-9f09-9fe7f4859ccb).html}, booktitle = {Proc. IEEE SenseApp}, publisher = {IEEE}, gsid = {11807852472963901506}, abstract = {Time-Slotted Channel Hopping from the IEEE 802.15.4-2015 standard requires that network nodes are tightly time-synchronized. Existing implementations of TSCH on embedded hardware are characterized by tens-of-microseconds large synchronization errors; higher synchronization accuracy would enable reduction of idle listening time on receivers, in this way decreasing the energy required to run TSCH. For some applications, it would also allow to replace dedicated time synchronization mechanisms with TSCH. We show that time synchronization errors in the existing TSCH implementations on embedded hardware are caused primarily by imprecise clock drift estimations, rather than by real unpredictable drift variance. By estimating clock drift more precisely and by applying adaptive time compensation on each node in the network, we achieve microsecond accuracy time synchronization on point-to-point links and a <2 microsecond end-to-end error in a 7-node line topology. Our solution is implemented in the Contiki operating system and tested on Texas Instruments CC2650-based nodes, equipped with common off-the-shelf hardware clock sources (20 ppm drift). Our implementation uses only standard TSCH control messages and is able to keep radio duty cycle below 1%.} }
Time-Slotted Channel Hopping from the IEEE 802.15.4-2015 standard requires that network nodes are tightly time-synchronized. Existing implementations of TSCH on embedded hardware are characterized by tens-of-microseconds large synchronization errors; higher synchronization accuracy would enable reduction of idle listening time on receivers, in this way decreasing the energy required to run TSCH. For some applications, it would also allow to replace dedicated time synchronization mechanisms with TSCH. We show that time synchronization errors in the existing TSCH implementations on embedded hardware are caused primarily by imprecise clock drift estimations, rather than by real unpredictable drift variance. By estimating clock drift more precisely and by applying adaptive time compensation on each node in the network, we achieve microsecond accuracy time synchronization on point-to-point links and a <2 microsecond end-to-end error in a 7-node line topology. Our solution is implemented in the Contiki operating system and tested on Texas Instruments CC2650-based nodes, equipped with common off-the-shelf hardware clock sources (20 ppm drift). Our implementation uses only standard TSCH control messages and is able to keep radio duty cycle below 1%.
[5]
@INPROCEEDINGS{Elsts-2017-dcoss, title = {Scheduling high-rate unpredictable traffic in IEEE 802.15.4 TSCH networks}, keywords = {Time slotted channel hopping, scheduling, Internet of Things}, author = {Atis Elsts and Xenofon Fafoutis and James Pope and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2017}, month = {3}, booktitle = {Proc. IEEE DCOSS}, gsid = {11148583356626153925}, publisher = {IEEE}, pages = {3-10}, doi = {10.1109/DCOSS.2017.20}, oa-url = {https://research-information.bristol.ac.uk/en/publications/scheduling-highrate-unpredictable-traffic-in-ieee-802154-tsch-networks(74903df9-1c10-438c-8a05-7a4ccad936ac).html}, abstract = {The upcoming Internet of Things (IoT) applications include real-time human activity monitoring with wearable sensors. Compared to the traditional environmental sensing with low-power wireless nodes, these new applications generate a constant stream of a much higher rate. Nevertheless, the wearable devices remain battery powered and therefore restricted to low-power wireless standards such as IEEE 802.15.4 or Bluetooth Low Energy (BLE). Our work tackles the problem of building a reliable autonomous schedule for forwarding this kind of dynamic data in IEEE 802.15.4 TSCH networks. Due to the a priori unpredictability of these data source locations, the quality of the wireless links, and the routing topology of the forwarding network, it is wasteful to reserve the number of slots required for the worst-case scenario; under conditions of high expected datarate, it is downright impossible. The solution we propose is a hybrid approach where dedicated TSCH cells and shared TSCH slots coexist in the same schedule. We show that under realistic assumptions of wireless link diversity, adding shared slots to a TSCH schedule increases the overall packet delivery rate and the fairness of the system.}, }
The upcoming Internet of Things (IoT) applications include real-time human activity monitoring with wearable sensors. Compared to the traditional environmental sensing with low-power wireless nodes, these new applications generate a constant stream of a much higher rate. Nevertheless, the wearable devices remain battery powered and therefore restricted to low-power wireless standards such as IEEE 802.15.4 or Bluetooth Low Energy (BLE). Our work tackles the problem of building a reliable autonomous schedule for forwarding this kind of dynamic data in IEEE 802.15.4 TSCH networks. Due to the a priori unpredictability of these data source locations, the quality of the wireless links, and the routing topology of the forwarding network, it is wasteful to reserve the number of slots required for the worst-case scenario; under conditions of high expected datarate, it is downright impossible. The solution we propose is a hybrid approach where dedicated TSCH cells and shared TSCH slots coexist in the same schedule. We show that under realistic assumptions of wireless link diversity, adding shared slots to a TSCH schedule increases the overall packet delivery rate and the fairness of the system.
[4]
X. Fafoutis, A. Vafeas, B. Janko, S. Sherratt, J. Pope, A. Elsts, E. Mellios, G. Hilton, G. Oikonomou, R. Piechocki, I. Craddock, "Designing Wearable Sensing Platforms for Healthcare in a Residential Environment", EAI Endorsed Transactions on Pervasive Health and Technology, European Alliance for Innovation, 17(12), 2017
@article{Fafoutis-2017-eai, title = {Designing Wearable Sensing Platforms for Healthcare in a Residential Environment}, author = {Xenofon Fafoutis and Antonis Vafeas and Balazs Janko and Simon Sherratt and James Pope and Atis Elsts and Evangelos Mellios and Geoffrey Hilton and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2017}, month = {9}, doi = {10.4108/eai.7-9-2017.153063}, volume = {17}, journal = {EAI Endorsed Transactions on Pervasive Health and Technology}, issn = {2411-7145}, publisher = {European Alliance for Innovation}, number = {12}, gsid = {1445270239734662268}, oa-url = {https://research-information.bristol.ac.uk/en/publications/designing-wearable-sensing-platforms-for-healthcare-in-a-residential-environment(5a9756d4-c840-479d-a989-2e8bbaa9f0ff).html}, abstract = {Wearable technologies are valuable tools that can encourage people to monitor their own well-being and facilitate timely health interventions. In this paper, we present SPW-2; a low-profile versatile wearable sensor that employs two ultra low power accelerometers and an optional gyroscope. Designed for minimum maintenance and a long-term operation outside the laboratory, SPW-2 is able to oer a battery lifetime of multiple months. Measurements on its wireless performance in a real residential environment with thick brick walls, demonstrate that SPW-2 can fully cover a room and - in most cases - the adjacent room, as well.}, }
Wearable technologies are valuable tools that can encourage people to monitor their own well-being and facilitate timely health interventions. In this paper, we present SPW-2; a low-profile versatile wearable sensor that employs two ultra low power accelerometers and an optional gyroscope. Designed for minimum maintenance and a long-term operation outside the laboratory, SPW-2 is able to oer a battery lifetime of multiple months. Measurements on its wireless performance in a real residential environment with thick brick walls, demonstrate that SPW-2 can fully cover a room and - in most cases - the adjacent room, as well.
[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]
@INPROCEEDINGS{Elsts-2016-SenseApp, title = {Microsecond-Accuracy Time Synchronization Using the IEEE 802.15.4 TSCH Protocol}, author = {Atis Elsts and Simon Duquennoy and Xenofon Fafoutis and George Oikonomou and Robert Piechocki and Ian Craddock}, year = {2016}, month = nov, booktitle = {Proc. IEEE SenseApp}, gsid = {11807852472963901506}, publisher = {IEEE}, oa-url = {https://research-information.bristol.ac.uk/en/publications/microsecondaccuracy-time-synchronization-using-the-ieee-802154-tsch-protocol(2e47abe7-60e9-48a7-9f09-9fe7f4859ccb).html}, abstract = {Time-Slotted Channel Hopping from the IEEE 802.15.4-2015 standard requires that network nodes are tightly time-synchronized. Existing implementations of TSCH on embedded hardware are characterized by tens-of-microseconds large synchronization errors; higher synchronization accuracy would enable reduction of idle listening time on receivers, in this way decreasing the energy required to run TSCH. For some applications, it would also allow to replace dedicated time synchronization mechanisms with TSCH. We show that time synchronization errors in the existing TSCH implementations on embedded hardware are caused primarily by imprecise clock drift estimations, rather than by real unpredictable drift variance. By estimating clock drift more precisely and by applying adaptive time compensation on each node in the network, we achieve microsecond accuracy time synchronization on point-to-point links and a <2 microsecond end-to-end error in a 7-node line topology. Our solution is implemented in the Contiki operating system and tested on Texas Instruments CC2650-based nodes, equipped with common off-the-shelf hardware clock sources (20 ppm drift). Our implementation uses only standard TSCH control messages and is able to keep radio duty cycle below 1\%.} }
Time-Slotted Channel Hopping from the IEEE 802.15.4-2015 standard requires that network nodes are tightly time-synchronized. Existing implementations of TSCH on embedded hardware are characterized by tens-of-microseconds large synchronization errors; higher synchronization accuracy would enable reduction of idle listening time on receivers, in this way decreasing the energy required to run TSCH. For some applications, it would also allow to replace dedicated time synchronization mechanisms with TSCH. We show that time synchronization errors in the existing TSCH implementations on embedded hardware are caused primarily by imprecise clock drift estimations, rather than by real unpredictable drift variance. By estimating clock drift more precisely and by applying adaptive time compensation on each node in the network, we achieve microsecond accuracy time synchronization on point-to-point links and a <2 microsecond end-to-end error in a 7-node line topology. Our solution is implemented in the Contiki operating system and tested on Texas Instruments CC2650-based nodes, equipped with common off-the-shelf hardware clock sources (20 ppm drift). Our implementation uses only standard TSCH control messages and is able to keep radio duty cycle below 1\%.
[1]
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.
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