Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

Area of Science:

• Oceanography
• Computer Science
• Engineering

Background:

• The Internet of Underwater Things (IoUT) enables monitoring of dynamic underwater environments using wireless sensor networks.
• Accurate event detection and source localization are crucial for timely responses in underwater monitoring.

Purpose of the Study:

• To develop a novel technique for detecting event coverage and determining event sources in underwater wireless sensor networks.
• To enhance the efficiency and accuracy of event analysis in IoUT applications.

Main Methods:

• A technique is proposed where events are identified by deviations in sensory data from neighboring sensor nodes.
• Sensor nodes relay data to sink nodes, where event coverage is mapped as a weighted graph.
• Event sources are determined as barycenters within the constructed weighted graph.

Main Results:

• The developed technique effectively detects event coverage and identifies event sources.
• Experimental results demonstrate the energy efficiency of the proposed method, particularly in steady network topologies.
• The graph-based representation accurately reflects the extent of sensory data deviation.

Conclusions:

• The proposed technique offers an energy-efficient solution for event detection and source localization in underwater wireless sensor networks.
• This method contributes to more effective monitoring and response strategies within the Internet of Underwater Things.
• The approach shows promise for applications requiring robust and efficient underwater data analysis.