Abstract: A seizure prediction algorithm based on deep learning that integrates the feature extraction and classification processes into a single automated architecture is claimed herein. In the method, the computation complexity is reduced because there is no feature engineering. The method uses a novel algorithm for EEG channel selection in which the number of EEG channels is decreased to reduce the required memory for storing the data and parameters. In one or more embodiments, an IoT based framework for accurate epileptic seizure prediction system is disclosed.