Monitoring coastal aquaculture devices in Taiwan with the radio frequency identification combination system

被引:2
作者
Yang, Jen-Han [1 ]
Yu, Lan-Lung [2 ]
Liu, Ching-Tsung [3 ]
Chang, Yi [4 ]
Yang, Jen-Yu [1 ]
Hsu, Tung-Yao [1 ]
Hsiao, Shih-Chun [5 ]
机构
[1] Natl Cheng Kung Univ, Inst Ocean Technol & Marine Affairs, Tainan, Taiwan
[2] Kaohsiung City Govt, Marine Bur, Kaohsiung, Taiwan
[3] Ocean Affairs Council, Kaohsiung, Taiwan
[4] Natl Sun Yat Sen Univ, Grad Inst Marine Affairs, Kaohsiung, Taiwan
[5] Natl Cheng Kung Univ, Dept Hydraul & Ocean Engn, Tainan, Taiwan
关键词
Oyster farming rafts; hybrid RFID system; monitoring system; GPS; drone; AREA EXTRACTION; EVOLUTION;
D O I
10.1080/15481603.2021.2016241
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Marine debris significantly influences the environment and economics of marine ecosystems. Measures to ban illegally discarded materials using monitoring techniques are expected to mitigate marine debris mismanagement. For example, derelict oyster farming rafts along the southwestern coast of Taiwan have been a source of marine debris pollution since the 1980s. An efficient inspection system is an urgent requirement for monitoring oyster farming areas and, is expected to implement control and surveillance measures for litter discarded from coastal fisheries. To address this issue, this study examined combinations of radio frequency identification (RFID), drone archiving, and onshore receiving systems to ascertain the positions of oyster rafts and their owners with digitally tagged labels. The results showed that the two proposed monitoring systems are feasible for use in marine environments. The RFID signals archived by the drone reached 100% of the 200 tags with a spatial bias ranging from 2.38 to 59.99 m. RFID-GPS hybrid tag signals received by the onshore station covered 100% of the 20 tags with spatial bias ranging from 1.27 to 10.47 m. The RFID-GPS hybrid system was confirmed as a feasible approach for monitoring oyster rafts within 3 km of the coast. The real-time (1 h intervals) position and attributes of each raft detected by the system indicated that our designed techniques enhance responsible fishery surveillance and management of coastal aquaculture worldwide.
引用
收藏
页码:96 / 110
页数:15
相关论文
共 53 条
  • [1] Allegretti M., 2015, WIRELESS SENSOR NETW, V7, P13, DOI [10.4236/wsn.2015.72002, DOI 10.4236/WSN.2015.72002]
  • [2] Bae S.M., 2016, 2016 INT C INF SCI S, DOI 10.1109/ICISSEC.2016.7885849
  • [3] Flood Monitoring Using Satellite-Based RGB Composite Imagery and Refractive Index Retrieval in Visible and Near-Infrared Bands
    Ban, Hyun-Ju
    Kwon, Young-Joo
    Shin, Hayan
    Ryu, Han-Sol
    Hong, Sungwook
    [J]. REMOTE SENSING, 2017, 9 (04)
  • [4] Fish Tagging via RFID and Bluetooth: Crowdsourced Fish Tracking Through Better Reporting Tools
    Bennett, Andrew
    Barrett, David
    Vandor, Isaac
    Soltan, Katerina
    Cho, Yoonyoung
    Lutcavage, Molly
    Lam, Chi Hin
    [J]. OCEANS 2016 MTS/IEEE MONTEREY, 2016,
  • [5] BIM, 2007, LOT 3 EV VAR MARK BU, V93
  • [6] Rapid determination of chemical and physical properties in marine sediments using a near-infrared reflectance spectroscopic technique
    Chang, CW
    You, CF
    Huang, CY
    Lee, TQ
    [J]. APPLIED GEOCHEMISTRY, 2005, 20 (09) : 1637 - 1647
  • [7] Chen C.-K., 2010, ISPRS J PHOTOGRAMM, V15, P167, DOI [10.6574/JPRS.2010.15(2).3, DOI 10.6574/JPRS.2010.15(2).3]
  • [8] RFID-based location based services framework for alerting on black spots for accident prevention
    Ochieng, Wilson Ogutu
    Cheruiyot, Kipruto Wilson
    Okeyo, George
    [J]. EGYPTIAN INFORMATICS JOURNAL, 2022, 23 (01) : 65 - 72
  • [9] Cruz R.D., 2019, 2019 IEEE 10 ANN INF, DOI 10.1109/IEMCON.2019.8936285
  • [10] CUI J, 2011, OCEANS-IEEE, pN1070