Physics Network Virtual Simulation Training System
Product Description
(1) Product Overview
The IoT Virtual Simulation Training System is a simulation platform designed for teaching and practical applications in sensor networks, as well as for IoT and AIoT use cases. This system supports a wide range of instructional courses, including sensor theory, hardware interfacing, perception-layer programming, simulated deployment of case‑study projects, application development, and innovative experiments, covering topics such as sensor networks and intelligent control.
(II) Product Features
1. Integrated Laboratory Management System
On the teacher side, users can centrally create and manage student accounts, assign tasks, and perform other administrative functions. The system records and stores students’ experimental procedures, outcomes, and durations, generates experimental reports, and conducts performance evaluations.
2. Implement cloud-based teaching
This system supports cloud-based instruction, enabling hands-on training without time or location constraints, even as the pandemic remains far from fully under control.
3. Perfect integration of virtual and real devices
The system adopts a client/server architecture, with all instructional content rendered in full 3D simulation and seamlessly integrated with a comprehensive hands-on training platform for sensor network system design and application development. The virtual simulations and physical equipment can independently complete their respective training tasks while cross‑validating one another, and they can also operate in tandem—enabling users to retrieve real‑world device data via the simulation software or to perform operations on actual hardware. In this way, the gap between simulation and reality is eliminated, achieving a perfect fusion of virtual and physical elements and delivering truly immersive learning.
4. Enriching the teaching content of application-layer development
Through this virtual simulation system, students can not only learn Android and C# development—from setting up the development environment to integrating sensor data—but also undertake courses on reverse control of sensor networks. Combined with the integrated experimental kit for sensing and intelligent control, the comprehensive training platform for the design and application development of sensing and intelligent control systems, and the integrated application system for smart cities and agricultural meteorology, secondary development can be carried out, thereby achieving the goal of cultivating high‑quality, skill‑oriented professionals at multiple levels.
(3) Teaching and Experimental Resources
1. Engineering Hardware Wiring Experiments in Sensing and Intelligent Control (39 experiments)
2. STM32 Basic Development Experiments in Sensing and Intelligent Control (8 experiments)
3. STM32 Sensor Development Experiments in Sensing and Intelligent Control (38 experiments)
4. Wireless Node, Module Firmware Flashing, and Networking Experiments in Sensing and Intelligent Control (7 experiments)
5. Application Development Experiments in Android Sensor and Intelligent Control (46 experiments)
6. Application Development Experiments in C# Sensor and Intelligent Control (46 experiments)
7. Python-Based Development Experiments in Sensing and Intelligent Control (26 items)
8. PyQt5 Development Experiments in Sensing and Intelligent Control (39 items)
9. PyQt5-Based Sensing and Intelligent Control AIoT Development Experiments (4 items)
Tag list： Physics Network Virtual Simulation Training System
The IoT Virtual Simulation Training System is a simulation platform designed for teaching and practical applications in sensor networks, as well as for IoT and AIoT use cases. This system supports a wide range of instructional courses, including sensor theory, hardware interfacing, perception-layer programming, simulated deployment of case‑study projects, application development, and innovative experiments, covering topics such as sensor networks and intelligent control.
Industrial Digital Intelligence Business Unit (Teacher Guo)：18666013984
Industry–Education Integration (Teacher Zeng)：18588894612
AIoT Business Unit (Teacher Liu)：13660039204
Low-Altitude Economy Division (Teacher Yang)：18620640166
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