E-Thesis 295 views 77 downloads
The Feasibility of Integrating Self-Powered Internet of Things Nodes in Indoor Conditions / GETHIN THOMAS
Swansea University Author: GETHIN THOMAS
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PDF | E-Thesis – open access
Copyright: The Author, Gethin Thomas, 2023. Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0).
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DOI (Published version): 10.23889/SUthesis.65363
Abstract
The internet of thing (IoT), also called internet of everything or industrial internet embeds intelligence into our environment, with 75.44 billion IoT connected devices projected to be worldwide by 2025. Many of these smart devices will be used in indoor environments, raising the question of how mu...
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Swansea, Wales, UK
2023
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| Institution: | Swansea University |
| Degree level: | Doctoral |
| Degree name: | Ph.D |
| Supervisor: | Carnie, Matt. and Sahoo, Deepak. |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa65363 |
| Abstract: |
The internet of thing (IoT), also called internet of everything or industrial internet embeds intelligence into our environment, with 75.44 billion IoT connected devices projected to be worldwide by 2025. Many of these smart devices will be used in indoor environments, raising the question of how much energy can be harvested under environmental ambient conditions to support IoT nodes. This thesis explores the best technology for optimised power harvesting, concluding that dye sensitised solar cells (DSSCs) provide the greatest design flexibility and performance when implemented in indoor applications, having the aesthetic qualities prioritised by users. The work investigates the optimal type of electrolyte and active area size of a monolithic DSSC for low light conditions, mainly changing the iodine concentration of the triiodide electrolyte. A new method of integrating a monolithic DSSC as an energy harvester and selfpower their interactive features was achieved in this work. This involved monitoring the photocurrent output of asymmetrical patterned monolithic DSSCs, using machine learning to recognise simple linear directional hand gestures, achieving an accuracy prediction of 98%. The patterned active area of this cell was also optimised through computer modelling the photocurrent outputs, increasing the prediction accuracy of additional directional hand gestures. Several different designs and prototypes are also presented in this work, demonstrating the importance of collaborating in the field of human computer interaction with material science. DSSCs were used to self-power different IoT node applications, which included a novel self-powered method of displaying a Moir´e pattern through an electromagnetic actuator, at very low light intensities. This thesis demonstrates that DSSCs are the ideal choice for IoT node integration in indoor conditions, having the capabilities to provide the aesthetic qualities and performance characteristics to power interactive technologies, as well as provide a mean of interactive control. |
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| Keywords: |
IoT, HCI, DSSC, Indoor Energy Harvesting, Hand Gesture Recognition |
| College: |
Faculty of Science and Engineering |
| Funders: |
EPSRC/Swansea University. |