Open experiment platform for engineering teaching of Internet of Things

Abstract

The invention discloses an internet of things engineering teaching open experiment platform, which comprises a main control module, and the main control module is the core of the whole experiment platform, is responsible for coordinating and managing communication and data exchange among all modules, and is also responsible for communicating with external equipment to realize data uploading and downloading; the sensor module is an important component of an Internet of Things sensing layer and is used for acquiring real-time data of various environmental parameters, and the sensor module is connected with the main control module through a standardized interface to realize data transmission and sharing; the RFID module is connected with the main control module through a standardized interface; the beneficial effects of the invention are that the platform is easy to expand and upgrade due to the modular design, can closely follow the development pace of the Internet of Things technology, and meets the constantly changing teaching requirements; the online management function and multi-mode remote control promote real-time interaction between teachers and students, and the participation degree and interestingness of experiment teaching are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of Internet of Things teaching, and in particular relates to an open experimental platform for Internet of Things engineering teaching. Background Art

[0002] As the main body of IoT talent training, colleges and universities need to actively promote the construction and development of IoT and related majors, take the initiative to explore the training model, curriculum setting and practical teaching system of IoT talents, innovate training methods and ideas, strengthen industry-university-research cooperation training, and continuously improve the innovation and entrepreneurship ability and hands-on practical ability of IoT professionals, so as to provide qualified and excellent IoT talents for the vigorous development of the IoT industry; engineering teaching, as an important part of university teaching, is a key link in cultivating IoT innovative research and engineering and technical talents. Among them, building IoT engineering teaching oriented towards IoT project development and practice, concentrating on the advantageous equipment and technologies of IoT-related majors and highly integrating them, connecting the IoT perception layer, network layer and application layer, and making comprehensive design projects to cultivate compound IoT innovative practical technical talents has gradually become a common practice of many universities.

[0003] The Internet of Things engineering teaching open experiment platform with publication number CN103165005A discloses the first, second and third modules which are connected to each other for communication. The first module includes an embedded wireless gateway and a WIFI module, a ZigBee coordinator, a 3G module and an image sensor which are respectively connected to the platform for communication. The second module includes a microcontroller A and a temperature and humidity sensor, a temperature sensor, a vibration sensor, an infrared sensor, a photosensitive module, a stepping motor, a universal editing interface A and a ZigBee module A which are respectively connected to the platform for communication. The third module includes a microcontroller B and a universal programming interface B, a ZigBee module B, a FRID module, a 12864 liquid crystal display and a matrix keyboard which are respectively connected to the platform for communication. Although the basic framework of the Internet of Things teaching experiment is provided to a certain extent, with the rapid development of the Internet of Things technology and the continuous changes in industrial needs, the platform has limitations in terms of module flexibility, teaching interactivity, and experimental diversity. Summary of the invention

[0004] The purpose of the present invention is to provide an open experimental platform for Internet of Things engineering teaching, to achieve comprehensive coverage and in-depth application of Internet of Things technology, to improve teachers' teaching flexibility, effectiveness and autonomy, and to promote students' learning efficiency and interest.

[0005] To achieve the above purpose, the present invention provides the following technical solutions: an open experimental platform for Internet of Things engineering teaching, comprising

[0006] The main control module is the core of the entire experimental platform, responsible for coordinating and managing the communication and data exchange between various modules, and is also responsible for communicating with external devices to upload and download data;

[0007] The sensor module is an important component of the IoT perception layer and is used to collect real-time data of various environmental parameters. The sensor module is connected to the main control module through a standardized interface to achieve data transmission and sharing;

[0008] RFID module, which is connected to the main control module through a standardized interface to achieve real-time transmission and processing of data;

[0009] A programming teaching module, which provides students with an environment and resources for learning IoT programming, and helps them master the basic skills and application methods of IoT programming;

[0010] The experimental teaching module is an important part of the Internet of Things teaching experiment platform, integrating various experimental projects and teaching resources; students can use this module to conduct experimental learning of Internet of Things technology, provide experimental report generation, experimental result analysis, and help students consolidate the knowledge they have learned and improve their practical ability.

[0011] As a preferred technical solution of the present invention, the environmental parameters include temperature and humidity, vibration, infrared, and light.

[0012] As a preferred technical solution of the present invention, it also includes an online management unit, which includes

[0013] Device management module: allows teachers or administrators to register new devices in the cloud management platform and configure their basic parameters; displays the online status, working mode, and fault information of each device in real time; supports remote power on and off of devices and parameter adjustment operations;

[0014] Data monitoring and analysis module: automatically collects experimental data from sensors and RFID modules, and displays them in real time on the cloud platform; provides data visualization tools and data analysis algorithms to help teachers and students analyze experimental data and discover patterns; uses cloud storage technology to ensure the security and long-term accessibility of experimental data;

[0015] Event warning module: Set thresholds to automatically trigger warnings when experimental data or equipment status exceeds the normal range; send messages via email, SMS or platform to notify relevant personnel to handle abnormal situations.

[0016] As a preferred technical solution of the present invention, it also includes a dynamic networking and topology monitoring unit, which includes

[0017] Dynamic networking module: dynamically adjusts the network topology according to the specific needs of teaching experiments; supports automated deployment of network configuration to reduce manual intervention;

[0018] Topology monitoring module: displays the current network topology in real time on the cloud platform; combines network status data to quickly locate network fault points and provide repair suggestions; integrates GPS or Beidou positioning systems for experiments that require geographic location information; and uses indoor positioning technology to improve the positioning accuracy of experimental equipment in indoor environments.

[0019] As a preferred technical solution of the present invention, it also includes a multi-mode remote control unit, which includes

[0020] Web browser control module: Through a web browser, teachers and students can access the cloud management platform on any web-enabled device for remote control; a user-friendly interface is designed to simplify the operation process;

[0021] Mobile APP control module: Develop a mobile APP so that teachers and students can remotely monitor and operate experimental equipment anytime and anywhere.

[0022] As a preferred technical solution of the present invention, a mobile phone APP is combined with a mobile phone push notification function to instantly receive experimental status updates and warning information.

[0023] As a preferred technical solution of the present invention, it also includes a user feedback and evaluation mechanism unit, which includes

[0024] Feedback collection module: Design structured interview questionnaires for different user groups to collect feedback on platform functions, usability, and teaching effectiveness; in addition to online questionnaires, feedback can also be collected through face-to-face interviews and telephone interviews;

[0025] In-depth analysis and evaluation module: conduct in-depth analysis of the collected feedback data to identify problems and improvement points; build user portraits to understand the needs and preferences of different user groups and provide a basis for platform optimization;

[0026] Continuous optimization module: Based on the analysis results, an optimization plan is formulated to implement improvements and upgrades to platform functions in stages; a user feedback loop mechanism is established to ensure that platform functions are always consistent with user needs.

[0027] As a preferred technical solution of the present invention, statistical analysis and text mining technology are used to conduct in-depth analysis on the collected feedback data.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The modular design makes the platform easy to expand and upgrade, keeping up with the development of IoT technology and meeting the ever-changing teaching needs;

[0030] Online management functions and multi-mode remote control promote real-time interaction between teachers and students, and increase the participation and interest of experimental teaching;

[0031] Organically combine theoretical knowledge with practical experience, so that students can deepen their understanding and application of IoT technology in practice and improve their learning efficiency and interest;

[0032] The platform design fully considers the future development trend of the Internet of Things industry and helps to cultivate high-quality Internet of Things professionals that meet market demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a diagram of the experimental platform structure of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example 1

[0036] See also Figure 1 , which is the first embodiment of the present invention, and provides an open experimental platform for Internet of Things engineering teaching, including

[0037] The main control module is the core of the entire experimental platform. It is responsible for coordinating and managing the communication and data exchange between various modules. It has powerful processing capabilities and can process data from various sensor modules, RFID modules, etc., and execute corresponding control instructions. It is also responsible for communicating with external devices (such as computers, cloud platforms, etc.) to upload and download data.

[0038] Sensor module (including temperature and humidity sensor, vibration sensor, infrared sensor, photosensitive module, etc.). The sensor module is an important part of the perception layer of the Internet of Things. It is used to collect real-time data of various environmental parameters (such as temperature and humidity, vibration, infrared, light, etc.). These data are the basis for analysis, decision-making and control of the Internet of Things system. They are connected to the main control module through a standardized interface to realize data transmission and sharing;

[0039] RFID module: The RFID module uses radio frequency identification technology to realize automatic identification and data reading of target objects. In the Internet of Things teaching experiment, it can help students understand the basic principles and application scenarios of RFID technology. The RFID module is connected to the main control module through a standardized interface to realize real-time transmission and processing of data.

[0040] Programming teaching module (supports multiple programming languages ​​and interfaces). The programming teaching module provides students with an environment and resources for learning IoT programming. It supports multiple programming languages ​​(such as C / C++, Python, Java, etc.) and interfaces (such as GPIO, UART, I2C, SPI, etc.), allowing students to choose appropriate programming languages ​​and interfaces for development according to experimental requirements. It also contains a wealth of tutorials, cases, and experimental projects to help students master the basic skills and application methods of IoT programming.

[0041] Experimental teaching module, the experimental teaching module is an important part of the Internet of Things teaching experiment platform. It integrates various experimental projects and teaching resources. Students can use this module to conduct experimental learning of Internet of Things technology, including sensor data acquisition, RFID technology application, and wireless communication technology (such as WiFi, ZigBee, etc.); it also provides functions such as experimental report generation and experimental result analysis to help students consolidate their knowledge and improve their practical ability.

[0042] Example 2

[0043] See also Figure 1 , which is the second embodiment of the present invention, is based on the previous embodiment, except that:

[0044] Also included is an online management unit which includes

[0045] Device management module:

[0046] Device registration and configuration: allows teachers or administrators to register new devices in the cloud management platform and configure their basic parameters, such as IP address, port number, device type, etc.

[0047] Status monitoring: Real-time display of the online status, working mode, fault information, etc. of each device to ensure the normal operation of the equipment;

[0048] Remote control: supports remote power on / off of equipment, parameter adjustment and other operations to improve management efficiency;

[0049] Data monitoring and analysis module:

[0050] Real-time data collection: Automatically collect experimental data from sensors, RFID and other modules, and display them on the cloud platform in real time;

[0051] Data analysis tools: provide data visualization tools (such as charts and graphs) and data analysis algorithms to help teachers and students analyze experimental data and discover patterns;

[0052] Data storage: Cloud storage technology is used to ensure the security and long-term accessibility of experimental data;

[0053] Event Alert Module:

[0054] Anomaly detection: Set thresholds to automatically trigger warnings when experimental data or equipment status exceeds the normal range;

[0055] Notification mechanism: timely notify relevant personnel to handle abnormal situations by sending messages via email, SMS or platform;

[0056] It also includes a dynamic networking and topology monitoring unit, which includes

[0057] Dynamic networking module:

[0058] Flexible configuration: Dynamically adjust the network topology according to the specific needs of the teaching experiment, such as adding and deleting nodes and changing the connection relationship;

[0059] Automated deployment: supports automated deployment of network configuration, reduces manual intervention, and improves networking efficiency;

[0060] Topology monitoring module:

[0061] Real-time display: The current network topology is displayed in real time on the cloud platform, including node location, connection status, etc.

[0062] Fault location: Combined with network status data, quickly locate network fault points and provide repair suggestions;

[0063] Precise positioning function:

[0064] GPS / Beidou integration: For experiments that require geographic location information, integrate GPS or Beidou positioning systems to ensure the spatial accuracy of experimental data;

[0065] Indoor positioning technology (such as Bluetooth beacons, Wi-Fi positioning): In indoor environments, indoor positioning technology is used to improve the positioning accuracy of experimental equipment;

[0066] Also included is a multi-mode remote control unit that includes

[0067] Web browser control module:

[0068] Cross-platform support: Through a web browser, teachers and students can access the cloud management platform on any web-enabled device for remote control;

[0069] Intuitive interface: Design a user-friendly interface to simplify the operation process and improve control efficiency;

[0070] Mobile APP control module:

[0071] Mobility: Develop a mobile phone APP so that teachers and students can remotely monitor and operate experimental equipment anytime and anywhere;

[0072] Real-time notification: Combined with the mobile phone push notification function, you can instantly receive experimental status updates and warning information; it also includes a user feedback and evaluation mechanism unit, which includes

[0073] Feedback collection module:

[0074] Structured interview questionnaire: Design structured interview questionnaires for different user groups to collect feedback on platform functions, usability, teaching effectiveness, etc.;

[0075] Multi-channel collection: In addition to online questionnaires, feedback can also be collected through face-to-face interviews, telephone interviews, etc.

[0076] In-depth analysis and evaluation module:

[0077] Data analysis: Use statistical analysis and text mining techniques to conduct in-depth analysis of the collected feedback data to identify problems and improvement points;

[0078] User portrait: Build user portraits to understand the needs and preferences of different user groups and provide a basis for platform optimization;

[0079] Continuous optimization module:

[0080] Iterative optimization: Based on the analysis results, an optimization plan is formulated to implement improvements and upgrades to platform functions in stages;

[0081] User feedback loop: Establish a user feedback loop mechanism to ensure that platform functions are always consistent with user needs.

[0082] Although the embodiments of the present invention have been shown and described, as detailed above, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An open experimental platform for Internet of Things engineering teaching, characterized by: include The main control module is the core of the entire experimental platform, responsible for coordinating and managing the communication and data exchange between various modules, and is also responsible for communicating with external devices to upload and download data; The sensor module is an important component of the IoT perception layer and is used to collect real-time data of various environmental parameters. The sensor module is connected to the main control module through a standardized interface to achieve data transmission and sharing; RFID module, which is connected to the main control module through a standardized interface to achieve real-time transmission and processing of data; A programming teaching module, which provides students with an environment and resources for learning IoT programming, and helps them master the basic skills and application methods of IoT programming; The experimental teaching module is an important part of the Internet of Things teaching experiment platform, integrating various experimental projects and teaching resources; students can use this module to conduct experimental learning of Internet of Things technology, provide experimental report generation, experimental result analysis, and help students consolidate the knowledge they have learned and improve their practical ability.

2. The Internet of Things engineering teaching open experiment platform according to claim 1 is characterized by: The environmental parameters include temperature and humidity, vibration, infrared, and light.

3. The open experimental platform for Internet of Things engineering teaching according to claim 1 is characterized by: Also included is an online management unit which includes Device management module: allows teachers or administrators to register new devices in the cloud management platform and configure their basic parameters; Real-time display of the online status, working mode, and fault information of each device; support remote power on / off and parameter adjustment of the device; Data monitoring and analysis module: automatically collects experimental data from sensors and RFID modules, and displays them in real time on the cloud platform; provides data visualization tools and data analysis algorithms to help teachers and students analyze experimental data and discover patterns; uses cloud storage technology to ensure the security and long-term accessibility of experimental data; Event warning module: set thresholds to automatically trigger warnings when experimental data or equipment status exceeds the normal range; Send messages via email, SMS or platform to notify relevant personnel to handle abnormal situations.

4. The Internet of Things engineering teaching open experiment platform according to claim 1 is characterized by: It also includes a dynamic networking and topology monitoring unit, which includes Dynamic networking module: dynamically adjusts the network topology according to the specific needs of teaching experiments; supports automated deployment of network configuration to reduce manual intervention; Topology monitoring module: displays the current network topology in real time on the cloud platform; combines network status data to quickly locate network fault points and provide repair suggestions; integrates GPS or Beidou positioning systems for experiments that require geographic location information; and uses indoor positioning technology to improve the positioning accuracy of experimental equipment in indoor environments.

5. The Internet of Things engineering teaching open experiment platform according to claim 1 is characterized by: Also included is a multi-mode remote control unit that includes Web browser control module: Through a web browser, teachers and students can access the cloud management platform on any web-enabled device for remote control; a user-friendly interface is designed to simplify the operation process; Mobile APP control module: Develop a mobile APP so that teachers and students can remotely monitor and operate experimental equipment anytime and anywhere.

6. The Internet of Things engineering teaching open experiment platform according to claim 5 is characterized by: The mobile app combines the mobile phone push notification function to instantly receive experimental status updates and warning information.

7. The Internet of Things engineering teaching open experiment platform according to claim 1 is characterized by: It also includes a user feedback and evaluation mechanism unit, which includes Feedback collection module: Design structured interview questionnaires for different user groups to collect feedback on platform functions, usability, and teaching effectiveness; In addition to the online questionnaire, feedback can also be collected through face-to-face interviews and telephone interviews; In-depth analysis and evaluation module: conduct in-depth analysis of the collected feedback data to identify problems and improvement points; build user portraits to understand the needs and preferences of different user groups and provide a basis for platform optimization; Continuous optimization module: Based on the analysis results, an optimization plan is formulated to implement improvements and upgrades to platform functions in stages; Establish a user feedback loop mechanism to ensure that platform functions are always consistent with user needs.

8. The Internet of Things engineering teaching open experiment platform according to claim 7 is characterized by: Use statistical analysis and text mining techniques to conduct in-depth analysis of the collected feedback data.

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