PARTNER FEATURE: According to statistics, the livelihood of more than 3 billion people in the world depends on the ocean and the loss of the natural disaster of more than 60% each year comes from the rainstorm and storm surge. It is important to effectively protect and manage ocean resources and explore the ecological development in the field of ocean information technologies.
As the technical means of observation are increasingly abundant, the data volume has also been continuously increased to the PB level. The effective use of data from different monitoring dimensions becomes the key to the implementation of the intelligent ocean.
ZTE’s Ocean Big Data Application Support (OaS) Platform is that integrates satellite remote sensing, sea-surface buoys, tide meters, and HD cameras to obtain comprehensive ocean data. Through in-depth mining of ocean data, ZTE provides data support and decision-making basis for environmental monitoring and protection, ocean economic planning, ocean disaster prevention and reduction, and ocean academic research.
Big data analysis minimizes the impact of natural disasters
Ocean disaster prevention and post-disaster review are important tasks for coastal cities.
Taking Shenzhen, the coastal city of China for example, Shenzhen is subjected to typhoons in the western Pacific from April to November each year. Since ZTE OaS platform was put into operation, it has improved the efficiency of ocean-related work such as ocean environment monitoring, ocean disaster prevention, ocean space supervision, and ocean economic statistics and analysis. The platform can obtain the current location, strength, direction, and speed of typhoons, and the tropical cyclone forecast information released by the world’s major meteorological organizations in real time. It can be used together with the online monitoring data of offshore seas in Shenzhen and all the historical typhoon information to provide more real-time and reliable typhoon path prediction, and to support reliable decision-making for the impact assessment of waves and storm surges.
The ZTE OaS platform can not only provide real-time typhoon conditions, but also make summary statistics of typhoons in the South Pacific nearly 70 years, which is convenient for researchers to analyze and compare. In addition to the path and intensity information, with real-time monitoring of coastal cameras, the OaS platform can visually display the impact of typhoon based on “wind, rain and wave” in the ocean area by comparing the offshore monitoring information with the offshore impact prediction.
The disaster prevention and mitigation mechanism based on artificial intelligence includes wind and wave impact prediction based on machine learning to support the pre-disaster risk assessment, the video image automatic recognition based on feature model training to support in-disaster emergency monitoring, and post-disaster recovery emergency mechanism to reduce losses caused by ocean disasters.
By building a key frame model, the platform can efficiently mine video contents, identify abnormal situations, and raise alarms automatically to save manpower. The minimum period can reach 5 seconds, which is sufficient for emergency monitoring by combining prediction, early warning and disaster scene.
AI implements the advance prediction of unknown disasters
Red tide is the ocean biological pollution phenomenon. With the impact of human activities, the occurrence frequency of red tides is increasing. Prevention is the key to occurrence of red tides. The ZTE OaS platform can analyze the sea areas where red tides occur over the years, the types of algae that cause red tides, the areas and time of occurrence, and ecological impacts with the online monitoring of ocean meteorological and water quality..
Thus, the occurrence of red tides is related to the overview of seasons and seas. By using the machine learning function, the platform can provide an exponential prediction model to predict red tides in advance, thus reducing the adverse effects on the ocean ecology and the aquaculture of the offshore sea.
Based on the data mining and association analysis, the change of seawater dissolved oxygen and nutrient can be analyzed. The change of the breeding area can also be analyzed in advance to reduce the loss of the breeders. The real-time environmental indicators and water quality of the bathing grounds, together with the number of people in the bathing grounds and vehicle distribution, can provide a basis for public decision making.
Going out of the vicious cycle between destruction and governance
The ocean is full of mystery and unknowns, and also full of resources and opportunities. Economic development and reclamation are causing irreversible damage to the ocean ecology environment. The ZTE OaS platform provided in-depth data mining and high-order association. Thus, an evaluation conclusion can be drawn for the economic projects, providing the optimal development solution.
For example, the water quality, water temperature, pH, dissolved oxygen, and other 17 monitoring indicators of the China White Dolphin Reserve in Lingding Island, Shenzhen are reported by the ZTE OaS platform in real time. Once finding any abnormal indicator, the platform will find the sewage emission source through reverse calculation, and immediately shut down it.
Focus on green ocean economic development
The ocean industry chain is accelerating the expansion into high-end products with high value-added economic benefits. The ocean industrial structure and hierarchy are continuously optimized and improved. With the continuous development of the ocean industry chain, it is increasingly important to judge and analyze the development trend of the green ocean economy. Efficient and timely economic statistics and analysis are the basis, which is exactly where big data technologies are used.
Based on the data governance and trend analysis, the platform can collect statistics on the service data of enterprises, enrich the ocean database to master the scale and development trend of the ocean economy, and establish the ocean industry evaluation model of innovation index. In addition, the platform’s capability of in-depth exploration and high-level associated analysis, combined with the sea area, economic benefits, enterprise types, pollution conditions and ecological values, can help the government to supervise the enterprises operation, make the sea area plan, and set sewage discharge settings, so as to promote the development of green economy.
To date, ZTE has been applying the latest technologies such as cloud computing and block chain to the ocean big data platform, which continuously accesses and enriches ocean data, and cooperating with industry chain manufacturers to develop new service applications, providing better ocean management.
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