Artificial Emotional Intelligence: 5G and Emotion Recognition
A 5G-integrated virtual emotion detection system based on AI has been developed by researchers that recognize human emotions using wireless signals and movement patterns
Can you think of a world in which machines perceive people’s emotional conditions and adjust their actions to provide adequate answers to those feelings? Well, artificial emotional intelligence is already being used to build products and systems that can identify, perceive, analyze and replicate human emotions. It is also known as emotion AI.
How does artificial emotional intelligence operate?
Artificial emotional intelligence systems capture data through a mixture of machine vision, cameras and sensors, loads of actual data, speech science, and deep learning algorithms, and then analyze and associate it against other data points that recognize main emotions like fear and happiness. The machine recognizes the emotion along with what it might mean in each case once the correct emotion is defined. The algorithms get better at recognizing the complexities of human expression as the emotion database expands.
Implementation of emotionally intelligent AI
The implementations are diverse.
Automated market analysis can be supported by emotion detection and speech analytics, an area where several businesses are now providing services to track target audiences engaging with a new product or service while systematically analyzing emotional reactions.
Detection of tension or exhaustion can help make vehicle traffic secure. Identification of curiosity and dissatisfaction are obvious candidates for software for e-learning.
Methods for speaker identification will help make automatic dialogs more human-like.
Emotion AI’s additional features include automatic security analysis, credible game characters, and acting practice for specialists such as sales representatives and politicians.
The health-care and fitness sectors are another huge area with potential uses. Emotional expression monitoring can help us better understand our own emotions and those of others, and help with psychological care.
Artificial emotional intelligence with 5G and emotion recognition
A 5G-integrated virtual emotion detection system based on AI has been developed by researchers that recognize human emotions using wireless signals and movement patterns.
At least five forms of emotion can be identified by the virtual emotion system 5G-I-VemoSYS: joy, pleasure, a neutral state, sorrow and anger. It is formed by three sub – systems that deals with the flow of detection and human emotion mapping.
According to Tech Xplore, researcher Hyunbum Kim from the Incheon National University in South Korea said that “Emotions are a critical characteristic of human beings and separate humans from machines, defining daily human activity. However, some emotions can also disrupt the normal functioning of a society and put people’s lives in danger, such as those of an unstable driver. Emotion detection technology thus has great potential for recognizing any disruptive emotion and in tandem with 5G and beyond-5G communication, warning others of potential dangers,” explains Prof. Kim. “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”.
An amazing feature of 5G-I-VEmoSYS is that it makes it possible to determine emotions without exposing the individuals’ face or other private parts, thereby guarding peoples’ confidentiality in public spaces.
In addition, it offers the person the option to remain private in restricted places while providing the system with details.
In addition, when a severe emotion is intercepted in a public place, such as pain or frustration, the information is immediately transmitted to the nearby police force or appropriate authorities, who can then take measures to prevent any possible danger of crime or terrorist activity. The framework, however, endures severe security problems, such as the possibility of illegal signal interfering, confidentiality mistreatment, and cyber-attacks related to hacking, the researchers said.