Authentication Techniques for Human Monitoring in Closed Environment

Human monitoring and trailing in a blocked or closed environment such as a jail or psychological shelter is an important research concern. Industry 4.0 has enabled the monitoring of physically or mentally challenged people in asylums and criminals who are sentenced to serve their terms in jails with various tools such as sensors, wireless systems and sophisticated cameras. The hidden nature of monitoring and reporting in closed environments without any new technologies such as IoT, RFID, etc., may lead to ill-treatment of the inmates in the above-mentioned places. The traditional physical monitoring system can end up with wrong reports about the inmates and can hide the real scenarios. Personal opinions and characteristics of officials as well as the prisoners may vary based on their health and behavioral patterns. The automation of human monitoring involves monitoring of security, activity, fitness, and health factors of the inmates in the closed environment. The human-activity monitoring is carried out by acquiring and analyzing the body signals of the inmates. Passive tags are attached to the wristband of each person in the RFID human monitoring systems. Minimal human intervention and effort is one of the biggest advantages of the human monitoring system. Authentication, intelligent decision making and minimum use of resources are the main challenges in designing a human monitoring system. Intelligent decision making algorithms are applied to predict human behavioral patterns. This work gives a summary of different authentication protocols and methodologies used with the Internet of Things (IoT) and RFID devices in human monitoring systems. It presents the components and infrastructure of a typical human monitoring system and summarizes the sensors and IoT devices used for the same. A wide investigation is conducted on security and privacy issues while storing the private and confidential details of the inmates. A comprehensive survey on different authentication techniques and data security issues in closed human monitoring is presented in this work.