IoT based climate prediction using ANN for green networking

Abstract

Weather forecasting plays a major role in various fields such as agriculture, transportation etc., It is also essential in prediction of natural disasters like Flood, storm etc., So in order to prevent the damages from such natural disorders, accurate weather prediction is essential. IoT topology is a combination of both hardware and wireless communication network utilized for real-time data analysis. Hence, this proposed topology formulated an IoT based weather monitoring using artificial neural network (ANN) for prediction. The main objective of this designed topology system is monitoring weather parameters such as temperature/humidity/pressure/rainfall etc., IoT is organized to collect data from sensors and is communicated through Wi-Fi network. ANN is tailored for weather prediction. The analysis proves that the proposed architecture shows better efficiency in weather prediction than the conventional methods.

The Use of Artificial Neural Networks (ANN) in the Chayote Chips Dough Mixer

“…An ANN is primarily based totally on a group of linked gadgets or nodes referred to as synthetic neurons [17], which loosely version the neurons in an organic brain. Each connection, just like the synapses in an organic brain, can transmit a sign to different neurons [18]. A synthetic neuron gets indicators then methods them and may sign neurons linked to it.…”

Performance Comparison Between Artificial Neural Network, Recurrent Neural Network and Long Short-Term Memory for Prediction of Extreme Climate Change

“…Based on research conducted by Amaratunga and friends, it shows that the results of applying the ANN model are very stable [14]. Research conducted by Rani and friends also explains that architecture provides better efficiency in weather prediction compared to conventional methods [15].…”