Internet of Things Architecture Model

Overview

The Internet of Things (IoT) has evolved from obscurity to widespread recognition, and our daily lives are now inseparable from it. Over a decade ago, during an internal company exchange, a PhD from our company first mentioned the term M2M to me. I was immediately impressed and convinced by the potential of this industry. Consequently, we established an IoT division to begin tracking and learning about this field.

In 1999, Kevin Ashton, co-founder of the Auto-ID Center at MIT, first mentioned the Internet of Things in a presentation to Procter & Gamble. IoT evolved from M2M communication, where machines connect to each other over a network without human interaction. M2M refers to connecting devices to the cloud, managing them, and collecting data. Taking M2M a step further, the IoT is a sensor network of billions of smart devices that connect people, systems, and other applications to collect and share data. As its foundation, M2M provides the connectivity that enables the IoT.

In short, the Internet of Things is the concept of connecting any device (as long as it has an on/off switch) to the Internet and other connected devices. IoT is a vast network of interconnected things and people, all collecting and sharing data about how they are used and their surrounding environment. As IoT technology becomes more prevalent and develops, people are increasingly benefiting from it. Businesses are rethinking their logic and methods for handling tasks, embarking on a path of digital transformation. Consumers' habits of using IoT are gradually forming, with growing reliance on it in work, life, learning, and other scenarios, thereby reducing resource waste, saving time, and gradually improving quality of life.

The Significance of Architectural Models

However, the fields and scope involved in IoT are too broad. As there is no internationally compatible standard for IoT, and due to the rich variety of IoT scenarios, no single technology or standard can cover all scenarios. Each standard has its specific scenarios and application ranges. For example, 6LoWPAN (IPv6 over Low-Power Wireless Personal Area Networks) is used for home automation, LoRaWAN for smart cities, the ZigBee (IEEE) 802.15.4 standard for industrial environments, and LiteOS is a Unix-like operating system for wireless sensor networks.

Because the IoT is composed of many different functions, a sustainable IoT ecosystem is necessary for the entire system to function fully and effectively. This system needs to include four building blocks: functionality, scalability, availability, and maintainability, with scalability being particularly critical as the system needs to grow alongside the needs of the organization or project. Although there is no unified standard, for the IoT to develop effectively and sustainably, a shared overall framework is needed, allowing developers to follow the same model when designing products. This is similar to the OSI reference model by the International Organization for Standardization (ISO), enabling everyone to develop their products with a common vision.

There are discussions of three-layer and four-layer IoT architectures. The complexity and number of architectural layers vary depending on the specific business task at hand. The four-layer architecture is the standard and most widely accepted format. The three-layer architecture refers to: Application Layer, Transport Layer, and Perception Layer. The four-layer architecture splits the Application Layer from the three-layer model into: Application Layer (various scenario-specific application software), Processing Layer (edge computing, machine learning, and algorithms), Transport Layer (Internet gateway), and Perception Layer (various sensors and terminal products).

The Four-Layer IoT Model

Perception Layer

The foundation of any IoT system consists of various sensors and actuators used to perceive information from the physical world. Without these fundamental devices, the implementation of IoT would be meaningless. These can be wireless sensors that react to the environment and make collected data available for analysis, or actuators, relays, and switches, as they can interact with the environment in significant ways. For example, they can be used to close a valve when water reaches a certain level or simply turn off lights when the sun rises.

Transport Layer (Network Layer)

The Transport Layer provides the interface and communication methods for data throughout the application. This layer contains Data Acquisition Systems and gateways. Data acquisition performs data aggregation and conversion functions (collecting and aggregating data from sensors, converting analog data to digital data, etc.). IoT gateways connect smart devices and network devices for data transmission.

Processing Layer

This layer handles preprocessing and enhanced data analytics. Given the vast amount of data collected by IoT systems and the consequent bandwidth demands, edge IT systems play a crucial role in alleviating pressure on the core IT infrastructure. Edge IT systems employ machine learning and visualization techniques to generate key metrics from the collected data. Machine learning algorithms provide analysis and execution logic based on the data, while visualization techniques present the data in an easily understandable manner.

Application Layer

The Application Layer is where users interact with IoT devices. It is responsible for providing application-specific services to users. This could be the operation of a smart home, where a user clicks a button or speaks to open or close curtains; it could be lowering a parking barrier in a smart parking system; or performing inventory tasks via a button in the Cloud Position Warehouse.

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