Underwater Networked Wireless Sensor Data Collection for Computational Intelligence Techniques: Issues, Challenges, and Approaches

Abstract

Underwater wireless sensor networks (UWSNs) is emerging as an advance terminology for monitoring and controlling the underwater aquatic life. This technology determines the undiscovered resources present in the water through computational intelligence (CI) techniques. CI here pertains to the capability of a system to acquire a specific task from data or experimental surveillance below the water. In today's time data is considered as the identity for everything that exists in nature, whether that data is related to human beings, machines or any type of device like internet of underwater things (IoUT). The collected data should be correct, complete and fulfill the requirements of a particular task to be done. Underwater data collection is very tough because of sensors mobility due to water drift 3 meters/sec, crest and trough. A lot of packet drop also exists due to underwater conditions that hurdles the data collection process. Various techniques already exists for efficient collection of data below the water but these are not properly classified. This manuscript has summarized the concept of data collection in UWSN along with its classification based on routing. Also, a short discussion about existence of CORONA below the water along with water purification is carried out. Furthermore, some data routing approaches are also analyzed on the basis of quality of service parameters and the current challenges to be tackled during data collection are also discussed. INDEX TERMS Acoustic sensor network, coronavirus (COVID-19), computational intelligence, routing, underwater sensor network DIVYA ANAND received the Ph.D. degree in computer science and engineering and Masters of Technology in information security from the Lovely Professional University. She has expertise in Teaching, Entrepreneurship and Research and Development. She is currently an Assistant Professor with the Lovely Professional University. She has published over 20 conferences and journal articles. Her research interests include networks security, bioinformatics, machine learning, gene identification, big data analytics and computational models.

A review on Diagnosis and Treatment methods for coronavirus disease with sensors

“…The authors of [27] presented different methodologies that allow the underwater detection of coronavirus with the use of various sensors available in the different types of devices. However, they reported reliable results with the proposed system.…”

Anchor Nodes Assisted Cluster-Based Routing Protocol for Reliable Data Transfer in Underwater Wireless Sensor Networks

“…Also, packets are transmitted on the basis of channel conditions and link quality by which reliability of the network is increased but the energy tax is compromised. In [2], authors have addressed different issues and suggested various techniques for efficient data collection in a harsh underwater WSNs. According to them, computational intelligence technique seems a prominent solution for efficient data collection from underwater environments.…”

“…A cube has six sides and eight vertices 2. Cube can also be referred to as a cluster and vice versa hereinafter.VOLUME 4, 2016…”

DACASN: Dynamic ant routing‐based channel accessing cognitive sensor network in Internet of Things

“…11 The initial deployments of WSNs assume that the sensors and base station/sink are static, and researchers are naturally led to the other paradigms of WSNs where sensors and base station are mobile. 12 Such mobile WSNs are expected to find many applications. 13 The simple energy constraints of various densely deployed sensor nodes need a suite of network protocols to set up various network control and management functions such as synchronization, node localization, 14 and network security.…”

“…The growing amount of IoT devices and the essentials of huge data handling would multiply the number of packets, where this issue can be a serious problem to the legacy network architecture 11 . The initial deployments of WSNs assume that the sensors and base station/sink are static, and researchers are naturally led to the other paradigms of WSNs where sensors and base station are mobile 12 . Such mobile WSNs are expected to find many applications 13 .…”