An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles
Abstract Due to a large amount of time‐series data (e.g. precipitation, temperature, humidity) in the air, reliable and fast data collection is a challenging issue. Using an unmanned aerial vehicle (UAV) as a data collector to collect time‐series data is an effective method. However, due to the limi...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-06-01
|
| Series: | IET Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cmu2.12110 |
| _version_ | 1811296881878237184 |
|---|---|
| author | Bing Sun Mingxing Yu Yi Wu Yuanhang Qi Xin Nie Shan Xi |
| author_facet | Bing Sun Mingxing Yu Yi Wu Yuanhang Qi Xin Nie Shan Xi |
| author_sort | Bing Sun |
| collection | DOAJ |
| description | Abstract Due to a large amount of time‐series data (e.g. precipitation, temperature, humidity) in the air, reliable and fast data collection is a challenging issue. Using an unmanned aerial vehicle (UAV) as a data collector to collect time‐series data is an effective method. However, due to the limited storage capacity of the UAV, the UAV must access the sensor multiple times to collect time‐series data from the deployed sensors and dump the data to the data centre, which leads to significantly increased time and cost for data collection mission. To address this challenge, an efficient time‐series data collection framework is proposed based on the Internet of UAVs. In this system, a min‐maximum data processing strategy is adopted based on data value to store the collected time‐series data. Specifically, efficient data compression storage is achieved with minimal loss of precision by extracting the dominant dataset with maximum value. Furthermore, an efficient affine transformation method is proposed to improve the efficiency of the system. Extensive case studies on some real‐world datasets demonstrate that the proposed framework can achieve efficient data management and compressed storage. |
| first_indexed | 2024-04-13T05:56:12Z |
| format | Article |
| id | doaj.art-9dfd23bf242e421fb10b8b403eb9b921 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-13T05:56:12Z |
| publishDate | 2021-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-9dfd23bf242e421fb10b8b403eb9b9212022-12-22T02:59:37ZengWileyIET Communications1751-86281751-86362021-06-0115101315132510.1049/cmu2.12110An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehiclesBing Sun0Mingxing Yu1Yi Wu2Yuanhang Qi3Xin Nie4Shan Xi5School of Economics and Management Harbin Engineering University Harbin ChinaSchool of Economics and Management Harbin Engineering University Harbin ChinaSchool of Data Science and Technology Heilongjiang University Harbin ChinaSchool of Computer Science University of Electronic Science and Technology of China, Zhongshan Institute Zhongshan ChinaSchool of Data Science and Technology Heilongjiang University Harbin ChinaSchool of Data Science and Technology Heilongjiang University Harbin ChinaAbstract Due to a large amount of time‐series data (e.g. precipitation, temperature, humidity) in the air, reliable and fast data collection is a challenging issue. Using an unmanned aerial vehicle (UAV) as a data collector to collect time‐series data is an effective method. However, due to the limited storage capacity of the UAV, the UAV must access the sensor multiple times to collect time‐series data from the deployed sensors and dump the data to the data centre, which leads to significantly increased time and cost for data collection mission. To address this challenge, an efficient time‐series data collection framework is proposed based on the Internet of UAVs. In this system, a min‐maximum data processing strategy is adopted based on data value to store the collected time‐series data. Specifically, efficient data compression storage is achieved with minimal loss of precision by extracting the dominant dataset with maximum value. Furthermore, an efficient affine transformation method is proposed to improve the efficiency of the system. Extensive case studies on some real‐world datasets demonstrate that the proposed framework can achieve efficient data management and compressed storage.https://doi.org/10.1049/cmu2.12110Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere researchOptical, image and video signal processingAerospace controlMobile robotsComputer vision and image processing techniquesData handling techniques |
| spellingShingle | Bing Sun Mingxing Yu Yi Wu Yuanhang Qi Xin Nie Shan Xi An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles IET Communications Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research Optical, image and video signal processing Aerospace control Mobile robots Computer vision and image processing techniques Data handling techniques |
| title | An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles |
| title_full | An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles |
| title_fullStr | An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles |
| title_full_unstemmed | An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles |
| title_short | An efficient data collection framework in the sky: An affine transformation approach based on Internet of unmanned aerial vehicles |
| title_sort | efficient data collection framework in the sky an affine transformation approach based on internet of unmanned aerial vehicles |
| topic | Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research Optical, image and video signal processing Aerospace control Mobile robots Computer vision and image processing techniques Data handling techniques |
| url | https://doi.org/10.1049/cmu2.12110 |
| work_keys_str_mv | AT bingsun anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT mingxingyu anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT yiwu anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT yuanhangqi anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT xinnie anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT shanxi anefficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT bingsun efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT mingxingyu efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT yiwu efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT yuanhangqi efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT xinnie efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles AT shanxi efficientdatacollectionframeworkintheskyanaffinetransformationapproachbasedoninternetofunmannedaerialvehicles |