Detection of Natural Disasters from the Acoustic Signal Generated by the Aquatic Species Using Dbn Algorithm Through Underwater Communication

• Main Authors: Umadevi, M., Mahesh, A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Science Publishing Corporation 2018
• Subjects: DBN algorithm; Feature extraction algorithm; AWUC; Many Islands; Blue whale
• Online Access: http://www.sciencepubco.com/index.php/IJET/article/view/28352; https://doi.org/10.14419/ijet.v7i4.28.28352

Dangerous natural disasters like earthquake and tsunami occurs very often in many islands and seashore areas without any alerts or symptoms of occurring. It is known to all that these disasters originate from the sea level and transmitted to the ground surface. Species living in the sub aquatic regions are capable of sensing these disasters earlier than their occurrence. Hence an effective technique is proposed in this paper so as to detect the disaster happenings from the acoustic signals generated by the aquatic species. Blue whale in particular is an intelligent species which has capability of sensing the distress condition in the deep underwater region and transmit the alert signal to its peer group. A method to extract the distress alert signal using the DBN algorithm and feature extraction algorithm from the acoustic signals generated by the blue whales is demonstrated and the results are simulated using the CHORUS tool , which is an enhanced framework of MATLAB software. Â