Why IoT needs AI to work
A vast network of interrelated sensors, actuators, physical objects, services, and other internet-powered devices produce voluminous data every day. These connected ‘things’ are self-sufficient to transfer this data on their own.
With such ever increasing connected devices, the Internet of Things (IoT) will keep producing treasure trove of Big Data that holds potential to provide insights for enterprises. The real challenge here lies not in collecting data, but in analysing the humongous amount of generated data that is of no use unless there is a way to understand it. This is where Artificial Intelligence (AI) comes to the rescue.
AI helps in bringing sense out of that limitless and mountainous amount of data by acting as a catalyst for informed decision-making. Both IoT and AI are changing business landscapes with automated, intelligent and efficient practices; however, companies need to combine both these technologies to realise the full potential of this technological advancement cited as the fourth industrial revolution by industry experts.
According to Gartner’s forecast, there would be more than 20 billion connected things by 2020. Other reports estimate the healthcare IoT alone to be worth $117b by 2020.  The data produced by IoT and processed through AI can lead to a variety of benefits to both companies and consumers in the form of personalised experiences, proactive intervention and intelligent automation.
For instance, Pandora using predictive intelligence to determine what other songs you may like based on your prior song list or Amazon suggesting you other similar books and movies learning from your previous choices. Wearable device market is already a burgeoning industry and soon these devices will be connected to the internet, which will provide real-time updates to health services so that doctors will be able to get real-time insights into information from biochips and pacemakers. This will help create truly smart homes with connected appliances and provide critical communication between self-driving cars too.
The merger of IoT and AI enables business to find ways for connected devices to work together and make these systems easier to use. This in turn would lead to higher adoption rates, which inevitably demand improvised speed, accuracy and data analysis by AI in order for IoT to function at its full potential. As rapid expansion of IoT continues, the sheer volume of data created will hold extremely valuable insights into business risks and opportunities by analysing what is working and what is not with the help of associations and correlations drawn.
It is clear that IoT is quite impressive though realisation of it depends on being able to gain the insights hidden in the vast amount of growing seas of data. Without a good AI system, this goal would be difficult to reach and hence both IoT and AI need to reach the same level of development in order to function to its fullest potential. Since current approaches do not scale to IoT volumes, the future realisation of IoT’s promise is dependent on AI to find patterns, correlations and anomalies that have the potential to improve business decision making as well our lives.
Hence, integrating AI into IoT network is a prerequisite for success and businesses must make use of it to allow machines point out where the opportunities are and drive value from the integration.