AIoT is a paradigm shift where digital capabilities develop a kind of consciousness; where intelligent systems connected to the Internet of Things (IoT) become self-learning and self-decisioning.
In the nearly two decades since the term “Internet of Things (IOT)” was coined, sensors, actuators and networked intelligence have made their way into every corner of society—from homes and cities to industry, energy exploration and environmental monitoring.
The progress is nonstop
Today the vast majority of IoT applications remain focused on gathering data and decision support. What if the vast IoT network could be leveraged for more than that? What if advances in machine and artificial intelligence could be overlaid onto the IoT for systems that become more predictive, self-learning and even self-decisioning? That’s the definition of AIoT, and it’s already happening to some extent today.
More than anything, the security video sector is facing an avalanche of content which is outpacing the human ability to monitor all the data. Against those human limitations is the exploding growth of data: Today, more than billions of hours of security video are recorded each day. The stark reality is that much of that footage is essentially ignored until an incident occurs.
Assuming IoT infrastructure, graphics, and cloud capabilities are powerful enough, machine learning can analyze large amounts of visual information to learn from examples, programmed configurations and historical data. This advanced technology can take the analysis even further, identifying everything in the photo and creating probability maps about behaviors. Such probability maps are what power advanced video capabilities like human intrusion alerts, fight detection, object recognition and people-counting.
You can read more about this subject in this article (Source : Security Management)
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