SenseSafe
Security & Public Safety Use Case
Background
A government agency is concerned about public safety when large crowds congregate in public places, commercial venues and public events.
Monitoring the mood of the crowd is considered essential to maintaining the right amount of security.
Objectives
Monitor the emotions of the crowd at different locations, time periods and activities.
Identify suspicious persons of interest, prevent violent behaviour. Defend public safety
Solutions
SenseSafe’s emotion sensing AI algorithm can be integrated with existing surveillance cameras in public places, billboards and streets, so that it can monitor facial expressions, determining the mood of the crowd and of persons of interest.
SenseSafe detects the crowd’s emotional temperature at facility entrances, exits and major check points providing an early alert to suspicious behavior.
When the algorithm detects a negative mood, security officers are warned to be ready to intervene quickly in case of a potential threat.
Studies show that most people experience a sense of guilt before they actually commit a crime.
It is usually impossible to mask this inner state and it reveals itself in facial expressions.
SenseSafe’s emotion-sensing algorithm is also useful in identifying the coalescence of aggressive groups and detecting the likelihood of abnormal behaviour.
Opsis ensures full compliance with the complex privacy laws of each country.
In deploying emotion AI recognition, we work together with the country’s official agencies and security departments.
Benefits
Emotion recognition AI can be a powerful tool when it comes to warning security officials of potentially dangerous emotional hot spots in a crowd.
The ability to detect and interpret emotions can be a crucial factor in protecting both the public and private assets.
Incorporating emotion recognition AI into automated surveillance cameras increases accuracy in identifying suspicious behaviour.
A deep understanding of human behavior is an essential element in control of emergencies. Emotion recognition AI makes it possible to analyze crowd behavior using semantic observation.
A major advantage of SenseSafe emotion recognition technology is that it is not physically intrusive.
Data concerning crowd engagement and mood is continuously collected without attracting unnecessary public attention. The result is real-time feedback for intervention.
SenseSafe’s emotion sensing AI algorithm can be trained using agency data bases.
