Introduction
Applications for Internet of Things (IoT) technology are many, and their use is expanding fast. The IoT operates by how it was created or constructed depending on the many application areas. But, it does not have an adopted, standard-defined architecture of working. The functionality and application of the Internet of Things affect its architecture in many industries. IoT is still built on a fundamental industrial flow, though. So in this post, we will cover the 4 Stage IoT Architecture, which is the basic IoT architecture. Know how an IoT architecture should be in detail.
What Is IoT Architecture?
There are lots of ways to look at IoT architecture, and each IoT system differs from the others. All follow the same fundamental structure and flow, despite all the differences. IoT architecture requires four key components: edge computing (often a component of a cloud platform), a processing system (often a component of a cloud platform offering), and a cloud-based or local data centre. It stores, manages, and analyses the data. Connected hardware "things" collect and process data via sensors and controlling devices at the edge. Knowing this architecture is the basis of any IoT certification course.
A Reference Architecture's Requirements
There are several particular requirements for the IoT that are special to IoT devices and the environments that enable them. For instance, many requirements result from the constrained form factors and power that IoT devices can use. Other requirements result from how IoT devices are created and used. Compared to current Internet approaches, the methods are more in line with designs of conventional consumer goods. You must follow several current best practices for server-side and Internet connectivity. Take these practices into consideration for better outputs.
Four Layers of the IoT Architecture
Internet of Things networks include many uses and components for cloud computing. But the majority of these IoT solutions are based on basic ideas, and these IoT Elements serve as the cornerstone of almost all IoT systems in use today. To enhance the entire IoT network, they are divided into various architecture layers. An IoT course explains these layers in detail.
These four IoT architecture layers, each serving a particular purpose, are necessary for IoT solutions to function well.
1. Device Layer
In the IoT architecture, the sensing layer comprises devices, sensors, and actuators that gather information from their surroundings and manage objects at the edge. An IoT ecosystem's base layer consists of devices that sense or control things in the physical world. IoT is being used by companies in almost every sector, and there are always new use cases emerging. We can gather data using sensors in IoT devices, and then we can send it to the server. It is not essential to link the devices and sensors in IoT devices. If the sensors are placed remotely, it is still possible to collect data and transfer it.
Examples of direct connections are:-
- Arduino equipped with an Ethernet port
- With a Wi-Fi connection, an Arduino Yun
- Ethernet or WiFi connections to the Raspberry Pi
2. Communication Layer
The second layer is a network layer that carries information from the device layer to the internet. It is often via a gateway that may carry out extra processing and sometimes aggregates connections from many edge devices. This layer may do some processing and decision-making and security capabilities including authentication, encryption, and virus prevention. Sharing a few distinct instances will help you grasp this layer the best. LoRaWAN sensors that connect with a gateway for what is referred to as edge processing make up a common topology that we see. The data is then transmitted from the gateway via cellular connectivity to the cloud.
The three most popular potential protocols are:
- HTTP/HTTPS (and RESTful approaches on those)
- Constrained application protocol (CoAP)
- MQTT 3.1/3.1.1
3. Cloud Ingest, Data Storage and Processing Layer
The data processing layer is set up to handle pre-processing and data analysis. This layer could be found inside the gateway or outside it, depending on the application and implementation. Applications for edge analytics can access this data in use cases like driverless vehicles when real-time data is required. While the processing is running, data is controlled and tracked. The data processing level receives data from edge devices and gateways, including images and readings from various sensors.
IoT-specific services are offered by cloud platform providers such as AWS, Azure, and others to help the ingestion and routing of data flow to the cloud. It will be simpler to handle and store this data and scale the infrastructure with more processing and routing power. The efficiency improves as the number of deployed devices increases. Understanding these concepts is a part of IoT training.
4. Application Layer
End-user apps consume data from the application layer, which is housed in the cloud. This is true even for edge computing, which always still communicates with the cloud for data that isn't needed right away. After the data has been processed in the cloud, it is used in applications for smart cities, smart farming, healthcare, manufacturing, fleet management, and other areas to track system performance, pinpoint issues, and do other things.
Each IoT system has distinct goals and objectives to fulfil business requirements. The majority of IoT apps perform specific tasks for enterprises while operating on different technology stacks and at diverse levels of sophistication. The above 4 are the main components of the IoT reference architecture.
The complex network of elements, including sensors, actuators, cloud services, protocols, and layers, that makeup IoT networking systems is referred to as IoT architecture. In most cases, it is separated into layers to enable administrators to assess, keep an eye on, and uphold the integrity of the system. The four-step IoT architecture involves the flow of data from sensor-connected devices, via a network, and into the cloud for processing, analysis, and storage.
Our Learners Also Read: What Is The Difference Between AI And IoT?
Why the IoT Reference Model?
A reference architecture for IoT is beneficial for several reasons, including the following:
- We need a mechanism to communicate with IoT devices because they are always connected, even in the presence of firewalls, network address translation (NAT), and other roadblocks.
- We need a scalable design because there are now billions of these devices and the number is increasing fast. Also, as these devices interact around the clock, we want an available (HA) strategy that supports deployment across data centres to provide disaster recovery (DR).
- We need to offer automated and managed upgrades as well as the ability to remotely track these devices. They may not have UIs and are intended for "everyday" use.
- IoT devices are often used for the collection and analysis of personal data. IoT devices must have a model for managing identification and access control for the data they publish and consume.
What Makes Up The IoT Architecture?
The key components of IoT Architecture are discussed below. You may also join an IoT Training Institute to learn them.
1. Applications and Analytics Component
The data gathered by IoT is processed and displayed in this piece. It has analytics tools, machine learning and AI features, and visualisation capabilities. Technology options for this component include standard analytics and visualisation tools. For instance R, IBM SPSS, and SAS, as well as specialised IoT tools and dashboards from cloud service providers. It includes companies like Amazon, Google, Microsoft, Oracle, and IBM, and vendors of application suites like SAP, Salesforce, and others.
2. Security And Management Component
IoT security entails protecting the system's physical components using embedded security providers. It can be both conventional security providers with IoT functionality and IoT-specific providers. The following are some examples: Armis, Auth0, Cisco, Digicert, Forescout, Ordr, Palo Alto, Rapid7, SimpliSafe, and SonicWall.
3. Integration Component
This part makes sure that the infrastructure, security, and tools all work together with the company's current ERP. They must follow other management systems in an efficient manner. The above software and cloud players are among the providers, along with a variety of middleware and open source technologies. They include Oracle Fusion Middleware, LinkSmart, Apache Kafka, and DynThings Open Source IoT Platform.
4. Infrastructure Component
This comprises real things like smart sensors, which gather data, and actuators, which regulate the environment. It refers to the network, which is not commonly a wireless network. For instannce Wi-Fi, Bluetooth, 4G, or 5G, on which the sensors or actuators are situated.
Architectures for the Internet of Things (IoT)
Examples of IoT architecture can be used to explain how these technologies operate in various situations:
1) Internet of Things (IoT) Design for the Aviation Industry
A busy airport may have hundreds of moving vehicles, both aeroplanes and ground vehicles, at any given time. These movements need to be made across several square miles of terrain inclement weather and limited visibility. In such a situation, IoT solutions assist airports in strengthening safety, enhancing efficiency, and reducing interruptions.
2. Architecture for the Internet of Things (IoT) in Manufacturing
A simple yet brilliant IoT solution was used by Stanley Black & Decker, a manufacturer of power tools, in the early 2010s. This system made considerable use of the IoT edge layer. A real-time location system (RTLS) tracker made by AeroScout Industrial connects with the factory's existing Cisco wireless routers. It helped Stanley Black & Decker identify the locations of issues on its factory floor. It works by attaching RFID tags to the goods moving through its manufacturing facility.
3. Microsoft Azure – Internet of Things (IoT) Architecture
Microsoft's managed Azure IoT platform consists of cloud services that connect, track, and manage billions of IoT devices. Particularly, Azure IoT provides for bi-directional connection between devices and apps. Also, it supports popular communication protocols like HTTP, MQTT, and AMQP. Operating systems like Windows 11 IoT Enterprise are intended for use with IoT devices. Microsoft's Windows for IoT gives the IoT more strength, security, and manageability. As a result, Microsoft offers a complete solution to manage all IoT system architecture layers, from devices to applications.
Conclusion
The IoT architecture may differ from solution to solution in reality. These four fundamental building pieces are present, but not always. Also, a solution must be functional, scalable, and resistant to malfunctioning while handling massive amounts of data. Businesses that have implemented IoT solutions are now surpassing their clients. They can now get more value from the data and provide them accordingly. It is crucial to avoid becoming perplexed by the IoT's technical terms. We must keep an eye on the countless opportunities and developments that could lead to total automation. If you are interested to learn about IoT, check out the Internet of Things course from The IoT Academy!
