The virtual emotion system -- 5G-I-VemoSYS -- can recognise at least five kinds of emotion -- joy, pleasure, a neutral state, sadness and anger -- and is composed of three subsystems dealing with the detection -- flow and mapping of human emotions.
"Emotion detection technology thus has great potential for recognising any disruptive emotion and in tandem with 5G and beyond-5G communication, warning others of potential dangers," said researcher Hyunbum Kim from the Incheon National University in South Korea.
"For instance, in the case of the unstable driver, the AI-enabled driver system of the car can inform the nearest network towers, from where nearby pedestrians can be informed via their personal smart devices," Kim added.
The system concerned with detection is called AI-Virtual Emotion Barrier, or AI-VEmoBAR, which relies on the reflection of wireless signals from a human subject to detect emotions.
This emotion information is then handled by the system concerned with flow, called AI-Virtual Emotion Flow, or AI-VEmoFLOW, which enables the flow of specific emotion information at a specific time to a specific area.
Finally, the AI-Virtual Emotion Map, or AI-VEmoMAP, utilizes a large amount of this virtual emotion data to create a virtual emotion map that can be utilized for threat detection and crime prevention.
In the study, published in the journal IEEE Network, the team studied the flip side of such technological revolution is that AI itself can be used to attack or threaten the security of 5G-enabled systems which, in turn, can greatly compromise their reliability.
The team found that it allows emotion detection without revealing the face or other private parts of the subjects, thereby protecting the privacy of citizens in public areas.
Furthermore, when a serious emotion, such as anger or fear, is detected in a public area, the information is rapidly conveyed to the nearest police department or relevant entities who can then take steps to prevent any potential crime or terrorism threats.
However, the system suffers from serious security issues such as the possibility of illegal signal tampering, abuse of anonymity and hacking-related cyber-security threats, the researchers said.