An early warning model for student performance based on machine learning algorithms in the context of big data in education

Nan Jia; Zhengye Li; Ling Jia

doi:10.1117/12.2628596

22 April 2022 An early warning model for student performance based on machine learning algorithms in the context of big data in education

Nan Jia, Zhengye Li, Ling Jia

Author Affiliations +

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121741E (2022) https://doi.org/10.1117/12.2628596
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

With the development of society, environmental problems are becoming more and more important. We should develop the environment while developing the economy. People's awareness of environmental protection should also continue to improve, and begin to pay more attention to ecology. Cities all over the world should take the road of ecological development and build ecological cities. The construction of ecological city is the symbol of human civilization and the inevitable trend of urban development. This leads to a very important concept in eco-city, that is the plant wall. Based on this, the author designed a simple intelligent planting system based on SCM. The system uses MCU "Arduino Uno R3" as the main control chip. The photosensitive resistance sensor and humidity sensor are used to measure the current information and feed back to the MCU. LED lights and feeders work to realize automatic watering, lighting and feeding fish on time. Finally, the entire system can be controlled through a wireless connection to the phone. In this paper, the hardware and software parts of the system are mainly designed, and the parameters of the system are tested, which basically realize the function and improve the intelligent degree of plant planting.

Citation Download Citation

Nan Jia, Zhengye Li, and Ling Jia "An early warning model for student performance based on machine learning algorithms in the context of big data in education", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121741E (22 April 2022); https://doi.org/10.1117/12.2628596

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