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The need to incorporate AI into IoT applications
Large volumes of data are generated by IoT devices. This data becomes important only when it can be analyzed for actionable insights. This is where AI comes into the picture where it helps to analyze the vast amounts of data and extract valuable insights from it which the IoT devices or applications can later put to good use.

The vast amounts of real-time data coming from IoT devices cannot be efficiently analyzed using traditional methods. Machine Learning which is a part of AI helps to analyze and derive optimum value from this data.

AI which has been integrated into an IoT environment plays a crucial role in the case of real-time as well as post-event processing. You can expect fast responses to conditions and the build-up of data related to events during real-time processing. AI aids in running a predictive analysis through pattern identification within the datasets in the aftermath of an event.

A few scenarios in which AI has been incorporated into an IoT environment;
Autonomous Cars by Tesla Motors
All the cars by Tesla Motors operate as a network. When a single car leverages the power of AI to learn and predict the behavior of pedestrians and vehicles in different conditions, all the other Tesla Motor cars within the same network learn from it.

Automated Vacuum Cleaners
An automated vacuum cleaner works efficiently by mapping and saving the layout of the house. This helps them to adjust to various surfaces and clean a particular room efficiently.

Industrial IoT
AI and IoT aid in predictive maintenance in an industrial setup. AI helps by extracting insights from datasets that are received from the IoT platform and uses it to predict conditions that can fail equipment.

AI and IoT work together and complement each other as “Connected Intelligence” that makes data actionable by enriching with its context and creativity.

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