How can you use this software in a real-time dynamic business? Here are a couple of examples:
More than 1.8 petabytes of data were used to fine-tune the performance of face recognition. The system is still digesting just below a thousand gigabytes per day to improve it even more. All AI features are part of a neural network and are spread across four dedicated AI models.
It is a feature capable of identifying and verifying a person from a visual frame for a camera. Face recognition works by comparing facial features with all identities before saved in a database. This feature works in a dynamic retail setup as well in access control spaces.
Age prediction makes estimation on how old each recorded person is. Age prediction is executed with a precision that falls into industry standard of +-5 years above or below real age. Gender prediction provides a certain estimation of the identity’s biological gender. Admin can choose to change the age and gender information of each visitor. Both features are used for complete demographic reporting.
Emotion recognition lets you understand visitor’s emotions and feelings at relevant moments. This helps to recognize the level of customer satisfaction. It also gives insight into the quality of your customer relationship management.
People counting is live data showing the number of people positioned in front of the camera. This data improves awareness in real-time without the need to constantly watch camera streams.
Hybrid setup combining the locally dedicated server and power of cloud deployment thus optimizing the resource consumption, storage capacities and bandwidth
The pricing is adjusted based on the number of cameras doing the AI processing
We are offering remote assistance via Zendesk and a thorough help section to get a better grip on the software’s capabilities.
The use of AI features, collected real-time and historical data aims to empower data-driven decision making processes. These features are constantly getting better thanks to Machine Learning.Try it for free!