scholarly journals DCEP: Data Collection Strategy with the Estimated Paths in Ocean Delay Tolerant Network

2014 ◽  
Vol 10 (3) ◽  
pp. 518439 ◽  
Author(s):  
Chao Liu ◽  
Zhongwen Guo ◽  
Feng Hong ◽  
Kaishun Wu
Keyword(s):  
Data Collection ◽  
Delay Tolerant Network ◽  
Data Collection Strategy ◽  
Delay Tolerant

scholarly journals Internet of Bikes: A DTN Protocol with Data Aggregation for Urban Data Collection

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2819 ◽  
Author(s):  
Yosra Zguira ◽  
Hervé Rivano ◽  
Aref Meddeb
Keyword(s):  
Data Collection ◽  
Data Aggregation ◽  
Delay Tolerant Network ◽  
Transport Systems ◽  
Intelligent Transport ◽  
Dtn Routing ◽  
Bike Sharing ◽  
Spatiotemporal Aggregation ◽  
Delay Tolerant ◽  
Global World

Intelligent Transport Systems (ITS) are an essential part of the global world. They play a substantial role for facing many issues such as traffic jams, high accident rates, unhealthy lifestyles, air pollution, etc. Public bike sharing system is one part of ITS and can be used to collect data from mobiles devices. In this paper, we propose an efficient, “Internet of Bikes”, IoB-DTN routing protocol based on data aggregation which applies the Delay Tolerant Network (DTN) paradigm to Internet of Things (IoT) applications running data collection on urban bike sharing system based sensor network. We propose and evaluate three variants of IoB-DTN: IoB based on spatial aggregation (IoB-SA), IoB based on temporal aggregation (IoB-TA) and IoB based on spatiotemporal aggregation (IoB-STA). The simulation results show that the three variants offer the best performances regarding several metrics, comparing to IoB-DTN without aggregation and the low-power long-range technology, LoRa type. In an urban application, the choice of the type of which variant of IoB should be used depends on the sensed values.

Online, Asynchronous Data Collection in Qualitative Research

2019 ◽  
pp. 442-467
Author(s):  
Tracy Spencer ◽  
Linnea Rademaker ◽  
Peter Williams ◽  
Cynthia Loubier
Keyword(s):  
Qualitative Research ◽  
Data Collection ◽  
Face To Face ◽  
Research Outcomes ◽  
Data Collection Strategy ◽  
Time Distance ◽  
Privacy Issues

The authors discuss the use of online, asynchronous data collection in qualitative research. Online interviews can be a valuable way to increase access to marginalized participants, including those with time, distance, or privacy issues that prevent them from participating in face-to-face interviews. The resulting greater participant pool can increase the rigor and validity of research outcomes. The authors also address issues with conducting in-depth asynchronous interviews such as are needed in phenomenology. Advice from the field is provided for rigorous implementation of this data collection strategy. The authors include extensive excerpts from two studies using online, asynchronous data collection.

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