Development of a Micro Weather Station Using Arduino and Internet of Things

Autor/inn/en	Essiane, Salome Ndjakomo; Essama, Bedel Giscard Onana
Titel	Development of a Micro Weather Station Using Arduino and Internet of Things
Quelle	In: Physics Education, 57 (2022) 1, Artikel 015005 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Essama, Bedel Giscard Onana)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0031-9120
Schlagwörter	Weather; Science Instruction; Measurement Equipment; Climate; Foreign Countries; Internet; Educational Technology; Technology Uses in Education; Artificial Intelligence; Higher Education; College Science; Cameroon + Suchen Sie Ihr Suchwort? Wetter; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Messinstrument; Klima; Ausland; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Künstliche Intelligenz; Hochschulbildung; Hochschulsystem; Hochschulwesen; Kamerun
Abstract	The goal of this work is to build a low cost pedagogical device able to improve the comprehension of weather phenomena for African students in particular and in general for students across the world. This experimental and didactic device can be seen as an easy teaching tool to measure meteorological and climatic data. This structure is called a micro weather station. The investigation is done in Metipkwale one of the village of Ebolowa town in Cameroon (Central Africa). Some weather data automatically obtained from the micro weather station (sensors) such as temperature, humidity and pressure, are directly transmitted by a modem (Wi-Fi connection) to the ThingSpeak platform in order to be registered online and plotted as a diagram. The illustration process is assured by a computer or a smartphone. Moreover, the prediction process of climatic behaviour and the reactions of students have been also outlined. Further, some notions such as Internet of Things and Deep Learning associated with exponential smoothing algorithms are also presented. (As Provided).
Anmerkungen	IOP Publishing. 190 North Independence Mall West Suite 601, Philadelphia, PA 19106. Tel: 215-627-0880; Fax: 215-627-0879; e-mail: ped@ioppublishing.org; Web site: https://iopscience.iop.org/journal/0031-9120
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01