Before implementing IoT in any business process, it’s important to know how we are going to design the layout. Let us first understand what IoT architecture really is.
We know what value IoT brings to the table for improvising business processes across industries. But when it comes to reality, the implementation is too complicated. To deal with these issues, it’s better to find a reliable IoT Edge solutions provider. It will help in significantly reducing the number of resources spent.
IoT architecture essentially comprises of a number of elements: firstly, cloud service, then layers, protocols, sensors and devices and so on. To simplify it further, there are 4 components to it.
Additionally, IoT comes with layers for tracking the system consistency. These layers need to be considered way before IoT architecture process begins. Now what are the three main layers of IoT architecture:
- IoT Device Layer – which is nothing but the client layer
- IoT Gateway Layer – that is server-side operators
- IoT Platform Layer – to connect the operator and client
The fundamental features of a stable Internet of Things architecture include: functionality, scalability, availability, and maintainability. We first need to address the layers at the beginning of the IoT architecture. If ignored, it may result in failure.
Coming back to the 4 Stage IoT architecture which are:
- STAGE 1: Sensors and actuators
- STAGE 2: Internet gateways and Data Acquisition Systems
- STAGE 3: Edge IT Data Processing
- STAGE 4: Datacenter and cloud
Here is the pictorial representation of the stages:
Let’s now understand the high-level architecture:
Stage 1. Connected devices (sensors/actuators)
The best thing about sensors is that it can convert the information it senses into a set of data which we can process further for analysis. Alternatively, it’s important to start including sensors in the early stages of IoT architecture framework to get information that we need to process.
This process goes even further for Actuators. They can decide and take actions based on the information they gather automatically. Example: Switching on a light when someone enters the room, or temperature regulation, etc.
In this stage, we can make use of hardware and gain necessary insights for further analysis.
Stage 2. Sensor Data Acquisition
We understand at this stage that IoT deals with working with sensors and actuators in close proximity. Internet gateways and Data Acquisition Systems (DAS) plays an important role here as well. DAS aggregates output by connecting to the sensor network. On the other hand, Internet gateways work with Wi-Fi, wired LANs and perform further processing.
This stage is important to process the information collected from the previous stage and compress it to the optimal size for further analysis. On top of this, timing conversion and structure conversion happens at this stage.
Eventually, Stage 2 helps to make data aggregated and digitized.
Stage 3. The appearance of edge enabled IT systems
Here, in this stage, we transfer the data that we prepared in stage 2 and expose them to the IT world. To be precise, the edge IT system performs enhanced analytics here along with pre-processing. Particularly, machine learning and visual representation.
Some additional processing may also happen here before the data is entered in data centers. Step 3 enables data to be captured at local sensors and at the same time transferring the data to the remote locations.
Stage 4: Analyzing, Visualizing and Storing Data
Here, in the last stage, data is processed in depth in the data centers. This stage requires skilled analytics IT professionals along with high-end applications. Data might also be gathered from other sources for execution. Once all the quality standards and requirements are met, the information is then brought back to the physical world for predictive analysis.
Would you like to implement Stage 5 to your IoT Architecture?
You may also want to extend the process by including human intervention as an extra stage for actions or approvals. It initiates a user’s control over the existing process. The process may not require to be fully automatic. The important task here would be visualizing and managing the existing process, sending commands to the sensors and going back into the loop.