An Information Interface Quantized Evaluation Method for Wireless Sensor Networks

DOI

10.2991/tlicsc-18.2018.53How to use a DOI?

Keywords

Wireless Sensor Networks; Information Interface; Quantized Evaluation Method; Qualitative analysis; Attractiveness.

Abstract

In the global-scaled internet of things, the wireless sensor networks play an important role of collecting information. The sensors are developing towards the integrated information sensor and complex information may be displayed. To obtain the comprehensive information rapidly and precisely through the sensor information interface, the visual appeal-oriented interface is important. In this paper, we proposed a preference-based evaluation-fuzzy-quantification method (EFQM) for the optimization of sensor information interface. In this model, the evaluation analysis, the fuzzy computing and the quantitative analysis were combined to quantify the importance of design considerations for the sensor information interface respectively. The characteristic of proposed method is that the qualitative analysis and quantitative analysis are combined to overcome the respective drawbacks. The results of experiment verified the proposed method could analysis the factors of design considerations quantitatively, and the proposed approach could improve the visual appeal of the sensor information interface.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Min Liu
AU  - Jun Wu
AU  - Liubin Song
AU  - Litao Chen
AU  - Xiaohao Mo
PY  - 2018/12
DA  - 2018/12
TI  - An Information Interface Quantized Evaluation Method for Wireless Sensor Networks
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 329
EP  - 335
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.53
DO  - 10.2991/tlicsc-18.2018.53
ID  - Liu2018/12
ER  -