Correlation among environmental parameters using an online Smart Weather Station System

Mittal, Yash; Mittal, Anshika; Bhateja, Diksha; Parmaar, Komal; Mittal, Veena

doi:10.1109/indicon.2015.7443621

Cited by 13 publications

(4 citation statements)

References 8 publications

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“…Surface weather data can be observed simply using local weather stations. These are the fundamental data used for weather forecasting and issue relevant warning messages (Gounaris et al 2010;Mittal et al 2015). The upper air data can be measured using radars and satellites (Haimberger et al 2008).…”

Section: Weather Parametersmentioning

confidence: 99%

Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station

et al. 2020

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Non-predictive or inaccurate weather forecasting can severely impact the community of users such as farmers. Numerical weather prediction models run in major weather forecasting centers with several supercomputers to solve simultaneous complex nonlinear mathematical equations. Such models provide the medium-range weather forecasts, i.e., every 6 h up to 18 h with grid length of 10-20 km. However, farmers often depend on more detailed short-to medium-range forecasts with higher-resolution regional forecasting models. Therefore, this research aims to address this by developing and evaluating a lightweight and novel weather forecasting system, which consists of one or more local weather stations and state-of-the-art machine learning techniques for weather forecasting using time-series data from these weather stations. To this end, the system explores the state-of-the-art temporal convolutional network (TCN) and long short-term memory (LSTM) networks. Our experimental results show that the proposed model using TCN produces better forecasting compared to the LSTM and other classic machine learning approaches. The proposed model can be used as an efficient localized weather forecasting tool for the community of users, and it could be run on a stand-alone personal computer.Soft Computing https://doi.org/10.1007/s00500-020-04954-0( 0123456789().,-volV) (0123456789(). ,-volV)Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. P. Hewage et al.

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Section: Weather Parametersmentioning

confidence: 99%

Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station

et al. 2020

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“…This standard includes the recording of several meteorological parameters, the recording interval, and recommendations on the positioning of the sensors. A weather station is used to manage data and communicate with measuring instruments [14,15].…”

Section: Requirementsmentioning

confidence: 99%

Solar Photovoltaic: A global technical study for Design, Installation and High Performance

Thomas¹

2023

IJLERA

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Solar energy is one of the possibilities for reducing the global carbon footprint. The solar is made up of two types of solar panels: the photovoltaic solar and the thermal solar. Solar thermal is mainly intended to produce hot water, while photovoltaic solar is intended for the direct production of electricity. This article is about photovoltaics. Its objective is to provide, after in-depth research, requirements on the design and installation of the elements of a photovoltaic system to guarantee optimum performance throughout the life cycle.

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“…Thanks to advances in science and technology, we are currently able to collect weather data at high spatial and temporal resolution and with low-cost [5][6][7][8][9][10][11]. This huge amount of generated data is unprecedented, and it brings the notion of big data to this field, which requires adequate infrastructure and processing methods.…”

Section: Introductionmentioning

confidence: 99%

Towards Smart Big Weather Data Management

Hachimi¹,

Belaqziz

Khabba

et al. 2022

The 1st International Online Conference on Agriculture—Advances in Agricultural Science and Technology

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Correlation among environmental parameters using an online Smart Weather Station System

Cited by 13 publications

References 8 publications

Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station

Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather station

Solar Photovoltaic: A global technical study for Design, Installation and High Performance

Towards Smart Big Weather Data Management

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