Publication: OMNISCIENT: A Branch Monitoring System for Large-scale Organizations
Type:
Article
Date
2020-12-10
Journal Title
Journal ISSN
Volume Title
Publisher
2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract
Omniscient is a system that enables higher-level
management of massive organizations to remotely monitor and
scrutinize the activities that take place in the branches from the
head office itself by providing exclusive insight in the form of
detailed reports on the employees’ behaviour and performance
daily, weekly and monthly. The system further monitors the
branch and provides reports on any suspicious behaviour and
also on the customers’ activity within the branch premises.
Omniscient rates the customer’s level of satisfaction by
capturing the customer’s facial expressions and analyzing their
emotions while they are being served. The employee face and
dress recognition models have accuracies of 90.90% and 87.00%
respectively while, employee activity detection has an accuracy
of 89.00%. Customer emotion and miscellaneous activities
detection models have the accuracies of 91.50% and 83.00%
respectively. All of the aforementioned procedures were made
possible by systematically analyzing the IP camera video footage
obtained throughout the day to analyze the work productivity
and performance of the branch as accurately as possible using
deep learning and modern visual computing techniques like
CNN, OpenCV, Haar Cascade classifier, face recognition, Dlib
and Darknet.
Description
Keywords
CNN, Darknet, Deep Learning, Dlib, face recognition, Haar Cascade classifier, IP camera, OpenCV, visual computing
