Abstract

With continuous innovation of technology and rapid development and wide application of new technologies, such as Internet of Things (IOT), cloud computing, big data, artificial intelligence, the demand for innovative talents familiar with new technologies has increased sharply. This has brought challenges and opportunities to university personnel training. In particular, technical talents based on IOT, intelligent control, embedded systems, and big data are in shortage. In recent years, many colleges and universities have set up new majors such as IOT, big data, and artificial intelligence. However, there are still many problems such as single teaching mode and weak practice links during the personnel training. Therefore, a practical training platform for IOT based on cloud services is established. The platform realizes the combination of class learning and web-based learning. It also implements the real-time monitoring and comments in the web-link-web experiment process. It is of great theoretical value and practical value to enhance the experimental effects of the IOT and implement personalized learning recommendations. The main functions include experimental teaching management, real-time monitoring in the experimental process, evaluation of experimental learning status, and other functions. Training platform for IOT based on cloud services develop on the basis of end-to-end communication module based on the cloud services, develop a networked web-link-web training platform. Through the construction of this platform, we can achieve the goal of training high-quality, mastering new high-tech talents, and making education modernization, intellectualization, and informatization.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.