IoT has been with us for many years in different forms. It facilitates remote connect, allows us to communicate and manage devices with an Internet connection. The right IoT platform can serve you in many ways, but first, we need to understand its meaning. To understand what IoT is and how it works, we have to understand how it fits in the larger picture.
Devices act as transmitters of information. They tell companies about your behavior, your health (think FitBit) and your likes and dislikes. These devices come under the realm of IoT. While it is great that companies can mine this data, it is virtually of no use to them if they cannot sort and study the data.
This is where machine learning algorithms come in. With the combination of machine learning concepts like supervised and unsupervised learning and IoT, companies can get exacting information about their customers. These are great and interesting concepts to learn, and if you want to learn more about these concepts and integrate them into your company’s operations, you can enroll in a machine learning certification course.
What is an IoT platform?
In a broader sense, an IoT platform is an integrated set of tools and services that help developers create applications.
Let’s think of how Uber works. Uber works when you use the app to look for taxis around you. In this case, Uber makes use of both IoT and machine learning. Your cell phone is the device that gives Uber information about your behavior, what you look for (a taxi), where your location is, how likely you are to cancel if the cab is too far away, so on and so forth. Here, IoT is represented by your mobile device.
By making use of machine learning algorithms, Uber can use this information to understand when people seek transportation most and how much they’re willing to pay (thank you, surge pricing). This is how business intelligence benefits companies. This is how companies who understand what machine learning is make use of it to increase their profit margins.
To simplify it, an IoT platform is a middleware layer that takes data from sensors and devices and delivers it to people and analytics software so as to derive insights. Most IoT platforms offer well-defined APIs and device SDKs that connect developers to any hardware platform and use their cloud services.
Buying an IoT platform is a critical decision that can impact an organization in many ways. This post maps out all the important points that could help you to select the right IoT platform.
The more data grows, the harder it becomes to handle. This needs to be fixed immediately. When companies can handle large amounts of data, then implementing machine learning algorithms can help derive better business intelligence, which in turn, can help make better decisions.
Therefore scalability becomes important. In order to implement machine learning algorithms to large amounts of data, you’ll need to first find an IoT vendor who can help get that data. Hence, the decision to choose an IoT vendor becomes critical. With enormous data, the costs and risks related to hardware and data safety increase as well. It doesn’t matter if you aren’t connecting to millions of devices right from the start, it is important to ensure that your IoT platform is capable of handling data loads.
When looking for a vendor, you need to consider scalability and the optimal performance of a platform. A scalable IoT platform allows you connect to millions of devices, which have different technological requirements and delivers insights using data without putting at stake quality and efficiency.
Support for Protocols
For a long time, M2M communication and industrial automation have existed. With the help of data-driven operational insights, IoT makes industrial automation a better and more exact field. In order to deliver a complete automation experience, IoT platforms support legacy and contemporary protocols. Moreover, an IoT platform should offer protocol translation. SCADA based RTUs and PLCs are still in trend for automation on existing platforms. The use of BACnet, Modbus, and Canbus is common by devices for communication. In short, an IoT platform should support existing and emerging protocols.
The pricing model
The platform provider should have transparent pricing policy. Beware of those vendors who offer reasonable introductory rates and then increase it when you do sign up.
If you are going for a subscription model, then you can cover the costs in subscription pricing. If you are into selling hardware then you can go for platform option with a license in order to wrap that into the development costs.
Look for the vendor who offers an IoT platform that fits well in your present IT landscape, mostly hosted on-premises. As compared to the singular approach, the hybrid cloud approach could prove to be successful. What makes the hybrid cloud best is the accessibility it offers. Companies who use this option can have access to both the private and public cloud. The latency and access time of operations reduces significantly when requests are not pushed through the public network.
From sensor nodes to gateways to actuators, the device layer of an industrial IoT solution contains them all. Many devices do not produce telemetry data that needs to be processed. The platform would give commands to actuators and sensors on which they act upon. An efficient IoT platform keeps a clean separation of device management to deal with data ingestion endpoints and M2M communication that consume data from different sensor nodes.
Refrain from using typical M2M endpoints that reveal MQTT for ingesting telemetry data. Also, avoid using endpoints for forwarding messages from devices that don’t associate to the telemetry datasets. When these layers have clean separation, efficient M2M communication and data ingestion layers are likely to proliferate.
With recent advancements, the internet of things will refine the way we interact with each other, and how the global economy functions. To be successful, a scalable and integrated platform is needed. IoT machine learning is also beneficial in shaping our environment according to our needs.
When selecting an IoT platform, you need to feed your requirements and constraints to the vendor. This vital step will explain the importance you keep on your IoT platform and therefore help to make a more targeted decision.
With 100s of self-proclaimed IoT platforms in the market, the only way to truly know each platform is to use it.
MIT E (MachNation IoT Test Environment) compares IoT platforms, producing 1000s of data points rating 70+ developer and operator workflows.
IoT platforms evaluated: Altizon, AWS, Bosch, Cumulocity (Software AG), Predix, Google, IBM, Microsoft, Sierra Wireless, thingsboard.io…
24 microservices tested
71 developer workflows
284 datapoints per vendor