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An integrated information system for snowmelt flood early-warning based on internet of things

Author

Listed:
  • Shifeng Fang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences)

  • Lida Xu

    (Institute of Computing Technology, Chinese Academy of Sciences
    Old Dominion University)

  • Yunqiang Zhu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences)

  • Yongqiang Liu

    (Xinjiang University
    Xinjiang University)

  • Zhihui Liu

    (Xinjiang University
    Xinjiang University)

  • Huan Pei

    (Yanshan University)

  • Jianwu Yan

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences)

  • Huifang Zhang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences)

Abstract

Floods and water resource management are major challenges for human in present and the near future, and snowmelt floods which usually break out in arid or semi-arid regions often cause tremendous social and economic losses, and integrated information system (IIS) is valuable to scientific and public decision-making. This paper presents an integrated approach to snowmelt floods early-warning based on geoinformatics (i.e. remote sensing (RS), geographical information systems (GIS) and global positioning systems (GPS)), Internet of Things (IoT) and cloud services. It consists of main components such as infrastructure and devices in IoT, cloud information warehouse, management tools, applications and services, the results from a case study shows that the effectiveness of flood prediction and decision-making can be improved by using the IIS. The prototype system implemented in this paper is valuable to the acquisition, management and sharing of multi-source information in snowmelt flood early-warning even in other tasks of water resource management. The contribution of this work includes developing a prototype IIS for snowmelt flood early-warning in water resource management with the combination of IoT, Geoinformatics and Cloud Service, with the IIS, everyone could be a sensor of IoT and a contributor of the information warehouse, professional users and public are both servers and clients for information management and services. Furthermore, the IIS provides a preliminary framework of e-Science in resources management and environment science. This study highlights the crucial significance of a systematic approach toward IISs for effective resource and environment management.

Suggested Citation

  • Shifeng Fang & Lida Xu & Yunqiang Zhu & Yongqiang Liu & Zhihui Liu & Huan Pei & Jianwu Yan & Huifang Zhang, 2015. "An integrated information system for snowmelt flood early-warning based on internet of things," Information Systems Frontiers, Springer, vol. 17(2), pages 321-335, April.
    • Handle: RePEc:spr:infosf:v:17:y:2015:i:2:d:10.1007_s10796-013-9466-1
    DOI: 10.1007/s10796-013-9466-1
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    References listed on IDEAS

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    2. Waleed A. Hammood & Ruzaini Abdullah Arshah & Salwana Mohamad Asmara & Hussam Al Halbusi & Omar A. Hammood & Salem Al Abri, 2021. "A Systematic Review on Flood Early Warning and Response System (FEWRS): A Deep Review and Analysis," Sustainability, MDPI, vol. 13(1), pages 1-24, January.
    3. Ashish Gupta & Amit Deokar & Lakshmi Iyer & Ramesh Sharda & Dave Schrader, 2018. "Big Data & Analytics for Societal Impact: Recent Research and Trends," Information Systems Frontiers, Springer, vol. 20(2), pages 185-194, April.
    4. Pan Wang & Ricardo Valerdi & Shangming Zhou & Ling Li, 2015. "Introduction: Advances in IoT research and applications," Information Systems Frontiers, Springer, vol. 17(2), pages 239-241, April.
    5. Xiongnan Jin & Sejin Chun & Jooik Jung & Kyong-Ho Lee, 0. "A fast and scalable approach for IoT service selection based on a physical service model," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
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    7. Rui Xu & Changqing Wu & Shengying Zhu & Baodong Fang & Wei Wang & Lida Xu & Wu He, 2017. "A rapid maneuver path planning method with complex sensor pointing constraints in the attitude space," Information Systems Frontiers, Springer, vol. 19(4), pages 945-953, August.
    8. Shan, Siqing & Jia, Yingwei & Zheng, Xianrong & Xu, Xiaobo, 2018. "Assessing relationship and contribution of China's technological entrepreneurship to socio-economic development," Technological Forecasting and Social Change, Elsevier, vol. 135(C), pages 83-90.
    9. Shivam Gupta & Vinayak A. Drave & Surajit Bag & Zongwei Luo, 2019. "Leveraging Smart Supply Chain and Information System Agility for Supply Chain Flexibility," Information Systems Frontiers, Springer, vol. 21(3), pages 547-564, June.
    10. Maria-Lluïsa Marsal-Llacuna, 2019. "How to succeed in implementing (smart) sustainable urban Agendas: “keep cities smart, make communities intelligent”," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(4), pages 1977-1998, August.
    11. Yunqiang Zhu & Peng Pan & Shifeng Fang & Li Xu & Jia Song & Jinqu Zhang & Min Feng, 2016. "The development and application of e-Geoscience in China," Information Systems Frontiers, Springer, vol. 18(6), pages 1217-1231, December.
    12. Hossein Vahidi & Mohammad Taleai & Wanglin Yan & Rajib Shaw, 2021. "Digital Citizen Science for Responding to COVID-19 Crisis: Experiences from Iran," IJERPH, MDPI, vol. 18(18), pages 1-34, September.
    13. Siqing Shan & Xin Wen & Yigang Wei & Zijin Wang & Yong Chen, 2020. "Intelligent manufacturing in industry 4.0: A case study of Sany heavy industry," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 679-690, July.
    14. Yen-Chun Chou & Benjamin B. M. Shao, 2023. "An Empirical Study of Information Technology Capabilities to Enable Value Chain Activities and Interfaces," Information Systems Frontiers, Springer, vol. 25(4), pages 1533-1547, August.

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