The Internet of Things concerns the mass connectivity of several devices including consumer products like watches, wearable technology, remotes, tabs, home appliances, as well as sensors, and more, with people using them. The solution is designed to capture data from the devices and send the captured data to data centers and servers for further analytics that drives actions and automation.
The IoT architecture plays a crucial role in guiding the data to its right path, defining the format to use, and what action to take.
What is IoT network architecture?
It is a network system of several elements such as sensors, actuators, cloud services, protocols, and IoT architecture layers. Different layers let administrators evaluate, monitor, and maintain system consistency. The system design plan is carefully integrated with the existing infrastructure systems for optimal impact.
Organizations with great IoT architecture have a better chance of improving business processes and driving better outcomes. Such organizations are known to maintain an IoT system architecture that is customized to specific IoT projects, as well as other general-purpose Internet of Things architecture formats.
In addition to this, the system includes IoT architecture layers that help in tracking system consistency. In fact, the layers need to be put in place long before the process of IoT architecture framing begins. A common IoT architecture would be made up of these 3 layers:
- Perception, or the IoT Device Layer – the client layer that collects data;
- Network, or the IoT Gateway Layer – the server-side operators who connect devices to smart objects, servers, and network devices;
- Application, or the Platform Layer – the final application that connects the operator, and the client;
These layers ensure that the IoT architecture is fully functional, scalable, available, and maintainable.
Once this is achieved, we move on to the 4 stages of the IoT architecture layout:
- Stage 1: Sensors and Actuators;
- Stage 2: Gateways and Data Acquisition Systems;
- Stage 3: Edge IT Data Processing;
- Stage 4: Datacenter and Cloud;
A more detailed review of each of the 4 stages of IoT architecture follows:
Stage 1: Sensors and Actuators
Sensors and actuators are the connected devices that monitor, and control the physical processes respectively. Sensors capture process status data or the environmental conditions such as humidity, temperature, fluid flow in a pipeline, the fluid level in a tank, and so much more. At times, some of the condition data requires an immediate response by the actuator to carry out real-time remediation actions. An example is that of adjusting the liquid flow rate to maintain a consistent level.
It is crucial to maintain low latency between Sensors, and the data analysis to trigger the actuator’s action. Data processing is carried out in close proximity to monitor, and control system to avoid delay in data relay to the server, its analysis, and the final signal to control the ‘thing.’
Stage 2: Gateways and Data Acquisition Systems
The data sent by the sensors is collected by a Data Acquisition System (DAS) and converted into a digital-analog format. The DAS aggregates and formats this data before it sends it through Internet gateways such as wireless WAN as in cellular or Wi-Fi, or wired WANs for the next stage of processing.
In the case of industrial, and factory settings, the data at this stage can be enormous with 1000s of sensors gathering them simultaneously. This necessitates data filtration and compression to an optimal size before its transmission.
Stage 3: Edge IT Data Processing
The IoT data that has been digitized and aggregated undergoes further processing before reaching the cloud center. The edge devices carry out advanced analytics and pre-processing, sometimes using Machine Learning and visual representation. Machine Learning helps provide ever-improving feedback into the system and further improves the process without waiting for instructions from the cloud data center. Such processing is often carried out in a device that is close to the sensor, such as in an on-site wiring closet. This stage then enables data capturing at the local sensors and its transfer to remote locations after analysis and processing.
Stage 4: Data Center and Cloud
In this last leg, data centers carry out in-depth processing with the help of high-end applications designed and run by skilled analytics professionals. Powerful IT systems analyze, manage, and store data in the cloud, or corporate data centers. Here, multiple site sensors combine to give a broader picture of the overall IoT system, and its deliverable actions. When operations are spread across geographies, these cloud data centers analyze and identify key trends, patterns, or spot anomalies to help optimize operations.
This is the stage when a company or industry-specific application carries out an in-depth analysis with unique or custom business rules in mind to determine the course of action to be taken. The incoming data may indicate that changes be done to device settings or suggest other corrective measures to optimize processes. It is part of a continual development loop that also stores data for future analysis.
The Internet of Things is fast evolving and improving business processes across industries. The ground reality of the process is definitely enhanced by an apt IoT architecture that maintains data, analyzes it, and signals corrective action. As we have seen, the IoT system architecture is laid out across 3 layers i.e., device, gateway, and platform. That then cascades into 4 stages that capture data, analyze, process, and suggest corrective measures using high-end applications. This elegant combination comes together to deliver powerful value in automated action.