research on data mining models for the internet of things (iot)

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Research on Data Mining Models for the Internet of Things (IoT) Shen Bin#, Liu Yuan*, Wang Xiaoyi* #Ningbo Institute of Technology, Zhejiang University Ningbo, China *College of Management, Zhejiang University Hangzhou, China [email protected] 報報報 : 報報報

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Research on Data Mining Models for the Internet of Things (IoT). Shen Bin#, Liu Yuan*, Wang Xiaoyi* #Ningbo Institute of Technology, Zhejiang University Ningbo, China *College of Management, Zhejiang University Hangzhou, China [email protected]. 報告人 : 謝侃呈. Abstract. - PowerPoint PPT Presentation

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Page 1: Research on Data Mining Models for the Internet  of  Things (IoT)

Research on Data Mining Models for the Internet of Things (IoT)

Shen Bin#, Liu Yuan*, Wang Xiaoyi*#Ningbo Institute of Technology, Zhejiang University

Ningbo, China*College of Management, Zhejiang University

Hangzhou, [email protected]

報告人 :謝侃呈

Page 2: Research on Data Mining Models for the Internet  of  Things (IoT)

Abstract

• multi-layer data mining model, distributed data mining model, Grid based data mining model and data mining model from multi-technology integration perspective.– data collection layer– data management layer – event processing layer– data mining service layer

Page 3: Research on Data Mining Models for the Internet  of  Things (IoT)

Abstract

• Grid based data mining model allows Grid framework to realize the functions of data mining.

• Data mining model from multitechnology integration perspective describes the corresponding framework for the future Internet.

Page 4: Research on Data Mining Models for the Internet  of  Things (IoT)

INTRODUCTION

• In a supermarket, there are about 700,000 RFID tag. So for a RFID data stream of supermarket

• if the supermarket has readers that scan the items every second, about 12.6 GB RFID data will be produced per second, and the data will reach 544TB per day.

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Data collection from smart objects of IoT

• Identification and addressing of smart objects• Data abstraction and compression. • Data archive, index, scalability and access control

for IoT data.• Data warehouse and its query language for

multidimensional analysis.• Interoperability and semantic intelligibility for

heterogeneous data of IoT.• Time-series level and event level data aggregation.• Privacy and protection problem in data

management of IoT.

Page 10: Research on Data Mining Models for the Internet  of  Things (IoT)

CONCLUSIONS

• we propose four data mining models for the Internet of Things– multi-layer data mining model– distributed data mining model– mining model– data mining model from multitechnology

• Distributed data mining model can well solve the problem arose from depositing data at different sites