Weather Data Transmission Driven By Artificial Neural Network based Prediction

Nowadays, the trend of big data that can be describe as a massive volume and
unstructured data have become more complicated because of its difficulty to be process
using traditional database and software techniques. Due to increase in size of data, there
also demand for big bandwidth for the transmission of big data. Data transmission is
important in communication in providing information at different location. In this
project we focus on big data transmission in the context of weather data. Weather data is
important for meteorologist as it helps them to make weather prediction. Real time
weather prediction is really important as it would help in making quick decision to react
with the environment and planning for our daily activities. The purpose of this project is
to develop a real time and low bandwidth usage for weather data transmission driven by
an artificial neural network perform weather forecast using Adaptive Forecasting Model.
This project seeks an application context offshore because the data transmission from
offshore to onshore is very costly and requires high usage of network bandwidth. Other
than that, offshore weather can change rapidly and cause offshore activity to be delayed.