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Innovation in the field of Science
Solar Sight
Green! Solar! Sustainable!
Description: Estimates the amount of
solar energy generated and the electricity Implementation
demands using machine learning. Backend Feature Engineering — Using
Spearman and Pearson correlation operators
on our datasets we concluded that pressure,
Abstract: It was rightly said by James
Cameron, “The nation that leads in humidity, wind direction, wind speed and
renewable energy will lead the world.”. Our the radial distance to solar noon are correlated
vision is to make solar energy accessible to to the amount of electrical power generated.
the common people and add value to the
lives of millions of people who rely on
clean energy. python in the backend and Flutter for the
app. Further it also predicts the energy
Due to the various uncertainties in weather demands of any Indian state using time-
conditions and solar radiation, Solar Power series estimation.
Plants cannot optimize their systems to
incorporate the variance of atmospheric Target Clients and Commercial Viability
conditions. Similarly, for individual users Solar Sight aims to help the existing individuals
they cannot estimate the amount of electricity and corporations who use green energy
produced. calculate the amount of electricity generated
and also find the electricity demands of a day.
Solar Sight is able to estimate the amount This is especially helpful for the solar power
of electrical power generated in an area per plant companies. It helps them improvise
100 Sq.Feet . It uses machine learning using and optimize their power management
systems.
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