An Information Interface Quantized Evaluation Method for Wireless Sensor Networks
Min Liu, Jun Wu, Liubin Song, Litao Chen, Xiaohao Mo
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.53How to use a DOI?
- Wireless Sensor Networks; Information Interface; Quantized Evaluation Method; Qualitative analysis; Attractiveness.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/tlicsc-18.2018.53 ID - Liu2018/12 ER -