IoT-based weather station with python user interface for measurement technique of educational purpose

Iswanto, Iswanto; Megantoro, Prisma; Pramudita, Brahmantya Aji

doi:10.1063/5.0030365

Cited by 6 publications

(1 citation statement)

References 34 publications

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“…Weather stations also have applications for specific areas or studies in literature such as agricultural activities by (Math & Dharwadkar, 2017), groundwater charge prediction carried out by (Holländer et al, 2016) and applied glaciology research carried out by (Citterio et al, 2015). Additionally, weather stations are extensively employed in laboratories, particularly those dedicated to education, research, and accreditation, as precise measurement accuracy is imperative in these areas (Iswanto et al, 2020). Variations in ambient conditions have the potential to compromise the measurement accuracy of physical quantities, leading to low sensitivity or erroneous measurements.…”

Section: Introductionmentioning

confidence: 99%

YÜKSEK GERİLİM LABORATUVARLARI İÇİN IoT TABANLI HAVA İSTASYONU TASARIMI VE UYGULAMASI

KUMRU,

VURAL

2023

Mühendislik Bilimleri Ve Tasarım Dergisi

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This study presents the design and implementation of an internet of things (IoT) based weather station for high voltage laboratories using the Raspberry Pi 4 Model B and two BME680 sensors. The weather station calculates the relative air density and humidity correction coefficients using the temperature, pressure, and relative humidity data obtained from the sensors. The study investigates the effect of the constant and real-time calculation of these coefficients on the measurement of AC, DC and lightning breakdown voltage using spherical electrodes. Measurements were performed within a laboratory setting for a period of 12 hours, and the obtained results were subsequently compared. The findings reveal that the real time calculation of the correction coefficients leads to a reduction in measurement errors. The study also includes the development of a web-based user interface using HTML and CSS, which is hosted on the Raspberry Pi 4 using the Flask web framework. This interface allows users to access the weather station data from any device with a web browser and provides real-time monitoring of the current coefficients, as well as the capability to calculate actual parameters online.

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