Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3021
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dc.contributor.authorTennekoon, S-
dc.contributor.authorChandrasekara, S-
dc.contributor.authorAbhayasinghe, N-
dc.date.accessioned2022-10-05T07:28:30Z-
dc.date.available2022-10-05T07:28:30Z-
dc.date.issued2022-02-11-
dc.identifier.issn2961-5011-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/3021-
dc.description.abstractClimate effects many major daily aspects of the society, from the food sources and transport infrastructure to the choice of fashion and certain daily routines. Due to these reasons, the demand for means to accurately foresee climatic changes have increased. Weather forecasting, especially in Sri Lanka, has been hampered due to numerous reasons and this has resulted in erroneous predictions that has adversely affected many areas of development ranging from agriculture, irrigation, and the tourism industry to certain branches of engineering. Many researchers have analyzed and proposed solutions to these problems. However, the need for accurate predictions prevails due to the hardship of accurate data acquisition, processing, and transmission. To address these problems, in this paper, a system that adheres to the rules and regulations set forth by the World Meteorological Organization (WMO) to carry out well informed and reliably accurate weather predictions based on the data attained from a wireless passive remote sensory medium has been implemented. This task was carried out by means of feeding the relevant climatic parameter readings measured via multiple wireless passive remote sensory nodes placed within the proximity of a considered area to a selected computational model, which in turn was implemented to yield considerably accurate predictions compared to the weather prediction systems currently available in the market. The paper comprises of the implementation of the category, Low-Cost Automatic Weather Station (LC-AWS) specified by the WMO and Internet of Things (IoT), one of the latest technologies, for the transmission of attained data even in the absence of Wi-Fi. The research was further conducted to perform an analytical comparison between highly accurate weather stations and the implemented low-cost weather station when compromising accuracy due to low cost. The hardware and related software implementation yielded an acceptable success rate and was concluded successfully.en_US
dc.language.isoenen_US
dc.publisherSLIITen_US
dc.relation.ispartofseriesProceedings of the SLIIT International Conference On Engineering and Technology,;Vol. 01-
dc.subjectLow-Cost Automatic Weather Stationen_US
dc.subjectWorld Meteorological Organization (WMO)en_US
dc.subjectWireless passive remote sensory mediumen_US
dc.subjectInternet of Things (IoT)en_US
dc.titleLow Cost – Remote Passive Sensory Based Weather Prediction System with Internet of Thingsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.54389/NUFC2535-
Appears in Collections:Proceedings of the SLIIT International Conference On Engineering and Technology Vol. 01(SICET) 2022
Research Papers - Department of Electrical and Electronic Engineering

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