Real time marine environment monitoring based on the DGPS and wireless mobile IT solution

2003 ◽  
Author(s):  
Y.C. Park ◽  
J.K. Choi ◽  
H.J. Lee
Keyword(s):  
Real Time ◽  
Marine Environment ◽  
Environment Monitoring ◽  
Marine Environment Monitoring ◽  
Wireless Mobile

scholarly journals Marine Environment Monitoring Based on Virtual Reality and Fuzzy C-Means Clustering Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuehong Zhu ◽  
Ying Han
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Marine Environment ◽  
Clustering Algorithm ◽  
Environment Monitoring ◽  
Real Time Monitoring ◽  
Virtual Reality Technology ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Marine Environment Monitoring

In modern society, with the rapid increase of population and the serious shortage of resources, the marine environment has been destroyed; there are also many people who go out to sea without permission, regardless of the legal constraints, fishing. This kind of behavior leads the marine environment to get worse and worse, so the real-time monitoring of the marine environment is very necessary. The main article marine environment monitoring, virtual reality technology, and fuzzy C-means clustering algorithm combine to improve the efficiency of monitoring and processing power of the data information. Through the application of virtual reality technology in the marine environment monitoring base and real-time simulation of the dynamics of the ocean, the monitoring personnel can understand the emergencies on the sea in time; the fuzzy C-means clustering algorithm is applied to the server receiving the data to classify the data. It is found in the experiment that when virtual reality technology and fuzzy C-means clustering algorithm are not used, the data of marine environment monitoring takes more than 1.3 s to return to the server, but, after applying two advanced technologies, the return efficiency is greatly improved, and the time consumed is less than 0.82 s. The results show that virtual reality technology and fuzzy C-means clustering algorithm can improve the efficiency of environmental monitoring, and through virtual reality technology, real-time monitoring of the marine environment can be achieved; in the absence of people out to sea, the actual situation on the sea can be clearly understood; and fuzzy C-means clustering algorithm can improve the speed of data processing, so that the monitoring personnel can solve the problem faster.

The Design of the Monitoring System Based on Marine Environment Buoy

2012 ◽  
Vol 605-607 ◽  
pp. 1769-1771 ◽  
Author(s):  
Xing Hong Kuang ◽  
Zhi Yu Wang ◽  
Ceng Yang ◽  
Hai Bo Huo ◽  
Yan Xiang Wu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Marine Environment ◽  
Remote Monitoring ◽  
Software System ◽  
Environment Monitoring ◽  
The Real ◽  
Marine Environment Monitoring ◽  
Monitoring Software

The real-time monitor ability will be improved when the Ocean buoy technology is used on the marine environment monitoring. The design of the monitoring system based on marine environment buoy were described in detail in the paper, which including the integrated hardware and the monitoring software. The ocean remote monitoring function was implemented using the developed software system.

scholarly journals Compressed Sensing of 3D Marine Environment Monitoring Data Based on Spatiotemporal Correlation

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 32634-32649
Author(s):  
Ge Liu ◽  
Guosheng Rui ◽  
Wenbiao Tian ◽  
Liyao Wu ◽  
Tiantian Cui ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Marine Environment ◽  
Monitoring Data ◽  
Environment Monitoring ◽  
Spatiotemporal Correlation ◽  
Marine Environment Monitoring

Implementation of Marine Environment Monitoring Data Quality Control System

2014 ◽  
Vol 926-930 ◽  
pp. 4254-4257 ◽  
Author(s):  
Jin Xu ◽  
Da Tao Yu ◽  
Zhong Jie Yuan ◽  
Bo Li ◽  
Zi Zhou Xu
Keyword(s):  
Quality Control ◽  
Control System ◽  
Data Quality ◽  
Marine Environment ◽  
Quality Control System ◽  
Monitoring Data ◽  
Environment Monitoring ◽  
Data Quality Control ◽  
Labor Costs ◽  
Marine Environment Monitoring

Traditional artificial perception quality control methods of marine environment monitoring data have many disadvantages, including high labor costs and mistakes of data review. Based on GIS spatial analysis technology, Marine Environment Monitoring Data Quality Control System is established according to the Bohai Sea monitoring regulation. In the practical application process, it plays the role of improving efficiency of quality control, saving the manpower and financial resources. It also provides an important guarantee for the comprehensive analysis and management of marine environment data.

scholarly journals Implementation and validation of a new operational wave forecasting system of the Mediterranean Monitoring and Forecasting Centre in the framework of the Copernicus Marine Environment Monitoring Service

2018 ◽  
Vol 18 (10) ◽  
pp. 2675-2695 ◽  
Author(s):  
Michalis Ravdas ◽  
Anna Zacharioudaki ◽  
Gerasimos Korres
Keyword(s):  
Mediterranean Sea ◽  
Marine Environment ◽  
Model Performance ◽  
Environment Monitoring ◽  
Marine Research ◽  
Forecasting System ◽  
The Mediterranean ◽  
Marine Environment Monitoring ◽  
Monitoring Service ◽  
Wave Forecasting

Abstract. Within the framework of the Copernicus Marine Environment Monitoring Service (CMEMS), an operational wave forecasting system for the Mediterranean Sea has been implemented by the Hellenic Centre for Marine Research (HCMR) and evaluated through a series of preoperational tests and subsequently for 1 full year of simulations (2014). The system is based on the WAM model and it has been developed as a nested sequence of two computational grids to ensure that occasional remote swell propagating from the North Atlantic correctly enters the Mediterranean Sea through the Strait of Gibraltar. The Mediterranean model has a grid spacing of 1∕24∘. It is driven with 6-hourly analysis and 5-day forecast 10 m ECMWF winds. It accounts for shoaling and refraction due to bathymetry and surface currents, which are provided in offline mode by CMEMS. Extensive statistics on the system performance have been calculated by comparing model results with in situ and satellite observations. Overall, the significant wave height is accurately simulated by the model while less accurate but reasonably good results are obtained for the mean wave period. In both cases, the model performs optimally at offshore wave buoy locations and well-exposed Mediterranean subregions. Within enclosed basins and near the coast, unresolved topography by the wind and wave models and fetch limitations cause the wave model performance to deteriorate. Model performance is better in winter when the wave conditions are well defined. On the whole, the new forecast system provides reliable forecasts. Future improvements include data assimilation and higher-resolution wind forcing.

scholarly journals Designing innovative services for marine environment monitoring using earth-observation tools in the frame of the pre-commercial procurement project MARINE-EO

2018 ◽  
Author(s):  
Ioanna Varkitzi ◽  
Anestis Trypitsidis ◽  
Alkis Astyakopoulos ◽  
Constantinos Rizogiannis ◽  
Beatriz Gómez Miguel ◽  
...  
Keyword(s):  
Marine Environment ◽  
Earth Observation ◽  
Environment Monitoring ◽  
Observation Tools ◽  
Marine Environment Monitoring
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