scholarly journals Synchronization of Catch Fish Data in Fisheries e-Logbook with a Vessel Monitoring System

2021 ◽  
Vol 2 (1) ◽  
pp. 46-54
Author(s):  
Abdi Wahab ◽  
Bayu Waseso ◽  
Hadi Pranoto
Keyword(s):  
Monitoring System ◽  
Data Synchronization ◽  
Fishing Vessel ◽  
Catch Data ◽  
The Future ◽  
Fish Catch

Indonesia as an archipelago country has many residents whose livelihoods is fishermen. Traditional fishermen who are scattered in various provinces need a tool that can help to record fish catch data after they sail. This study aims to propose a method for synchronizing fish catch data between e-logbook and a fishing vessel monitoring system. The Unix timestamp reference was used to help synchronize fish catch data with the position in the monitoring system, and it was expected to run well. The results of this study are fisheries e-logbooks for Android devices equipped with data synchronization features. In the future, it would be better if a tool was made to help transmit data from the middle of the sea for traditional fishermen.

scholarly journals Assessing the Capacity of Adaptive Policy Pathways to Adapt on Time by Mapping Trigger Values to Their Outcomes

2019 ◽  
Vol 11 (6) ◽  
pp. 1716 ◽  
Author(s):  
Luciano Raso ◽  
Jan Kwakkel ◽  
Jos Timmermans
Keyword(s):  
Monitoring System ◽  
Decision Makers ◽  
Level Of Confidence ◽  
Adaptive Policy ◽  
Misclassification Errors ◽  
The Future ◽  
Adaptive Action ◽  
The Face

Climate change raises serious concerns for policymakers that want to ensure the success of long-term policies. To guarantee satisfactory decisions in the face of deep uncertainties, adaptive policy pathways might be used. Adaptive policy pathways are designed to take actions according to how the future will actually unfold. In adaptive pathways, a monitoring system collects the evidence required for activating the next adaptive action. This monitoring system is made of signposts and triggers. Signposts are indicators that track the performance of the pathway. When signposts reach pre-specified trigger values, the next action on the pathway is implemented. The effectiveness of the monitoring system is pivotal to the success of adaptive policy pathways, therefore the decision-makers would like to have sufficient confidence about the future capacity to adapt on time. “On time” means activating the next action on a pathway neither so early that it incurs unnecessary costs, nor so late that it incurs avoidable damages. In this paper, we show how mapping the relations between triggers and the probability of misclassification errors inform the level of confidence that a monitoring system for adaptive policy pathways can provide. Specifically, we present the “trigger-probability” mapping and the “trigger-consequences” mappings. The former mapping displays the interplay between trigger values for a given signpost and the level of confidence regarding whether change occurs and adaptation is needed. The latter mapping displays the interplay between trigger values for a given signpost and the consequences of misclassification errors for both adapting the policy or not. In a case study, we illustrate how these mappings can be used to test the effectiveness of a monitoring system, and how they can be integrated into the process of designing an adaptive policy.

scholarly journals Futurevolc: A European volcanological supersite observatory in Iceland, a monitoring system and network for the future

2013 ◽  
Author(s):  
Colm Jordan ◽  
Freysteinn Sigmundsson ◽  
Kristin Vogfjord ◽  
Magnus T. Gudmundsson ◽  
Ingvar Kristinsson ◽  
...  
Keyword(s):  
Monitoring System ◽  
The Future

Fish catch data: Less than what meets the eye

Marine Policy ◽  
2013 ◽  
Vol 42 ◽  
pp. 268-269 ◽  
Author(s):  
David J. Agnew ◽  
Nicolas L. Gutiérrez ◽  
Doug S. Butterworth
Keyword(s):  
Catch Data ◽  
Fish Catch

scholarly journals Using the “mean temperature of the catch” to assess fish community responses to warming in a temperate lake

2021 ◽  
Author(s):  
Külli Kangur ◽  
Erki Tammiksaar ◽  
Daniel Pauly
Keyword(s):  
Fish Community ◽  
Time Lag ◽  
Segmented Regression ◽  
Lake Peipsi ◽  
Data Set ◽  
Preferred Temperature ◽  
Catch Data ◽  
Mean Temperature ◽  
Fish Catch ◽  
The Mean

AbstractThis contribution applies the “mean temperature of the catch” (MTC) concept of Cheung et al. (Nature 497:365–368, 2013) to fish catch data for Lake Peipsi, Estonia/Russia, covering the years 1931 to 2019. The preferred temperature of each of the ten target fish species was obtained from the literature, and combined with the species-specific catch data to obtain MTC values for each year. The analysis of the MTC time series thus obtained with a segmented regression yielded two trend lines, one horizontal at 14.5 °C (1931–1986), and the other (1987–2019) ascending with a slope 0.85 °C·decade−1. Overall, the segmented regression model explains over half of the variance of the MTC data set (multiple R2 = 0.53; adjusted R2 = 0.51). Lake surface water temperatures correlate with MTC, even though weakly (r = 0.30), when considering a 2-year time lag. The fish community of the shallow Lake Peipsi reacts more strongly to temperature changes than marine ecosystems so far studied using the MTC.

scholarly journals Detection of pelagic habitats and abundance of skipjack tuna in relation to the environment in the Indian Ocean around Sri Lanka

2019 ◽  
Author(s):  
Thushani Suleka Madhubha Elepathage ◽  
Danling Tang
Keyword(s):  
Monsoon Season ◽  
Remote Sensing Data ◽  
Cumulative Distribution ◽  
Optimum Level ◽  
Skipjack Tuna ◽  
Chl A ◽  
Catch Data ◽  
South West Monsoon ◽  
Pelagic Habitat ◽  
Fish Catch

Using remote sensing data of sea surface temperature (SST), chlorophyll-a (Chl-a) together with catch data, the pelagic hotspots of Skipjack tuna (SKPJ) were identified. MODIS/Aqua satellite data and the fish catch data were obtained during 2002-2016 period. Empirical cumulative distribution frequency (ECDF) model of satellite-based oceanographic data in relation to skipjack fishing was used for the initial statistical analysis and the results showed that key pelagic habitat corresponded mainly with the 0.4 – 0.7 mg m-3 Chl-a concentration. Chl-a represents the phytoplankton that attracts the food items of SKPJ like zooplankton and nekton The favorable SST range for SKPJ is 26 - 27 0C which provides suitable thermocline and an optimum level of upwelling to circulate nutrients needed for the primary production. The high total catches and CPUEs were found within the months of September to December and the optimum levels of Chl-a, SST also were observed in similar months. Hence, the South-West monsoon season was identified as the best and peak season of SKPJ fisheries. SST and Chl-a are important indicators to detect the habitats of SKPJ and the maps prepared can be used in the future to cost-effectively and efficiently identify and demarcate the biological conservation regions or fisheries zones of SKPJ. According to GAM the 0.3 - 0.6 mg m-3 Chl-a, 28 - 28.5 0C SST in Western and 0.25 - 0.3 mg m-3 Chl-a and 28.5 - 28.80C SST in Eastern were found as highly correlated predictor variables value ranges with SKPJ abundance. The deviances explained in above areas in GAM were 90.8% and 61.4% respectively. The GAM was considered as a robustly dealing method with nonlinear relationships and it can be used to model the fish catch abundance with influencing variables significantly since it could predict the CPUE values greater than 90% similarly to nominal CPUEs in both subregions of the study area.

scholarly journals Prediction by Soft Computing, Planning, and Strategy Building of Aquatic Catch: Chilika Lagoon, Odisha, India

2021 ◽  
pp. 47-62
Author(s):  
Siba Prasad Mishra ◽  
Ananta Charan Ojha
Keyword(s):  
Random Forest ◽  
Soft Computing ◽  
Tidal Inlet ◽  
Chilika Lagoon ◽  
Catch Data ◽  
Soft Computing Method ◽  
Hydraulic Regime ◽  
Fish Catch ◽  
And Migration ◽  
Strategy Building

Introduction: The Chilika lagoon in south Odisha, India was ecologically degraded from 1985 onwards by reduction of its aquatic (fish + prawn + shrimp) catches along with reduction in salinity, hydraulic regime, water exchange, aquatic weeds invasion, and sediment influx. The aquatic catch was 8669MT in year 1985-1986 gradually reduced to 1274MT during 1995-1996 from Odisha Fisheries Dept. records which resulted in poor economic condition of ≈0,2million fishermen and they migrated to adopt other livelihood. One direct tidal inlet dredged (Sipakuda) and Naraj barrage in the apex of South Mahanadi Delta were the major hydraulic interventions made to regain hydraulic regime. After the hydraulic interventions, the eco system restored, and the aquatic catch surged but it was insufficient to livelihood sustenance for the fishermen community of the Chilika,     so   that  they are forced for alternate occupation and migration. Methodologies: Fish catch data collected for 30 years and soft computing models linear regression, Multi Linear Perception (ANN), SMOorg (SVM) and the Random Forest algorithms (Weka Software) are used to predict the fish catch data of the lagoon for coming decade from 2020 to 2030. The effects of major hydraulic interventions are analyzed and the soft computing method of the fish and shrimp catch prediction of the Chilika has been attempted for the first time except some statistical approaches. Results: The Random Forest is found to be the preferred algorithm followed by the MLP model. The amount of catch remained around 12-13TMT if the variables and the present status of the lagoon is maintained. The combined effect of the Sipakuda Tidal inlet and the effective operation of the Naraj barrage have maintained the sustainable aqua catch. The present study shall be an immense help for the lake users and policy makers to augment aquatic catch, and alternate livelihood fishers community of the Chilika lagoon.

The Design of the Supervisory System Based on the SOPC

2011 ◽  
Vol 383-390 ◽  
pp. 4103-4108
Author(s):  
Ming Zhang
Keyword(s):  
Monitoring System ◽  
Supervisory System ◽  
The Future ◽  
Software And Hardware

System on a programmable chip is designed for the development of embedded system．By embedding a micro_ processor in FPGA．SOPC not only takes the advantage of micro-processor system which is rich in software and hardware resource．it also is a part of FPGA system which has fast logic．So SOPC is considered to be the direction of the future in embedded filed. Meanwhile．This thesis has interpreted the application of SOPC in the monitoring system, and tries to find the advantage and features of the SOPC system by practical designs.

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