research-article

POSEIDON - Passive-acoustic Ocean Sensor for Entertainment and Interactive Data-gathering in Opportunistic Nautical-activities

Authors:

Dinarte Vasconcelos,

Valentina NisiAuthors Info & Claims

DIS '18: Proceedings of the 2018 Designing Interactive Systems Conference

Pages 999 - 1011

https://doi.org/10.1145/3196709.3196752

Published: 08 June 2018 Publication History

Abstract

Recent years demonstrate an increased interest in Passive Acoustic Monitoring (PAM) applications when studying cetaceans. However, they remain expensive underwater systems and targeted for industrial and military purposes. While the usage of smartphones as acoustic sensors has been observed in terrestrial environments, ocean and nautical PAM applications remain greatly unexplored. This paper presents the design, deployment and testing of a POSEIDON system, used for real-time augmentation of whale-watching experiences. We collect and use cetaceans' vocal call acoustic samples (clicks, moans and whistles) and apply machine learning for offline model training and prediction. When discriminating the calls, we find that Extra Trees and Gradient Boosting outperform other classifiers (>0.95 confidence threshold). Collected samples are at disposal to citizen scientists and marine biologists. Future studies involve real-time on-boat user testing.

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Published In

cover image ACM Conferences

DIS '18: Proceedings of the 2018 Designing Interactive Systems Conference

June 2018

1418 pages

ISBN:9781450351980

DOI:10.1145/3196709

General Chairs:
Ilpo Koskinen
University of Twente
,
Youn-kyung Lim
KAIST
,
Program Chairs:
Teresa Cerratto-Pargman
Stockholm University
,
Kenny Chow
The Hong Kong Polytechnic University
,
William Odom
Simon Fraser University

Copyright © 2018 ACM.

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Published: 08 June 2018

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Regional Government of Madeira
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DIS '18: Designing Interactive Systems Conference 2018

June 9 - 13, 2018

Hong Kong, China

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DIS '18 Paper Acceptance Rate 107 of 487 submissions, 22%;

Overall Acceptance Rate 1,158 of 4,684 submissions, 25%

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https://dl.acm.org/doi/10.1145/3679318.3685372
Dar FLiyanage MRadeta MYin ZZuniga AKosta STarkoma SNurmi PFlores H(2023)Upscaling Fog Computing in Oceans for Underwater Pervasive Data Science Using Low-Cost Micro-CloudsACM Transactions on Internet of Things10.1145/35758014:2(1-29)Online publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1145/3575801
Zambon TBassetti CPrandi C(2023)A Close Look at Citizen Science Through the HCI Lens: A Systematic Literature ReviewHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42283-6_23(414-435)Online publication date: 25-Aug-2023
https://doi.org/10.1007/978-3-031-42283-6_23
Dionisio MMendes MFernandez MNisi VNunes N(2022)Aqua: Leveraging Citizen Science to Enhance Whale-Watching Activities and Promote Marine-Biodiversity AwarenessSustainability10.3390/su14211420314:21(14203)Online publication date: 31-Oct-2022
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Radeta MZuniga AMotlagh NLiyanage MFreitas RYoussef MTarkoma SFlores HNurmi P(2022)Deep Learning and the OceansComputer10.1109/MC.2022.314308755:5(39-50)Online publication date: 1-May-2022
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