Research and Application of Internet of Things in Monitoring System of Marine Environment
|School||Shanghai Ocean University,|
|Course||Applied Computer Technology|
|Keywords||internet of things marine environment monitoring wireless sensornetworks genetic clustering algorithm|
In recent years, the exploitation and utilization of oceanic resources of our countryhave increased the pollution of the ocean environment, and marine naturaldisasters occurred frequently, which has seriously affected the marine ecologicalenvironment and caused huge economic loss and the society affects. Therefore, it is veryimperative to protect the marine environment.Marine environment monitoring is an important part of protectingmarine environment. The marine monitoring technology and ability directly affect to thelevel and result of marine resource development and environment protection.Combining with Internet of Things, this paper presents the monitoring system of marineenvironment based on the Internet of Things, which can realize intelligent monitoringof the marine environment and achieve the goals of measurement parameters integration,modular system, real-time demonstration of data transmitting and monitoring serviceintegration in marine environment monitoring.In this paper, basing on the actual needs and development trend of marineenvironment monitoring, the functions need to be realized of the system is clear. Theresearch content includes monitoring data transmission, data integration, databasemanagement and data analysis and assurance. With the research goal of constructing aneffective monitoring system of marine environment, the monitoring system of marineenvironment is designed based on the Internet of Things, which includes dataacquisition subsystem, data monitoring terminal and information managementsubsystem.In the section of data acquisition subsystem, a self-organization and multi-hopnetwork system is composed by a large number of sensor nodes using a wirelesscommunications mode in the monitoring area. The data of marine environmentalelements are sent to the data monitoring terminal by ZigBee wireless communication.The real-time monitoring data are transferred to the monitoring center by3G from data monitoring terminal. In order to achieve better overall–management of monitoring area,video surveillance system has been taken and the video data is sent to the monitoringcenter by the wireless microwave communication. The information managementsubsystem of the monitoring center is based on the object-oriented developing thoughtsand realized the visualization function by GIS. The data warehouse of monitoring centeris applied to manage the monitoring data and computational data. VC++6.0has beenused to realize the programming of visual interface. ADO controls are used toconnect the database and call data. MATLAB is taken as the computing engine tocalculate a variety of analysis model and early-warning model. The mix-programtechnology is adopted to realize the effective development of early-warning and forecastsystem of marine environment monitoring. The system realizes the function ofmanaging the monitoring information online and the release, query and analyses of theearly-warning information.Finally, the paper discussed the application of data mining algorithm in theanalysis of water quality data based on cluster analysis. Traditional Fuzzy c-meansclustering algorithm (FCM) is a local optimization algorithm, which has the defect ofinitialization-dependence and is difficult to obtain the global optimal solution. Geneticalgorithm can obtain the global approximate optimal solution of optimization problem.Therefore, combined of the two methods above, a method based on genetic clustering ofspace vector is proposed to process the monitoring data of marine environment and amodel of water quality evaluation model is established in the end. This method canreduce data processing greatly and obtain scientific and reasonable results. Great resultshave been achieved in processing the monitoring data of marine environment using themethod based on genetic clustering.The results of the research provides important reference and guidance for furtherresearch and development of the intelligent monitoring and disaster forecasting systemof the marine environment in the future. It also can provide technical support for thecountry’s marine administrative department to conduct comprehensive management ofthe marine environment and rational exploitation and utilization of marine resources.