Although playing an increasingly important role in assistive technology, HAR is underutilised due to its high cost and the lack of adequate training in its use.
A framework enabling collection of information about human activity by using a sensor to capture 3D-skeleton data which is then analysed to understand patterns of movement. The sensor can recognise characteristics of different actions, thus interpreting the activities being performed. This information can be used in fields including sports training, security, ambient-assisted living, entertainment and health monitoring and management.
Parham is a Computer Science Ph.D. student at Universiti Brunei Darussalam (UBD). He completed his Bachelor of Engineering in Computer Engineering and M.SC. degree in Information Technology Engineering. His vast research and experience in the field has focused on areas such as computer vision, machine learning, evolutionary algorithm, artificial intelligence, data mining and optimization. He is currently working on 6 projects simultaneously that include unsupervised human activity recognition, unsupervised deep clustering for image clustering, heart disease risk calculator using symbolic regression, unsupervised fault diagnosis, inventing a new evolutionary algorithm inspired by nature and application of deep learning in scaffold decoration for drug discovery.moreLinkedIn
AI-driven device providing purchasing advice to the elderly
Using advanced data analysis to eradicate segregation in urban areas