2018
[4]
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.
[3]
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
[2]
@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.
[1]
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.
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