With the advent of IoT (Internet-of-Things), the adoption of this technology across different industry vertical is rapidly increasing worldwide. This innovative technology creates new networks of products and services and unfolds splendid business opportunities with new business models. The resulting transformation is ushering in a new era of how companies run their operations and engage with customers. However, tapping into the IoT is only part of the story.
Hence, in order to leverage the full potential of IoT enablement, in reality, the companies require combining IoT with rapidly-advancing Artificial Intelligence (AI) technologies, to simulate intelligent behavior in ‘smart machines’ and make well-informed decisions with little or no human intervention.
IoT will produce a tsunami of big data, with the rapid expansion of devices and sensors connected to the Internet of Things continues, the sheer volume of data being created by them will increase to an astronomical level. This data will hold extremely valuable insights into what’s working well or what’s not.
Examples of IoT data
- Data that gives doctors real-time insight into information from pacemakers or biochips
- Data that helps cities predict accidents and crimes
- Data that optimize productivity across industries through predictive maintenance on equipment and machinery
- Data that provides critical communication between self-driving cars
- Data that creates truly smart homes with connected appliances
Need of AI:
That’s the good news, but it’s simply impossible for humans to review and understand all of this data with traditional methods, even if they cut down the sample size, simply takes too much time. The big problem will be finding ways to analyze the deluge of performance data and information that all these devices create. Finding insights in terabytes of machine data is a real challenge!!
To harvest the full benefits of IoT last mile (data), we need to improve:
- Speed of big data analysis
- Accuracy of big data analysis
When the IoT enabled devices and sensors are integrated with AI, it helps companies take the billions of data points, that are really accurate and meaningful. These data help to explore the potential problems, which data can be used and which is not of use. The data captured is huge and to identify the which one to use, it is very necessary to find out similarities, correlations, and abnormalities based on the real-time streams of data.
Now, the collected data are combined with AI to simplify the task, with the help of intelligent automation, proactive intervention and predictive analytics.
AI in IoT Application:
- Cognitive systems will create new recipes that appeal to the user’s sense of taste, creating optimized menus for each individual, and automatically adapting to local ingredients.
- Visual big data, for example – will allow computers to gain a deeper understanding of images on the screen, with new AI applications that understand the context of images.
- Newer sensors will allow computers to “hear,” gathering sonic information about the user’s environment.
- Heart beat data collected by wearable if found irregular will send the closest ambulance to you while notifying the hospital and your doctor. It then starts and drives your doctor’s autonomous car (an IoT device itself), delivering him or her to the hospital as quickly as possible. So, adding AI to IoT could save the critical minutes to keep you alive.
- Agriculture data collected from the field will predict the crop health & the yield.
Not all the IoT application is supported by Artificial Intelligence, however, there are few applications that have increased the capability of the product and services.
As we understand, how IoT leverages huge potential to render personalized service and has drastically changed the way, “how people live and think.” For instance; e-commerce website provides personalized suggestion to the customer based on the customer shopping behavior.
Challenges facing AI in IoT:
- Ethical and legal Issues
What is Next …?
The Gartner report reveals that by 2018, 6 billion connected objects will be requesting support – meaning that strategies, technologies, and processes will have to be in place to respond to them. It will become necessary to think of connected devices less as ‘things’, but more as customers and consumers of services in themselves – and as such in need of constant support.
The figure clearly states that in the coming future, the demand for AI will increase considerably as the number of IoT enabled devices and sensors will grow unexpectedly.