Design of Robotic Fish for Aquatic Environment Monitoring

Maindalkar, Anuradha A.; Ansari, Saniya M.

doi:10.5120/20649-3414

Cited by 4 publications

(3 citation statements)

References 7 publications

(5 reference statements)

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“…These robotsoften equipped with advanced sensors, AI, and machine learning capabilitiesadeptly perform analytical tasks with minimal human intervention. Robotic fishes have been developed by various researchers over the years for different applications such as environmental monitoring, scientific research, and underwater exploration. , For example, Ogurtsov et al devised an autonomous robotic fish equipped with electrochemical sensors to monitor port water quality (Figure -III) . This innovative robotic fish demonstrated the capabilities to independently navigate in the port waters, and facilitate the collection of data related to the heavy metals, phenols, dissolved oxygen, conductivity, and oxidation–reduction potential.…”

Section: Different Types Of Sensing Systems With Elements Of Automationmentioning

confidence: 99%

Automation and Computerization of (Bio)sensing Systems

Raju,

Elpa,

Urban

2024

ACS Sens.

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Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

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Section: Different Types Of Sensing Systems With Elements Of Automationmentioning

confidence: 99%

Automation and Computerization of (Bio)sensing Systems

Raju,

Elpa,

Urban

2024

ACS Sens.

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“…A 4D model is used to study the oil reservoir's fluctuation over time to evaluate the oil field operation and apply ad hoc treatments. Onshore fields are often routinely monitored using permanent instruments on a daily, quarterly, or annual basis [9,10]. Conversely, sub-merged oil fields are more demanding because the deployment of sensors is not presently permanent in the oil fields underwater.…”

Section: Motivation and Contributionmentioning

confidence: 99%

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

Sathish

Venkata

Anbazhagan

et al. 2023

Telecom

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Oceanographic data collection, disaster prevention, aided navigation, critical observation sub-missions, contaminant screening, and seaward scanning are just a few of the submissions that use underwater sensor hubs. Unmanned submerged vehicles (USVs) or autonomous acoustic underwater vehicles (AUVs) through sensors would similarly be able to explore unique underwater resources and gather data when utilized in conjunction with integrated screen operations. The most advanced technological method of oceanic observation is wireless information routing beneath the ocean or generally underwater. Water bottoms are typically observed using oceanographic sensors that collect data at certain ocean zones. Most research on UWSNs focuses on physical levels, even though the localization level, such as guiding processes, is a more recent zone. Analyzing the presenting metrics of the current direction conventions for UWSNs is crucial for considering additional enhancements in a procedure employing underwater wireless sensor networks for locating sensors (UWSNs). Due to their severely constrained propagation, radio frequency (RF) transmissions are inappropriate for underwater environments. This makes it difficult to maintain network connectivity and localization. This provided a plan for employing adequate reliability and improved communication and is used to locate the node exactly using a variety of methods. In order to minimize inaccuracies, specific techniques are utilized to calculate the distance to the destination. It has a variety of qualities, such as limited bandwidth, high latency, low energy, and a high error probability. Both nodes enable technical professionals stationed on land to communicate data from the chosen oceanic zones rapidly. This study investigates the significance, uses, network architecture, requirements, and difficulties of undersea sensors.

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“…The transceiver also can transmit and receive long-range radio frequency signals for communication with the onshore station. The collected data are used locally or connected to another network for a particular purpose [ 9 ]. Figure 2 illustrates an overview of the UWSN environment.…”

Section: Underwater Wireless Sensor Networkmentioning

confidence: 99%

A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges

Fattah

Gani

Ahmedy

et al. 2020

Sensors

127

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The domain of underwater wireless sensor networks (UWSNs) had received a lot of attention recently due to its significant advanced capabilities in the ocean surveillance, marine monitoring and application deployment for detecting underwater targets. However, the literature have not compiled the state-of-the-art along its direction to discover the recent advancements which were fuelled by the underwater sensor technologies. Hence, this paper offers the newest analysis on the available evidences by reviewing studies in the past five years on various aspects that support network activities and applications in UWSN environments. This work was motivated by the need for robust and flexible solutions that can satisfy the requirements for the rapid development of the underwater wireless sensor networks. This paper identifies the key requirements for achieving essential services as well as common platforms for UWSN. It also contributes a taxonomy of the critical elements in UWSNs by devising a classification on architectural elements, communications, routing protocol and standards, security, and applications of UWSNs. Finally, the major challenges that remain open are presented as a guide for future research directions.

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Design of Robotic Fish for Aquatic Environment Monitoring

Cited by 4 publications

References 7 publications

Automation and Computerization of (Bio)sensing Systems

Automation and Computerization of (Bio)sensing Systems

Review of Localization and Clustering in USV and AUV for Underwater Wireless Sensor Networks

A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges

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