Publication: Low Cost – Remote Passive Sensory Based Weather Prediction System with Internet of Things
Type:
Article
Date
2022-02-11
Journal Title
Journal ISSN
Volume Title
Publisher
SLIIT
Abstract
Climate 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.
Description
Keywords
Low-Cost Automatic Weather Station, World Meteorological Organization (WMO), Wireless passive remote sensory medium, Internet of Things (IoT)
