Data Mining for the Internet of Things: Literature Review and Challenges

Abstract

The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

Обеспечение Информационной Безопасности Киберфизических Систем

“…В статье [23] представлен систематический обзор методов интеллектуального анализа данных (Data Mining, DM) с учетом знаний, техники и приложений, включая классификацию, кластеризацию, ассоциациативный анализ, анализ временных рядов и выбросов. Также рассматриваются некоторые новые случаи применения и новые алгоритмы.…”

Influence of on-Device Measurement Analysis on Energy Efficiency in Machine-to-Machine Systems

“…Chen et al [5] introduce an overview of data mining techniques in the area of Internet of Things. They present five data mining functionalities: classification, clustering, association analysis, time series analysis, and outlier analysis.…”

“…Although interlaced with the aforementioned areas, in this paper we use the term of M2M systems for a sensing systems in which end devices collect measurements from sensors, and send them via gateway to the back-end system. M2M systems generate massive data sets which are considered to be of high business value [5]. To extract hidden knowledge from data, data mining algorithms can be applied.…”

Data mining technology based on rough set and genetic algorithm under large data environment

“…Data analysis is the foundation of scientific research, many scientific research is based on data collection and analysis in the current business activities [1][2][3]. The data analysis is always and some special groups of people high IQ behavior, because not every ordinary person can predict future trends or make the right decisions from past sales, but as a business or industry continues to accumulate business data, especially due to the popularity of the database, To manually sort out and understand such a large data source has been the existence of efficiency, accuracy and other issues.…”