5 Principles that Support the IoT Theory

Internet of Things is gradually spreading its wings to offer a comprehensive solution for different requirements. You will see that there are certain pillars that support the internet of things theory, which strengthen its need in offering a convincing solution.

Here, we will discuss 5 principles of Internet of Things that will help offer a perfect solution.

A major chunk of the data that you use on a daily basis is analog data. Right from temperature to sounds to radio signals and velocity, all are available as analog data. While it represents one of the oldest forms of data, it poses an IT challenge to capture record and analyze this data. You need to understand that analog and digital data differ from each other. Internet of Things offers a methodical approach towards capturing and recording the analog data, thus proving to be a major support to the solution.

Internet of Things keeps you connected to the different products and users at all times. As a result of this, you get the 3M benefit- Monitor, Maintain and Motivate. You can monitor the product/user continuously thus gaining access to real time knowledge of the products. You can push in upgrades, fix patches and even offer to manage the products as a result of monitoring. As you are always connected to the users, you can motivate and direct the workers towards offering the best possible solutions. It works more on the principle of predictive analytics, as a result of which you can offer solution as and when you forecast problems.

The IoT definition of real time differs from that of other solutions. In IoT, real time begins even before the data is acquired by the computer system. The moment the data is captured by the device, is when the real time begins for IoT. This means, you are able to get a solution as soon as you are struck with the problem. It does not wait to be transferred to the device. Such is the real time in case of IoT solutions.

The data in IoT flows through five phases: real time, in motion, early life, at rest and archive. These five phases contribute towards data acquisition real time, and finally monitoring and predictive analysis of the data. The archived data can be easily retrieved for comparative analysis at the end of the spectrum, and can help towards offering better insights on the problem. This will help benefit in acquiring the right solutions.

When the data is collected, what it typically needs in an Internet of Things framework is visibility. The transfer of the data should be possible across locations, and should be made accessible even in the remote locations.