kumoh national institute of technology
Networked Systems Lab.

Heidy Indrayani, Rizki Rivai Ginanjar, Dong-Seong Kim, "Leveraging Fingerprinting for Indoor Positioning System in Industrial IoT", pp.206-207, 2018 KICS Fall Conference, Korea University, 17 Nov, 2018 (A) (N2+N4+N8)
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Date : 2018-10-21
Views : 367

This paper aims to analyze indoor positioning system based on fingerprinting and hybrid techniques such as fingerprinting with trilateration for industrial environment. Due to the harsh environment in industrial IoT, hence it is required to develop a location fingerprinting technique to provide accurate and reliable in indoor positioning services. In this paper, several fingerprinting algorithms, which achieves much better positioning accuracy in industrial IoT such as K-Nearest Neighbors (K-NN) and linear programming are analyzed.  Based on the analysis it is shown that fingerprinting technique is suitable to be implemented in industrial IoT environment. 

Presentation of KICS Conference 2018



Q&A


Q : How many (K) did you set in this paper?

A : For this paper, i only introduced the way to localization without the implementation. But for the future i will do.


Weak point : This paper only introduce fingerprinting.

Future Work : Make a Implementation paper about fingerprinting


Attachments
Attachment 1:   ÷ KICS-Fall-Heidy.pdf(269.8KB)