Computer vision-based system for tracking and monitoring aquatic animals

To monitor and manage the health status of domestic, pet, and aquatic animals, the Indian government has expanded the use of Internet of Things (IoT) and Wireless Sensor Networks (WSN) for livestock through digitisation, national start-up organisations, and programs promoting technological breakthroughs. Aquatic animal owners and farmers may now easily track and monitor the health of their animals thanks to the advent of Internet of Things (IoT) technologies and intelligent systems that use wireless technology and real-time sensors. By incorporating IoT into current systems or creating IoT systems with WSN that are safe for newborn and young aquatic animals, the full process of remotely monitoring the health of these domestic aquatic creatures can be accomplished. With the use of Internet of Things (IoT) technology, which is extensively used in many electronic products, it is possible to remotely track the location, health, and other pertinent behaviours of domestic, farm, and wild aquatic animals. The Internet of Things (IoT) and its collaborative technologies, such as Wireless Sensor Network, Artificial Intelligence, Data Analytics, and Automation, will enable owners and carers of aquatic creatures and gadgets to interact with anything, anywhere, at any time. The lifespan of such sensor nodes is determined by their power supply and energy consumption, which are frequently controlled by the communication subsystem. The suggested framework needs to concentrate more on maximising the data transmission rate using a variety of packet handling techniques

Authors

Publication Details

Journal
International Journal of Aquatic Research and Environmental Studies
Published
2025-05-20
DOI
https://doi.org/10.70102/ijares/v5i1/5-1-03
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
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article

Computer vision-based system for tracking and monitoring aquatic animals

D R Ganesh, Naresh Kaushik, Nittin Sharma, J. Albert Mayan et al.
International Journal of Aquatic Research and Environmental Studies
Water Quality Monitoring and Analysis
article

Computer vision-based system for tracking and monitoring aquatic animals

D R Ganesh, Naresh Kaushik, Nittin Sharma, J. Albert Mayan, Trapty Agarwal, G M Srinath, Praveen Priyaranjan Nayak
article en

Abstract

To monitor and manage the health status of domestic, pet, and aquatic animals, the Indian government has expanded the use of Internet of Things (IoT) and Wireless Sensor Networks (WSN) for livestock through digitisation, national start-up organisations, and programs promoting technological breakthroughs. Aquatic animal owners and farmers may now easily track and monitor the health of their animals thanks to the advent of Internet of Things (IoT) technologies and intelligent systems that use wireless technology and real-time sensors. By incorporating IoT into current systems or creating IoT systems with WSN that are safe for newborn and young aquatic animals, the full process of remotely monitoring the health of these domestic aquatic creatures can be accomplished. With the use of Internet of Things (IoT) technology, which is extensively used in many electronic products, it is possible to remotely track the location, health, and other pertinent behaviours of domestic, farm, and wild aquatic animals. The Internet of Things (IoT) and its collaborative technologies, such as Wireless Sensor Network, Artificial Intelligence, Data Analytics, and Automation, will enable owners and carers of aquatic creatures and gadgets to interact with anything, anywhere, at any time. The lifespan of such sensor nodes is determined by their power supply and energy consumption, which are frequently controlled by the communication subsystem. The suggested framework needs to concentrate more on maximising the data transmission rate using a variety of packet handling techniques

International Journal of Aquatic Research and Environmental StudiesVol. 5(1)
Openalex Percentile: Top 86%
Water Quality Monitoring and Analysis
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