The two technologies that have become the cynosure of all eyes in the technology industry since their emergence are artificial intelligence (AI), and the Internet of Things (IoT). These technologies have helped companies in bringing significant innovations in multiple processes and applications.
The IoT technology enables smart automation of many devices, vehicles, buildings, and others by providing them the ability to host algorithms and perform functions through AI-enabled solutions. The AI-enabled software enables a user to manage the IoT data at speed and scale without any human intervention. The software also helps to handle the complexity of IoT technology without compromising with accuracy.
The existing AI algorithms that are designed for viewing, analyzing, and acting, are deployed primarily as a single agent where intelligence takes place independently. These individual algorithms cannot have a massive influence on the operations of a company. However, Social AI can be the answer to addressing the issue as it can combine all the results of individual occurrences, enabling businesses to gain significant insight. For instance, the algorithms in driverless cars are not just focused on an individual car; rather it optimizes the distribution of traffic in a congested situation by combining data from all the other vehicles.
The integration of IoT data in AI-enabled software can help to make distributed smart agents. These combinations will help companies in various decision-making processes by allowing a shift from default internet-connected devices to a collection of interacting smart agents. The smart agents can also help a great deal in predictive maintenance as AI-based software can use the IoT data to analyze the health of equipment. The predictive maintenance can help companies to maintain the health of their equipment and prevent any mechanical failure.
Most of the investment in the IoT industry is focused on providing innovative solutions to consumers. Businesses have now started to use IoT technology in more enterprise and B2B operations. Companies need AIOPs to handle the complexities of enterprise and B2B IoT data.