IoT Platform Decoded: 3 Major Types You Should Know

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IoT Platform Decoded: 3 Major Types You Should Know


We’ve all heard of IoT platforms as the lynchpin of the IoT ecosystem; but what exactly is an IoT platform? If you search for the term on Google, you could easily find millions of results and still be left confused by the end of the day. The truth is, not all IoT platforms are created equal; and the difference between them isn’t just about the bewildering range of use cases that they target.

IoT platforms can be categorized based on their core functionalities, with each platform type intended for distinct purposes and coming with varying features and services. Often times, different platform types will interoperate in an IoT system to deliver the complete suite of capabilities needed to end users. Understanding the different nuances of IoT platforms is crucial to determine which options are most relevant for your business. To help you better navigate the crowded and ever-changing IoT platform space, here is a snapshot of the three major platform types you should know.

[bctt tweet=”IoT platforms come in many shapes and sizes, with each platform type intended for distinct purposes and services.”]

1. Network and Device Management Platforms

As the name suggests, these platforms provide a tool for users to easily set up their edge networks, as well as connect and manage devices at scale. Rather than fine-grained data analytics and visualization, the key functions of a network and device management platform pertain to secure endpoint on- and off-boarding, connectivity monitoring and diagnostics, and automated software/firmware updates on devices. At the same time, it delivers an overview of all incoming traffic, alongside key hardware metrics (e.g. device ID, sensor type, gateway CPU and memory load, etc.), so you can stay on top of the network health and device status.

Depending on the vendor and connectivity type, this type of platform could be run either in the network operator’s proprietary cloud, in a public cloud, or in an on-premises data center. As such, it’s worth looking into what deployment options are available and whether they are aligned with your IoT strategy. For example, cloud deployment introduces high elasticity and scalability together with the flexibility to manage your network from anywhere, while on-premises deployment is ideal when stringent data privacy and ownership requirements apply.

MYTHINGS Central by BehrTech is an example of a network and device management platform.

You Might Also Like: 5 Reasons to Have an IoT Device Management Platform

2. Cloud Platforms/ Infrastructure-as-a-Service (IaaS)

Cloud platforms or IaaS solutions deliver inexpensive and scalable computing infrastructure like servers and repositories, so users can bypass the cost of installing and maintaining their own data centers. While cloud platforms provide the ability to ingest and store vast data streams, there are no tailor-made IoT applications available to analyze and transform this raw data into user-friendly and actionable insights.

In addition to the backend infrastructure, many cloud vendors also extend their offerings to include basic rule engine and tools that support third-party developers in building and hosting their applications in a cloud environment. That being said, there’s still a lot of in-depth development work to be done. So, end users will have to either implement a third-party IoT application platform or completely write their own enterprise application on top of the cloud infrastructure to really make sense of the data.

Microsoft Azure, Amazon Web Services, or IBM Watson are representative examples of IoT cloud platforms.

3. IoT Application Platforms

IoT application platforms come with built-in algorithms for varying services from basic data interpretation to complex machine learning and predictive analytics. Through intuitive visualization dashboards with 2D or 3D graphs, users can easily identify trends and patterns to act on their data. Event-based and/or predictive alerts can also be set up to notify abnormal behaviors and facilitate task execution.

Some IoT application platforms are fully out-of-the-box and customized to a certain set of IoT use cases. Provided as cloud-based software or Software-as-a-Service, they are often bundled with the supported devices in a single offering. Users don’t have to do any on-top programming or development, but there’s also a limit in terms of device and connectivity interoperability. Some even lack the ability to integrate with external systems for further data transfer. While not all, many of these platforms are used in Smart City and Consumer IoT contexts where usability and readiness are supreme. An example is the Samsung SmartThings platform for home automation.

On the other hand, IoT application platforms geared towards large-scale industrial and commercial deployments are mostly designed to be device- and industry-agnostic and can support data in different formats. These are referred to as Application Enablement Platforms (AEP). Quite often, there are powerful prewritten application templates for immediate data analysis and visualization in key IoT use cases. Concurrently, these platforms offer tools and services that enable developers to build and manage multiple tailored-made applications with minimal costs and complexity – many times, even without the need to code. Deployment models are typically flexible, and it is easy to integrate the platform with existing business systems and/or more advanced third-party analytics solutions.

Final Thoughts: Connecting the Dots

As you can see, each type of IoT platform discussed above is focused on a specific domain, and in most cases, it isn’t about selecting any one type over the others. Instead, they should be interoperable with each other through open interfaces and messaging protocols to deliver all key building blocks of an IoT platform architecture. Specifically, an application enablement platform can interface with one or many network and device management platforms to aggregate data from various sources for analytics and visualization in diverse use cases. Both of these can be hosted in the cloud infrastructure to capitalize on massive data processing and scalability at reduced costs. Through seamless integration, end users can easily manage all aspects of their network from a central interface to streamline operational tasks.

BehrTech is working with multiple cloud and IoT application enablement platform vendors to make MYTHINGS networks easily accessible and consumable for businesses. Our MYTHINGS Central platform for network and device management provides full backend integration with top-tier cloud platforms at the user’s disposal and a powerful plugin system to interface with compelling IoT applications to derive business intelligence.


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