Md. Hasan Al Banna

TL;DR: An artificial intelligence-based system that uses sensor data to monitor the patient’s condition, and based on the emotion and facial expression of the patient, adjusts the learning method through exciting games and tasks can help the parents to adjust to the new situation and continue the mental growth of the patients.

TL;DR: Wang et al. as mentioned in this paper proposed a novel pipeline for fall detection based on wearable accelerometer data and three publicly available datasets have been used to validate their proposed method, and more than 7700 cross-disciplinary time-series features were investigated for each of the datasets.

TL;DR: Covering all existing AI-based techniques in earthquake prediction, this article provides an account of the available methodologies and a comparative analysis of their performances and outlines some open challenges and potential research directions in the field.

TL;DR: In this paper, some of the research works in the field of application of AI, ML, and IoT in autism were reviewed and incorporation of the autism facilities in smart city environment is described.

TL;DR: In this article, an earthquake occurrence and location prediction model is proposed, which is composed of combinations of various LSTM architectures and dense layers, and an attention mechanism was added to the LSTMs architecture to improve the model's earthquake occurrence prediction accuracy.