IoT Architecture: 4 Layers of IoT Explained in Detail

A lot has been said about how we are progressing towards a smarter tomorrow. And in these statements, definitely, IOT is mentioned a lot of times. So what is all the buzz about IoT, and what is it actually? Stay tight and read this blog to know more about IoT.

IoT in a Nutshell 

First of all, IoT stands for the Internet of Things that contains things that are connected to the internet. These objects sense the environment around them and collect data that is used for further processing. These unprocessed data generated in huge quantities are converted to a digital format and then pre-processed for further analysis.

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Then comes the devices that actually process these data to draw valuable insights from them. Lastly, the processed data is then sent to the cloud or local machines, where they are stored and analyzed for performing actions. IoT is a four-step process. 

IoT architecture stages

Steps Involved

There are 4 main layers of IoT architecture, as shown above. Let’s go through each of them in detail. 

Sensors

Sensors belonging to the primary level of the IOT architecture is responsible for capturing the physical parameters in the real world. The parameters can be — temperature, smoke, air, moisture, etc.

These can either be embedded devices, i.e., multiple sensors present in a single board or a standalone device to collect and measure it. An example of an embedded sensor would be a sensor that measures methane content, carbon monoxide percentage, and the presence of smoke together.

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Whereas a humidity sensor would be an example of a standalone sensor. With sensors, actuators also play an important role in this layer. Their task is to convert the data generated by IOT objects into physical action.

For instance, consider a smart fan. With suitable sensors in place, the actuator would increase or decrease the fan’s speed based on the surrounding temp(which will be measured by the temperature sensor). And all of this would happen without human intervention. Another example can be a smart irrigation system.

After measuring the moisture content in the soil, the sensors would trigger the actuators that will decide whether to turn the valve on or off. A lot of research in IOT is currently directed towards integrating as many as possible sensors in a given board. 

Data Acquisition System

This layer works closely with sensors and actuators. But because of its unique functionality, it deserves a place in a separate layer. It is a connecting layer that connects the sensor layer with the analytics layer.

Its main function is to collect, select, and send the data to further processing layers. Before processing can happen, the data from the sensor must be converted into a suitable format. A format that is easy to use and also transferable. This is achieved by this layer.

For example, consider a sensor that measures light intensity. It takes to input the photons or the light in the form of volts like 10V, 5V, etc., and produces a digital output as some number. Similarly, color sensors in color intensity as input and output an RGB range from 0–255.

These are also called gateways, and they provide a platform for local processing of the incoming sensor data so that it is ready for further processing. To improve the security of this layer, suitable encryption and decryption algorithms are used that prevent malicious activities like a data leak.

A good example of a device in this layer is an Analog to Digital Converter or ADC. The measurable parameters in the surrounding, like light, sound, temperature, etc., are analog in nature. ADC converts these analog values into digital values. 

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Analytics

Not every IOT architecture may have this layer. Their presence can bring added value to the entire process, especially for large scale projects where data is generated in plethora. For such projects, data transfer rate or rate of analytics plays a vital role. These infrastructures are located close to the source of the data.

This allows them to act promptly on the incoming real-time data and provide an output in the form of actionable information. In this case, those data that require processing in the cloud are passed to this layer. As data transfer happens in this layer, it is imperative to increase security by minimizing network exposure.

As only some preprocessing happens in this layer, it works with minimum power and bandwidth. One example can be to remove the presence of outliers in the data. There can be thousands of outliers in a million data points. Getting rid of them in an early stage would mean saving time in the final processing.

Data Centre

Data Centre is often regarded as the brain of the IOT architecture. They are intended to store, process, and analyze tons of data. With data analysis and machine learning algorithms in operation, this layer provides some useful insights about the data.

This kind of processing is heavier computationally than the analytics performed in the previous layer. If deployed and furnished properly, the data centers can provide business intelligence and recommendations to help users interact with the system.

This layer provides many benefits to the business, right from higher production rates to reducing energy consumption. They also provide lucid visualization in the form of pie charts, histograms, or graphs, for customers that help them make informed decisions about the business. 

Real-world example

Self-driving cars use IOT applications all the time. These cars are driverless and rely on their sensors for safe navigation from one point to another. Equipped with hundreds of sensors like LIDAR, cameras, gyroscopes, cloud architecture, internet, and many more, these cars sense their surroundings and make rapid and intelligent decisions based on the sensor outputs.

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For instance, in a pedestrian case, the camera constantly takes input frames and passes them to the cloud for processing. A human detection algorithm then detects the presence of a human. If there exists a human, the controller then sends a signal to the brakes. In this way, information from one sensor is moved to the cloud and then to the actuator in the internet presence.

Conclusion

In reality, the IoT architecture may vary from solution to solution. But mostly, these four fundamental blocks are present. One must also design a functional and scalable solution and not prone to break down while processing tons of data.

Deployment of IoT solutions in business has allowed them to extract more value from the data and cater to their customers accordingly, thereby outperforming their customers. It is important not to get confused by the technical jargon of IoT and not lose sight of the endless possibilities and changes that can bring complete automation.

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