Prescriptive analytics for impulsive behaviour prevention using real-time biometrics

• Published in: Progress in artificial intelligence Vol. 10; no. 2; pp. 99 - 112
• Main Authors: Raychaudhuri, Soumya Jyoti, Manjunath, Soumya, Srinivasan, Chithra Priya, Swathi, N., Sushma, S., Nitin Bhushan, K. N., Narendra Babu, C.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Bayesian analysis; Biometrics; Computational Intelligence; Computer Imaging; Computer Science; Control; Data Mining and Knowledge Discovery; Deep learning; Lightweight; Machine learning; Market segments; Mechatronics; Natural Language Processing (NLP); Pattern Recognition and Graphics; Real time; Regular Paper; Robotics; Segments; Sensors; Tracking devices; Vision; Wearable technology; Biometrics; Variational autoencoders; Bayesian prediction; Artificial intelligence; Convolutional neural network

The present biometric market segment has been captured by compact, lightweight sensors which are capable of reading the biometric fluctuations of a user in real-time. This biometric market segment has further facilitated rise of a new ecosystem of wearable devices helpful in tracking the real-time p...