The Internet of Things Comprehensive Training Platform (FS_SXTC) is a platform that integrates multiple projects such as smart home, smart agriculture, smart warehousing, smart transportation, and smart security. The IoT comprehensive training platform is not only suitable for learning IoT theoretical knowledge and related courses such as IoT system design, installation, wiring, debugging, and system maintenance, but also provides a powerful teaching and research platform for IoT innovation and development.

It consists of 6 detachable panels and 24 magnetic suction plates. The 6 detachable panels include 1 basic and gateway training panel, 1 intelligent storage panel, and 4 project training application panels. The Basic and Gateway Training Panel is suitable for learning the basic theory of the Internet of Things and includes 6 basic learning units. The basic learning unit and panel use magnetic attraction for easy disassembly. The unit includes Cortex-M0 chip basic peripheral driver development, multiple sensor driver development, and 6 wireless network development. The gateway area is suitable for platform level development and learning needs, including Linux system development and FreeRTOS system development. The application area is suitable for practical training courses, course design, and graduation projects. The training application area of the 4 projects adopts modular design, with the control board (MCU) and sensor hardware separated. The control board and sensors are fixed in the application area of the training platform using magnetic attraction and hooks. The control board can connect any sensor. Its flexibility and compatibility can meet the design needs of students in different scenarios and projects.

1. Adopting magnetic attraction and design, users can freely disassemble, eliminating complex wiring troubles;

2. It includes basic learning units that cover 6 types of wireless sensor networks (ZigBee, BLE, WiFi, LoRa, IPv6, NB-IOT) and 12 types of sensing and execution components. It can help customers quickly get started and master the core knowledge of wireless sensor networks and the Internet of Things;

3. Adopting a Cortex-A53/Cortex-M4 dual gateway design, the Cortex-A53 gateway is designed for the embedded field and is used to cultivate embedded talents such as computer and software design;

4. It includes over 20 common sensors and actuators, 6 wireless communication networks (ZigBee, BLE, WiFi, LoRa, IPv6, NB-IOT), and 485 bus communication technologies, which can meet the design requirements of different projects;

5. Single wireless network networking (ZigBee, BLE, WiFi, LoRa, IPv6) or hybrid network networking can be selected to meet project applications under different conditions;

6. FS_SXTC is an end-to-end (user, cloud, sensor, actuator) project application system, consisting of a perception layer (sensor/chip), a network layer (chip/communication module), a platform layer (operating system), and an application layer (intelligent terminal). It meets the current technological application scenarios and facilitates users' understanding of IoT system design and architecture. Users can conduct research and teaching specifically for a certain layer.

7. Provide IoT cloud services.

Integrated Training Platform System Architecture Diagram

1、 Smart Home

The smart home system is a unified and complex whole that requires many types of perception sensors to detect the indoor environment. At the same time, it is necessary to control related household appliances based on this information.

Structure diagram of smart home system

2、 Intelligent Agriculture

In the intelligent agricultural control system, IoT devices such as temperature sensors, humidity sensors, pH sensors, illuminance sensors, CO2 sensors, etc. are used to detect physical parameters such as temperature, relative humidity, pH value, light intensity, soil nutrients, CO2 concentration, etc. in the environment, ensuring that crops have a good and suitable growth environment. The implementation of remote control enables technicians to monitor and control the environment of multiple greenhouses in the office. Using wireless networks to measure and obtain the optimal conditions for crop growth.

Structure diagram of intelligent agriculture system

3、 Intelligent transportation application scenarios

This system is based on urban road traffic and residential communities, and relies on sensors and control, wireless networks, intelligent training vehicles, video surveillance, intelligent gateways, and other devices deployed in real-world sand tables to achieve intelligent control and management of simulated cities.

Structure diagram of intelligent transportation training system

4、 Intelligent warehousing

The intelligent warehousing training system is based on Internet of Things technology. Relying on wireless networking technology within the training room, a stable and reliable ZigBee coverage environment is formed; Various access devices (sensors, control devices) can wirelessly connect to the IoT information platform, becoming part of the IoT experimental equipment and building the perception layer of the IoT. The system stores, analyzes, and applies data through a unified warehouse management center.

Structure diagram of intelligent warehousing system

Project 1:

Through mobile phones PC、 An app in devices such as tablets that controls indoor equipment. At the same time, indoor sensing devices will adjust the lighting and temperature according to changes in the surrounding environment, and monitor the indoor environment in real time, playing a timely warning role.

Application technologies: comprehensive cabling technology, network communication technology, security prevention technology, automatic control technology, audio and video technology, etc.

Equipment highlight: The smart home system is a unified and complex whole. Many types of perception sensors are needed to detect the indoor environment. At the same time, it is necessary to control related household appliances based on this information. To achieve a living environment that is safe, convenient, comfortable, artistic, and environmentally friendly and energy-efficient.

Framework diagram of lighting system based on training platform

Project 2:

The system simulates a real ETC scenario and intelligently charges passing vehicles. The ETC system automatically lifts the barrier barrier when a vehicle passes, simulating automatic toll collection. After the vehicle passes, the barrier automatically drops, achieving non-stop toll collection.

Application technologies: wireless network, AI artificial intelligence, RFID identification, sensors and controllers, AGV magnetic navigation, embedded systems, mobile Internet, cloud computing, etc.

Equipment highlights: The system takes urban road traffic and residential communities as the prototype, comprehensively uses wireless network, AI artificial intelligence, RFID identification, sensors and controllers, AGV magnetic navigation, embedded systems, mobile Internet, cloud computing and other technologies, and relies on sensors and control, wireless network, intelligent training vehicles, video surveillance, intelligent gateways and other equipment deployed in the live sand table to achieve intelligent control and management of analog cities, help students become familiar with the development of smart city system related projects, and complete the improvement from specific basic knowledge points to comprehensive applications.

Parking Lot System Structure Diagram