Statistics suggest that a whopping 64 billion IoT devices can be speculated by 2025. When we talk about the latest technologies shaping the IT industry, Artificial Intelligence and the Internet of Things are often top the list. No wonder these technologies complement each other so well. The duet has revamped the conventional solutions both on the industrial and business fronts.
Consolidating IoT with AI can help us make Intelligent Machines. These smart automation systems not only help in facilitating the monotonous tasks but making witty decisions without even the slightest of human involvement.
A typical IoT system integrates various sensors, servo motors, either on an Arduino board or Raspberry pi board. This integrated circuit is then fit into the device that is intended to be made smart. Now, these devices generate data. The data can either be structured or unstructured. The devices actually become smart when they invoke the experiential analysis from this data. This is where AI comes into the picture.
Both IoT and AI have their part to play. IoT server generates humongous data, while AI has the potential to decipher and derive insights from it. Hence, by coupling both the capabilities, one can establish an intelligent-acting system.
Businesses and Enterprises across verticals can leverage the IoT-based analysis to make efficacious decisions and creative plans. An artificial Intelligence-based IoT-system can also provide enhanced security and confidentiality.
The continuous data streams, along with complex data points, can be analyzed using various Machine Learning algorithms like Linear or Logistic Regression, Random Forest, etc. Which, in turn, can help find the loopholes that need to be fixed for efficient system execution.
It also helps in identifying the deficiencies and find an optimal alternative for a pre-existing architecture. Thus, eventually resulting in increased efficiency.
AI-enabled IoT systems can predict a wide range of risk points well in advance. This not only helps in mitigating the risk but also ensures a smooth recovery just in case the system failure occurs. This serves as a dual benefit saving the overhead expenses and avoiding a breakdown facilitating BAU (Business as Usual).
Thus, enterprises should have a well-structured business continuity plan in place so that the risk mitigation can be implemented. IoT-based smart devices get a high degree of benefit when it comes to mitigating risk and disaster recovery, provided they have a research-intensive analysis in place.
The low-end sensors and ICs which form the entire IoT system may not be cent percent accurate at all times. But, if the system has an AI filter that analyzes the data and sends the refined version for further processing, the scalability prospects can be increased dramatically. Think of it as a screening mechanism wherein the machine learning techniques analyze and filter the valid data points and transmit if further to give a more concrete overview of things.
The smart systems are actually 'smart' when they employ experiential learning and caters to the users with a predictive fault-tolerant mechanism. The predictive maintenance enables the users to forecast possible damages and breakdowns well in time. Another facet to the reduced expenditure is the reduced operational cost. The integration of AI into the IoT system saves the cost and effort for an explicit mechanism to handle data concerns.
These were the benefits that an AI-based IoT-system offers to its users. Now, let's look at the real-world implementation of the same.
Self-Driving Cars are the best example of AI+IoT based system in the real world. These cars can predict the pedestrian's movements and suggest possible measures to be taken for the cognitive sensing machines. It helps in finding the suitable driving speed, amount of time, and the optimum path to reach a destination.
Thus, if we critically analyze the integration of Artificial Intelligence with the Internet of Things, then it is a win-win situation. The AI-based systems manage the data streams and evaluate data points in real-time to make wise decisions in order to optimize the performance and efficiency of the smart devices and automation systems.