Coulby, Graham, Clear, Adrian, Jones, Oliver and Godfrey, Alan (2021) Low-cost, multimodal environmental monitoring based on the Internet of Things. Building and Environment, 203. p. 108014. ISSN 0360-1323
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Abstract
Monitoring Indoor Environmental Quality (IEQ) is of growing interest for health and wellbeing. New building standards, climate targets and adoption of homeworking strategies are creating needs for scalable, monitoring solutions with onward Cloud connectivity. Low-cost Micro-Electromechanical Systems (MEMS) sensors have potential to address these needs, enabling development of bespoke multimodal devices. Here, we present insights into the development of a MEMS-based Internet of things (IoT) enabled multimodal device for IEQ monitoring. A study was conducted to establish the inter-device variability and validity to reference standard sensors/devices. For the multimodal, IEQ monitor, intraclass correlations and Bland-Altman analyses indicated good inter-sensor reliability and good-to-excellent agreement for most sensors. All low-cost sensors were found to respond to environmental changes. Many sensors reported low accuracy but high precision meaning they could be calibrated against reference sensors to increase accuracy. The multimodal device developed here was identified as being fit-for-purpose, providing general indicators of environmental changes for continuous IEQ monitoring.
Item Type: | Article |
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Additional Information: | Funding information: This work was supported by the European Regional Development Intensive Industrial Innovation Programme (IIIP) as part of doctoral research, Grant Number: 25R17P01847. The sponsoring small to medium enterprise for this programme was Ryder Architecture and it was delivered through Northumbria University. |
Uncontrolled Keywords: | Building Performance, Internet of Things (IoT), Multimodal, Sensor Fusion, Indoor Environmental Quality (IEQ) |
Subjects: | G400 Computer Science G500 Information Systems G900 Others in Mathematical and Computing Sciences |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | Rachel Branson |
Date Deposited: | 18 May 2021 15:02 |
Last Modified: | 31 May 2022 03:30 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/46205 |
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