Artificial intelligence first debuted in the 1950s, was temporarily revived in the 1980s, and then vanished. AI resurfaced in the late 2000s and became a driving force in the IT industry.
Large-scale data is required for artificial intelligence training, however this data was not accessible until the 2000s. Things took a turn in the late 2000s with the growth of the Internet, mobile, and subsequently cloud-based services.
The Internet and cellphones facilitated data collecting from numerous sources to the cloud, while the Internet of Things has sped data collection. With this vast collection of data, artificial intelligence has accomplished what was previously simply a pipe dream.
And “the Fourth Industrial Revolution” refers to the emergence and transformation of an industrial platform comprised of IoT (smartphones), cloud services, data, and AI.
Greater security implies a greater range of procedures, that increases the inconvenience and inefficiency for those in charge of the responsibilities. In the access control system industry, the scenario is similar.
We could efficiently save money and effort by monitoring the precise region where errors are more likely to occur. Its better than watching the entire procedure where the fault happens once in a thousand.
Furthermore, if we can forecast potential problems by recognizing symptoms, we can improve security without compromising with convenience or efficiency.
AI training on large-scale data sets enables such intelligence-driven processes.
If we can capture user activity information to train AI using individual-specific behaviors and patterns, we can spot these odd undesirable behaviors that are very likely to cause a problem.
Furthermore, if an issue happens, AI may learn behaviors and patterns to predict the activity ahead of time and prevent it from happening again.
This is only conceivable if AI is installed and trained in the cloud with very accurate access, behavior, and location data collected continually via access control systems.
The Fourth Industrial Revolution
Real-time location systems (RTLS) can, on the other hand, be game changers by providing precise access and movement information. It enables you to discover circumstances where authentication/tagging is being exploited (trying to follow others without authorization or leaving after the initial tag). RTLS-enabled access control enables the data scientists to collect data with adequate precision and quality for AI training. In the future, we will have access control systems that foresee potential difficulties based on accurate entry in and out data, so preventing problem occurrence.
The article has been published by the editorial board of the Identity Herald. For more
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