The term Internet of Things (IoT) refers to the collective network of connected devices, a technology that facilitates communication between devices and the cloud as well as between the devices themselves.
What is IoT Architecture?
Due to the evolving nature of IoT devices and the wide variety of sensors, there is no one-size-fits-all architecture for IoT projects. However, some building blocks are similar across projects.
First, you need to build with scalability in mind. Over time, the amount of data you’ll collect will be a huge percentage, and you’ll need a platform that can accommodate that data in the long run.
You also need to ensure high availability at any given time. A system failure could cost you some business at best, or could be fatal at worst.
In the end, you will need a system that is flexible enough to accommodate rapid and frequent changes. As your architecture evolves or your business needs change, you’ll need to iterate quickly without breaking your existing architecture.
These requirements make MongoDB the perfect choice for processing and storing data in your advanced IoT architectur With a MongoDB cluster, your replica sets will ensure your servers are highly available. MongoDB’s sharding capabilities are also key to easily scaling your application as needed. Additionally, flexible data schemas are ideal for storing ever-changing data.
What are the three principal layers of IoT architecture?
Granted, no two IoT projects are the same, but the key layers remain the same. The three layers are perception (or device), network, and application.
Perception: The sensors themselves are located in this layer. That’s where the data comes from. Data can be collected from any number of sensors on connected devices. Actuators that act on the environment are also located at this layer of the architecture.
Network: The network layer describes the amount of data moving throughout the application. This layer connects various devices and sends data to appropriate backend services.
Application layer: The application layer is what the user sees. This could be an app for controlling devices in a smart home ecosystem, or a dashboard showing the status of devices that are part of the system.
What are the other five layers of the IoT architecture?
For this reason, many proposed architectures have other or additional layers. A common architecture is called a five-tier architecture, which includes the transport layer, processing layer, and business layer replacing the detection and application layers and networks of the three-tier architectural model.
A three-tier architecture is a good way to describe. For this reason, many proposed architectures have other or additional layers. The common architecture is referred to as a five-tier architecture and includes the transport layer, processing layer, and business layer, which replace the recognized application layer and network of the three-tier architecture model.
What are the four main phases of IoT architecture?
Another way to describe the architecture of an IoT solution is to use a four-phase approach. The architecture describes the various building blocks that make up an IoT solution. In this case, more emphasis is placed on edge computing compared to other proposed designs.
Devices: This phase is about the actual devices in the IoT solution. These devices can be sensors or actuators in the perception layer. These devices will generate data (in the case of sensors) or act on their environment (in the case of actuators). The resulting data is converted in digital form and transmitted to the internet gateway stage. Unless a critical decision has to be made, data is usually sent to the next stage in its raw state due to the limited resources of the device itself.
Internetr Gateway: The Internet Gateway section receives raw data from the device and pre-processes it before sending it to the cloud.
This internet gateway can be physically connected to a device or a standalone device that can communicate with sensors and relay data to the internet over a low-power network.
Edge or Fog Computing: To process data as quickly as possible, you may want to send data to the edge of the cloud. This will allow you to quickly analyze the data and determine if it requires immediate attention. This layer typically only focuses on the latest data needed for time-critical operations. Some preprocessing may also be done at this stage to limit the data that is ultimately transferred to the cloud.
Cloud or Data Center: In the final stage, the data is stored for later processing. The application and business layers are at this stage, and dashboards or management software can be fed with data stored in the cloud. Deep analytics or resource-intensive operations such as machine learning training will take place during this phase.
IoT Architecture in Business:
IoT use cases are diverse and can take many forms. Commercial airlines have many planes, and each plane has a large number of sensors.
The perception layer consists of all sensors in the plane. These will indicate the current status of the aircraft, as well as data about the current flight. Sensors will monitor information such as altitude, position, airspeed and vertical speed. Other sensors are collecting data to ensure the integrity of the plane is in good shape, monitoring feedback such as engine vibration.
This data, which comes from a number of different sensors from different manufacturers, will be sent to a central unit on the aircraft as part of the network layer. This data will be converted into a standard format and preprocessed there. If a critical event occurs, such as an engine failure, the executor will be triggered immediately instead of waiting for a full round trip to the cloud. Once the aircraft is connected to the internet, the data will be sent to the cloud and moved to the application layer.
IoT Architecture in MongoDB Atlas:
The key to a successful IoT architecture is finding the right way to process the massive amounts of data generated by the perception layer. MongoDB’s Database-as-a-Service offering, MongoDB Atlas, provides a set of tools for all layers of an IoT solution.
Once the data leaves the device and enters the network layer, MongoDB Atlas can provide you with several ways to configure the server to be close to the device. You can even deploy MongoDB at the edge by enabling MongoDB data locality and workload isolation on edge clusters. You can use MongoDB 5.0 native support for time series to store your data in collections that are ideal for IoT applications because they are optimized to collect measurements over time from a variety of sources. You may also need to be prepared for bad internet connections. Atlas App Services can help you do this by giving you offline-first syncing.
For your application layer, MongoDB also provides you with connectors to platforms like Spark for your machine learning and data analytics needs. You can also use MongoDB Connector for BI to connect to your BI tools, or use MongoDB Charts directly to create dashboards and get visual representations of your data.