It is difficult to find anyone who is aware of the ‘Internet of Things’ and isn’t aware of its key effects to the future. Studies have recently suggested that by 2020, the global IoT market will be worth more than $1.3 trillion with a CAGR or 16.9 percent. The world has already started experiencing IoT equipped devices in homes and offices, and the number of these devices will surpass 50 billion in next three years. These figures are good enough to avow the claim that IoT market is going to get bigger with time, and the success of IoT, in the long run, will be very much determined by machine learning. Machine learning is a word buzzing in the technology industry right now, and for the right reasons. It represents a major leap forward towards understanding how computers can learn. Before going into details, let’s take a look at how both of these terms are related to each other.

IoT & Machine Learning

IoT is nothing but the inter-networking of devices in such a way that they can send and receive data automatically without any manual interference. Due to this data automation, IoT saves a lot of time and efforts, resulting in higher productivity and better user experience. Machine learning, on the other hand, is a type of artificial intelligence that enables computers to learn quickly without being programmed explicitly. It automates the data analysis process and enables computers to learn from data using novel algorithms and hidden insights.

One of the examples of machine learning can be self-driven cars from Tesla & Google. In a recent survey of top auto executives by IBM, 74 percent expect to see smart cars on the road by 2025. This smart car would not just integrate the Internet of Things but also learn from its environment and its user. Adjustments of settings, accessing features like audio control, temperature and seat positions will be automatic based on user and can even fix problems and offer real time traffic information.

In an IoT based environment where terabytes of data need to be, it becomes important for machine learning to keep up with IoT data and generate insights from it

Can Machine Learning Determine the Success of IoT?

The sole reason behind why IoT witnessed a massive success in such a quick succession is because it has the potential to make everyone’s life easier and more hassle-free than ever before. Machine learning is another in-demand technology just like the internet of things and can kick your IoT efforts up a notch by integrating predictive analytics. What if one could be automatically alerted to and be able to take action on an issue or a business opportunity before it even happens? That’s the potential of Machine Learning for IoT.

In an IoT based environment where terabytes of data need to be analyzed for capturing value, it becomes important for it to adopt machine learning to keep up with this IoT data and generate insights from it. Machine learning is perfectly capable of taking the billions of data points, review them, analyze them and unlock patterns or recurring trends. Doing this in an enhanced way without adding to cost overheads will make machine learning a key success driver in IoT.

Are there Any Barriers?

Although IoT has opened new doors to success for businesses, there are many unanswered questions which need to be addressed soon. With the passage of time, the data volumes and varieties will continue to increase. In order to compile it quickly in an efficient manner, and use for attaining organizational objectives, businesses will need to learn the proper application of IoT and Machine Learning as soon as possible.