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Comprehensive Database Creation for Potential Fish Zones Using IoT and ML with Assimilation of Geospatial Techniques

Author

Listed:
  • Sanjeev Kimothi

    (Division of Research & Innovation, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India)

  • Asha Thapliyal

    (Uttarakhand Space Application Centre, Dehradun 248001, India)

  • Rajesh Singh

    (Division of Research & Innovation, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India
    Department of Project Management, Universidad Internacional Iberoamericana, Campeche 24560, CP, Mexico)

  • Mamoon Rashid

    (Department of Computer Engineering, Faculty of Science and Technology, Vishwakarma University, Pune 411048, India
    Research Center of Excellence for Health Informatics, Vishwakarma University, Pune 411048, India)

  • Anita Gehlot

    (Division of Research & Innovation, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India
    Department of Project Management, Universidad Internacional Iberoamericana, Campeche 24560, CP, Mexico)

  • Shaik Vaseem Akram

    (Division of Research & Innovation, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India)

  • Abdul Rehman Javed

    (Department of Cyber Security, Air University, Islamabad 44000, Pakistan
    Department of Electrical and Computer Engineering, Lebanese American University, Byblos P.O. Box 36, Lebanon)

Abstract

The framework for aqua farming database collection and the real-time monitoring of different working functions of aqua farming are essential to enhance and digitalize aqua farming. Data collection and real-time monitoring are attained using cutting-edge technologies, and these cutting-edge technologies are useful for the conservation and advancement of traditional aquatic farming, particularly in hilly areas with sustainable development goals (SDGs). Geo-tagging and geo-mapping of the aqua resources will play an important role in monitoring the species in the aquatic environment and can track the real-time health status, movement, and location, and monitor the foraging behaviors, of aquatic species. This study proposed an architecture with the IoT to manage the aqua resource for eco-sustainability with geospatial data. This study also discussed the geo information systems (GIS)- and geo positioning system (GPS)-based web-based framework for the fisheries sector and the creation of a database for aqua resource management. In the study, the results of database generation for the aqua resource management and the results of the fishpond in the cloud server are presented in detail. Machine learning (ML) is integrated with the framework to analyze the sensor data and geo-spatial data for the identification of any degradation in the water quality. This will provide real-time information to the policymakers for their critical decisions for the further development of aquatic species for enhancing the economy of the state as well as aqua farmers.

Suggested Citation

  • Sanjeev Kimothi & Asha Thapliyal & Rajesh Singh & Mamoon Rashid & Anita Gehlot & Shaik Vaseem Akram & Abdul Rehman Javed, 2023. "Comprehensive Database Creation for Potential Fish Zones Using IoT and ML with Assimilation of Geospatial Techniques," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1062-:d:1027160
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    References listed on IDEAS

    as
    1. Han-Chieh Chao & Hsin-Te Wu & Fan-Hsun Tseng, 2021. "AIS Meets IoT: A Network Security Mechanism of Sustainable Marine Resource Based on Edge Computing," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
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    Cited by:

    1. Lele Sun & Baoxuan Jin, 2023. "Improving NoSQL Spatial-Query Processing with Server-Side In-Memory R*-Tree Indexes for Spatial Vector Data," Sustainability, MDPI, vol. 15(3), pages 1-23, January.

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