Research Article
Understanding the Trend of Internet of Things Data Prediction
@INPROCEEDINGS{10.1007/978-3-031-50580-5_27, author={Lu Zhang and Lejie Li and Benjie Dong and Yanwei Ma and Yongchao Liu}, title={Understanding the Trend of Internet of Things Data Prediction}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part IV}, proceedings_a={ICMTEL PART 4}, year={2024}, month={2}, keywords={Internet of Things Time series data Data analytics Data prediction Machine learning}, doi={10.1007/978-3-031-50580-5_27} }- Lu Zhang
Lejie Li
Benjie Dong
Yanwei Ma
Yongchao Liu
Year: 2024
Understanding the Trend of Internet of Things Data Prediction
ICMTEL PART 4
Springer
DOI: 10.1007/978-3-031-50580-5_27
Abstract
With the advancement of science and technology in recent years, the Internet of Things has become another technology hotspot after the Internet. It is widely used in various fields under its intelligent processing and reliability of transmission. However, rapid development also brings certain opportunities and challenges. The most prominent is the massive increase in equipment data, which brings huge challenges to the field of data analysis and prediction. Therefore, how to efficiently process and predict the time series data generated by the Internet of Things has become a research hotspot and difficulty. With the improvement of computer indicators in the past ten years, machine learning has developed to a certain extent. Most scholars will use machine learning methods when researching time-series data processing and forecasting of the Internet of Things. Therefore, we provide a preliminary overview of the history and evolution of machine learning-based IoT time-series data analysis and forecasting from a bibliometric perspective.
