The term IoT has been serving us in obscurity, allowing us to communicate and manage our lives through internet connections while connecting remotely. However, under the premise of understanding that the Internet of Things is serving us, it is necessary to understand the future of the Internet of Things platform and even how to serve us.

The first is that the device acts as an information delivery platform and this will tell the users of the IoT platform about their behaviour, health, and even some personal preferences of the user. These data are all good for the IoT platform. Although it is very valuable for companies to mine this data, but if they can not sort and study the data, it is useless. So, this is one of the reasons why machine learning and algorithms are so popular today. Through the combination of machine learning technology the companies can obtain accurate information about users.

So, what exactly is the Internet of Things platform? How do users and enterprises choose an Internet platform?

In a broader sense, the IoT platform is a complete set of tools and services that help developers create applications. For this we need to understand how Uber works. Uber will look for the use of taxis around us while their users are using the app. Under this premise, Uber uses the IoT platform, machine learning technology and our mobile devices who provide information about our user behavior looking for a car, our location, and where we are going. Here, the IoT platform is our mobile device. Uber can use this information to understand people’s travel needs by using machine learning algorithms and even when it is peak time when the user is willing to pay.

This is the best case of how business intelligence can benefit the company, which is how machine learning uses it to increase profit margins. The Internet of Things has an intermediate link that takes data from sensors and devices and passes it to relevant people and analysis software to get useful data from it. Most IoT platforms provide well-defined APIs and SDKs to connect developers to any hardware platform and use their cloud services. Of course, the more data, the more complicated the processing. When companies are able to handle large volumes of data then implementing machine learning algorithms can help companies get better business intelligence solutions that help the public make better decisions.

So, good scalability becomes very important. In order to implement a large amount of data for machine learning algorithms then we must first find an IoT provider or hire IoT developer who can help obtain data. So the decision to choose an IoT provider becomes critical. When a large amount of data is obtained, the costs and risks associated with hardware and data security increase accordingly. In addition, when looking for suppliers, we need to consider scalability and the best performance of the platform. The scalable IoT platform allows us to connect to millions of devices with different technical requirements.
The platform is critical to the efficiency and quality of the data.

In addition, in the long run, M2M communication field and industrial information automation have become a necessary part of technological development. Data-driven operations have become routine operations and have led the Internet of Things to become more and more specialized. Of course, in order to provide a more complete automation experience, the IoT platform needs to support traditional and modern protocols.

No doubt, the pricing model is also very important. Platform providers should have transparent pricing policies in order to guard against vendors that provide reasonable referral rates. Of course, if you use the subscription mode, you must pay the subscription fee. If there is a need to sell hardware in the main business, then the license platform is used to prove the choice, and finally, it is included in the development cost by IoT development company.

In addition, vendors looking for an IoT platform need to adapt to the current IT technology environment and be hosted locally because the hybrid cloud approach has proven to be successful as compared to a single approach. The best thing about using a hybrid cloud is its good accessibility, and developers using this option can easily and quickly access private and public clouds. From our point of view, from the sensor node to the gateway to the actuator, the Industrial Internet has already included these things as a solution, and many devices no longer need to generate telemetry data to be processed. The platform issues commands to the actuators and sensors. After all, an efficient IoT platform maintains a clear separation of device and data management to facilitate communication between the consumer processing data and the consumption of data from different sensor nodes. Also, avoid using endpoints to forward messages from devices that are not associated with telemetry data sets. When these messages have a clear separation then the effective M2M communication and data ingestion layer may increase.

To conclude, most importantly as technology advances, the Internet of Things is improving the way users and devices communicate and the way the global economy operates. Choosing a good IoT platform will give us an idea of the importance of the right IoT platform to help us make more targeted decisions.

About the Author

Chandresh Patel is a founder & M.D at Bacancy Technology. He is a founder of vision and mission of Bacancy Technology and constructed work ethics @bacancytech to achieve that vision and mission. He oversees Business development, day to day execution of strategic planning and he also looking after customer service delivery. Right now his main focus is on expanding his business globally and he is putting all his efforts to make his company known worldwide.