I. The Concept of the Internet of Things
The Internet of Things (IoT) utilizes technologies such as RFID, infrared sensors, GPS, and laser scanning to collect real-time data on objects requiring monitoring, connection, and interaction. This data includes various necessary information such as sound, temperature, light intensity, and heat. Through various network access methods, it achieves ubiquitous connectivity between things and between things and people, enabling intelligent sensing, identification, and management of objects and processes. The IoT is an extension of the internet's applications and represents a new wave of development in the global information industry following computers and the internet. Application innovation is the core of IoT development, while user experience is its soul.
II. Applications of the Internet of Things
The Internet of Things (IoT) is a core driver of Industry 4.0. Industry 4.0 is based on interconnected networks and physical systems, supporting the use of technologies such as artificial intelligence, machine learning, robotics, and big data.
In terms of application areas, the Internet of Things (IoT) can be divided into two categories: consumer IoT and industrial IoT. Consumer IoT is closer to daily life, such as smart homes, shared bicycles, and smart wearables, while industrial IoT is mainly used in industries with mature business models, such as manufacturing, transportation, and construction. With the rapid development of information technology, IoT will also face new challenges and improvements.
III. Applications of the Internet of Things in Manufacturing
1. Intelligent design and production
On the one hand, the integration of the Internet of Things (IoT) with manufacturing enables intelligent product design, manifested in digital design, virtual space design, multimedia design, and remote design. On the other hand, this integration also enables the intelligentization of the products themselves, by incorporating modern information technology to achieve more intelligent functions and meet diverse consumer needs. For example, digital twin technology uses real-time data to build intelligent model structures—twins—which can then detect potential inefficiencies in products, helping companies upgrade their manufacturing processes.
2. Visual monitoring of the production process
The Internet of Things (IoT) can track smart meters for water, electricity, and other fuels, and has therefore been introduced into manufacturing, energy, and other industries. Utilizing IoT technology allows for the visual monitoring and management of manufactured products and equipment, collecting information related to products and equipment in real time, such as production output and anomaly reports. This enables equipment to self-reinforce and self-diagnose, facilitating quality management and troubleshooting for businesses.
3. Automated warehousing and transportation
On the one hand, the integration of the Internet of Things (IoT) with manufacturing enables intelligent product design, manifested in digital design, virtual space design, multimedia design, and remote design. On the other hand, this integration also enables the intelligentization of the products themselves, by incorporating modern information technology to achieve more intelligent functions and meet diverse consumer needs. For example, digital twin technology uses real-time data to build intelligent model structures—twins—which can then detect potential inefficiencies in products, helping companies upgrade their manufacturing processes.
4. Upgraded after-sales service
Manufacturing companies can embed sensing components into their products during production. These intelligent components, transmitted via information networks, allow the company's data center to receive real-time information about the product's operational status. For example, manufacturers can gain insights into different consumer habits and how products are handled, as well as the impact of weather, routes, and other environmental variables on the product. This enables remote upgrades, which involve obtaining product circulation information via wireless networks and improving after-sales management through online sales services.
IV. IOTOS Internet of Things Platform
OTOS IoT Middleware Platform (also known as "IoT Middleware") is an IoT platform for system integration. It adopts AIoT multi-system data fusion technology, providing a data foundation and application foundation. It is used in IoT multi-system data fusion and integration scenarios such as building, environmental protection, and industry. Its main features are "one-click adaptation of device subsystems and ready-to-use IoT applications", which solves the problem of complicated device subsystem access and business application development and customization in a high-efficiency, low-cost and low-threshold way.
The platform has the following six innovative aspects, from data access to application:
1. Unified hardware and software model
In addition to supporting conventional IoT platforms to access incremental smart hardware devices via triplet and certificate authentication methods, the platform provides unified abstraction and encapsulation of existing access objects related to smart buildings (such as sensors, devices, services, platforms, databases, algorithms, etc.), offering three layers: gateway, device/system, and data point. It also enables communication between devices and the cloud, and between devices.
2. Visualization of nested components
All component properties can be bound to exposed variables, and when dragged and dropped onto a new component, the bound and retained variables can be re-entered into variable binding, as well as new property exposure variables can be bound. In this way, through multi-level nesting and multi-level exposure, it is possible to encapsulate any graphical component and expose configuration properties, and finally perform actual configuration through the outermost application.
3. Distributed routing bus
The RPC soft bus approach allows any driver engine to connect to any end node within the routing system branch. Addressing between driver engines is achieved by automatically selecting the data transmission channel through a load-balanced link, using an RPC interface for connection, and maintaining data context.
4. Data permissions are tradable.
By abstracting devices into data points, these data points can be published and offered to other users for paid or free subscriptions. Subscribed users can perform various operations on these data points as if they were their own. In particular, they can perform unified algorithmic and business analysis on data points subscribed to by multiple parties, enabling new services to be hosted on the platform. This allows for the abstraction of more advanced data points, which can then be published again, thereby facilitating data transactions.
5. Driver-driven acquisition engine
Drivers, as support for protocol conversion and device model abstraction, can be modularized and pluggable, supporting hot-swapping and plug-and-play functionality. For example, for standard protocols such as Modbus, OPC, and BACNET, as well as non-standard protocols such as SDKs, corresponding drivers supported by the platform can be provided, allowing devices to be dynamically loaded upon association. With the necessary communication and protocol parameter configurations, rapid integration and access of device systems can be achieved.
6. Intelligent human-like interaction
It supports AI chat assistants for mobile devices, empowered by an intelligent brain, enabling unified operation and management of devices through instant chat. No customized interface is required, and it can achieve unified operation and management of any type and any data device, realizing universal interaction of mobile devices.
