Posted by Ashish Trikha

Believe it or not, but the possibilities that the Internet of Things, IoT brings to the table are countless. The internet of things, IoT continues to be the next big thing in technology, and now the new phase of the internet of things is pushing everyone hard to ask questions about the data collected by sensors and devices of IoT.  

Undoubtedly, the internet of things, IoT will generate a tsunami of data, with the swift expansion of sensors and devices connected to the IoT. The sheer volume of data being produced by the internet of things will rise exponentially in the upcoming years. This generated data can provide extremely valuable insight to figure out what’s working well and what’s not. Moreover, the internet of things, IoT, will point out the issues that often arise and provide meaningful and actionable insight into new business opportunities and potential risks as correlations and associations are made. 

Examples of IoT Data:  

• Data that improves productivity of industries through predictive maintenance of equipment and machinery 

• Data that assists smart cities in predicting crime rates and accidents   

• Data that creates truly smart living homes with connected devices    

• Data that provides doctors real-time insight into information from biochips to pacemakers 

• Data that gives critical communication between self-driven automobiles          

That’s great news, but it’s not possible for humans to monitor, analyze and understand all of this data using traditional methods. Even if they reduce the sample size, it will simply consume too much of their time.  Undoubtedly, finding actionable insights in terabytes of machine data is not a cakewalk, just ask a data scientist. The biggest challenge is to find ways to analyze the deluge of performance data and information that the internet of things, IoT devices creates. The only possible way to keep up with the terabytes of data generated by IoT devices and sensors and gain the hidden insights that it holds is using Artificial Intelligence, commonly known as AI.  

Artificial Intelligence (AI) and IoT    

Artificial intelligence, also known as machine intelligence (MI) is the intelligence that is exhibited by machines or software. John McCarthy, the person who coined this terminology back in 1955, describes it as "the science and engineering of making intelligent machines". In a nutshell, AI is a branch of computer science that emphasizes the creation of an intelligent machine that thinks intelligently, the way intelligent humans think and works and reacts like humans.   

In an IoT environment, Artificial Intelligence (AI) can aid business enterprises take the billions of data points they have and prune them down to what’s really helpful and actionable. The general principle is akin to that in retail applications i.e. review and analyze the data you have collected from different sources to find out similarities or patterns, so that better business decisions can be made.  

To be able to figure out the potential risks or problems, the collected data has to be analyzed in terms of what’s normal and what’s not. Abnormalities, correlations, and similarities need to be identified based on the real-time streams of data generated. The collected data combined with Artificial Intelligence makes life easier with predictive analytics, intelligent automation, and proactive intervention. 

Artificial Intelligence in IoT Applications  

• New sensors will enable computers and smart devices to “hear,” gather sonic information about the user’s ambience   

• Visual big data will allow computers and smart devices to gain a deeper insight of images on the screen, with the new AI app that understands the context of images

These are some of the promising applications of Artificial Intelligence in the internet of things, IoT ecosystem. The potential for highly personalized services are countless and will dramatically change the way people live. For example, Amazon.com can suggest what other books and movies you may like, helping Saavn and Gaana to determine what other songs you may love listening, and your family doctor would receive notification if you’re not feeling comfortable.  

Here Are Some Challenges Facing AI in IoT

• Artificial Stupidity

• Complexity

• Safety

• Ethical and legal Issues

• Compatibility

• Privacy/Security 

What’s Next? 

Gartner has predicted that by the end of next year, 6 billion connected devices will be requesting support, which means that processes, technologies, and strategies will have to be in place to respond to them. It is important to think of connected devices less as ‘things’, but more as customers or consumers of services in themselves. The need for Artificial intelligence, AI will become more prominent at the stage when the number of connected devices and sensors increase manifold.

Hope you find this post helpful. If you did, share it with your friends and colleagues. For AI and IoT Courses Online, you can do some research on Google to find the best institute that suits your needs and budget.

For any query related to this post, you can comment down below. Thanks for your time.