In our last article, we discussed what IoT is, its history and how it became the spearhead of Industry 4.0. But how does IoT work? What structures are necessary to implement IoT? What keeps data collection and conversion flowing?
1. Sensors and Actuators
Sensors and actuators go hand in hand and make up the baseline of IoT. At this stage, sensors collect data about their environment, and actuators act within that environment. For example, in an emergency situation, sensors might detect power has failed at the source and throughout a building. That information then directs the actuator to turn on the backup generator. Sensors continue to monitor power and inform the actuator to turn off the generator when normal operations have been restored. There are different types of actuators with different ranges of motion and force, so they can perform in a multitude of situations, usually involving pumps, switches or valves.
2. Internet Gateways and Data Acquisition Systems
Sensors collect massive amounts of data and in analog form. At the second stage, acquisition systems process that data into manageable sizes and convert it into digital formats. They also filter the data and select only vital information, reducing the amount to be processed and stored. Gateways transfer data over Wi-Fi, LANs or via internet. They can also work in the opposite direction, pulling commands from the cloud or distributing firmware updates. Network protection is critical at this stage as data is transferred.
3. Edge IT Systems
Though not a requirement for every IoT architecture, edge devices offer significant advantages in IoT optimization. They work as a field-based counterpart to the cloud, taking in data for further processing and analyzing. This reduces bandwidth consumption and latency for cloud data transfers and allows for faster transfer speeds. Edge devices also reduce cloud storage consumption.
Edge computing’s ability to quickly process and analyze data on site makes such systems crucial for real-time analytics and actions. It also plays a large role in machine learning. For example, edge computing allows a camera to detect devices or faces near-instantly or a microphone to process languages in real time.
Security can also be improved with edge computing by enabling related data to be stored on the device instead of sending it over the network.
4. Data Center and Cloud
The cloud is the main stage for data processing and feedback, with the ability to store and process data on a greater scale than edge devices (though slower). Data can be pulled from sources other than sensors, and hybrid cloud computing (connecting a private cloud to a public cloud) is also an option. The cloud can be a management system for software and security updates.
This is also the stage for human interaction with the IoT system. Here, the system can be monitored, and non-immediate decisions made based on analytics. An additional human interface system, such as an app or software, might be a fifth stage of IoT data collection, conversion and transfer.