bSpace: A Data Cleaning Approach for RFID Data Streams Based on Virtual Spatial Granularity

Author(s):  
Baoyan Song ◽  
Pengfei Qin ◽  
Hao Wang ◽  
Weihong Xuan ◽  
Ge Yu
Keyword(s):  
2010 ◽  
Vol 21 (4) ◽  
pp. 632-643 ◽  
Author(s):  
Yu GU ◽  
Ge YU ◽  
Xiao-Long HU ◽  
Yi WANG
Keyword(s):  

Author(s):  
Yunhua Gu ◽  
Bao Gao ◽  
Jin Wang ◽  
Mingshu Yin ◽  
Junyong Zhang
Keyword(s):  

2018 ◽  
Vol 7 (3.1) ◽  
pp. 63 ◽  
Author(s):  
R Revathy ◽  
R Aroul Canessane

Data are vital to help decision making. On the off chance that data have low veracity, choices are not liable to be sound. Internet of Things (IoT) quality rates big data with error, irregularity, deficiency, trickery, and model guess. Improving data veracity is critical to address these difficulties. In this article, we condense the key qualities and difficulties of IoT, which impact data handling and decision making. We audit the scene of estimating and upgrading data veracity and mining indeterminate data streams. Also, we propose five suggestions for future advancement of veracious big IoT data investigation that are identified with the heterogeneous and appropriated nature of IoT data, self-governing basic leadership, setting mindful and area streamlined philosophies, data cleaning and handling procedures for IoT edge gadgets, and protection safeguarding, customized, and secure data administration.  


Author(s):  
Hailong Liu ◽  
Zhanhuai Li ◽  
Qun Chen ◽  
Shanglian Peng
Keyword(s):  

Sensors ◽  
2012 ◽  
Vol 12 (4) ◽  
pp. 4187-4212 ◽  
Author(s):  
Libe Valentine Massawe ◽  
Johnson D. M. Kinyua ◽  
Herman Vermaak

Author(s):  
Liao Guoqiong ◽  
Zhou Jun ◽  
Hui Ni ◽  
Huang Xiaomei ◽  
Huang Zhiwei ◽  
...  

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