Scalable Lightweight IoT-Based Smart Weather Measurement System Article Swipe
Abdullah Albuali
,
Ramasamy Srinivasagan
,
Ahmed Aljughaiman
,
Fatima Alderazi
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/s23125569
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/s23125569
The Internet of Things (IoT) plays a critical role in remotely monitoring a wide variety of different application sectors, including agriculture, building, and energy. The wind turbine energy generator (WTEG) is a real-world application that can take advantage of IoT technologies, such as a low-cost weather station, where human activities can be significantly affected by enhancing the production of clean energy based on the known direction of the wind. Meanwhile, common weather stations are neither affordable nor customizable for specific applications. Moreover, due to weather forecast changes over time and location within the same city, it is not efficient to rely on a limited number of weather stations that may be located far away from a recipient’s location. Therefore, in this paper, we focus on presenting a low-cost weather station that relies on an artificial intelligence (AI) algorithm that can be distributed across a WTEG area with minimal cost. The proposed study measures multiple weather parameters, such as wind direction, wind velocity (WV), temperature, pressure, mean sea level, and relative humidity to provide current measurements to recipients and AI-based forecasts. In addition, the proposed study consists of several heterogeneous nodes and a controller for each station in a target area. The collected data can be transmitted through Bluetooth low energy (BLE). The experimental results reveal that the proposed study matches the standard of the National Meteorological Center (NMC), with a nowcast measurement of 95% accuracy for WV and 92% for wind direction (WD).
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s23125569
- https://www.mdpi.com/1424-8220/23/12/5569/pdf?version=1686729696
- OA Status
- gold
- Cited By
- 10
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380996275
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4380996275Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s23125569Digital Object Identifier
- Title
-
Scalable Lightweight IoT-Based Smart Weather Measurement SystemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-14Full publication date if available
- Authors
-
Abdullah Albuali, Ramasamy Srinivasagan, Ahmed Aljughaiman, Fatima AlderaziList of authors in order
- Landing page
-
https://doi.org/10.3390/s23125569Publisher landing page
- PDF URL
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https://www.mdpi.com/1424-8220/23/12/5569/pdf?version=1686729696Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/1424-8220/23/12/5569/pdf?version=1686729696Direct OA link when available
- Concepts
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Weather station, Wind speed, Computer science, Scalability, Renewable energy, Real-time computing, Wind power, Environmental science, Automatic weather station, Cloud computing, Meteorology, Engineering, Database, Electrical engineering, Geography, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 3, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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