ISSN 0914-4935
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Fishing Position Detection by Wearable Sensing to Achieve Fishery Support

Hiroaki Taka

(Received October 13, 2018; Accepted December 21, 2018)

Keywords: fishery, wearable sensing, activity recognition, support vector machine

Many types of research focus on supporting fisheries utilizing information and communication technology (ICT) to realize sustainable and efficient fishing industries. However, most of the previous studies focused on monitoring environmental data and fishing vessels. Our study focused on the identification of the timing when a fisherman catches an octopus in pot drift fishing for the North Giant Pacific Octopus to support fishery industries. The support vector machine (SVM) detects the timing by which a fisherman catches an octopus using the feature amounts derived from acceleration data obtained by a wearable device. In this study, the author adopt three types of feature amounts sets for SVM, peak frequency of fast Fourier transform (FFT), statistics, and the combination of peak frequency and statistics. From the evaluation results, the SVM achieved over 90% of the recall. As for the future works, collecting a large amount of data and developing an application to detect the timing of catch will be needed.

Corresponding author: Hiroaki Taka



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