KEYWORDS: Sensors, Environmental sensing, Data storage, Data analysis, Environmental monitoring, Data visualization, Data processing, Data acquisition, Visualization, Humidity
Environmental sensors play a crucial role in modern society. They provide strong support for environmental protection, resource management, and sustainable development by monitoring and perceiving various parameters in real-time. With the development of big data and artificial intelligence technologies, intelligent management of environmental data has become possible. To enhance the level of intelligence in environmental monitoring, this paper studies the performance of environmental sensor data operations in data warehouses such as Hive, ClickHouse, and Doris, and constructs an environmental sensor data analysis system based on a real-time data warehouse. The system employs Flink for real-time collection of environmental data, ClickHouse for data storage, Spark for data analysis, and front-end and back-end technologies for data visualization. The system achieves automatic collection, processing, and analysis of environmental data, thereby improving the efficiency and accuracy of environmental monitoring.
KEYWORDS: Data analysis, Data storage, Data acquisition, Artificial intelligence, Databases, Safety, Data modeling, Data visualization, Data processing, Visualization
Ship manning is the focus of maritime supervision. Insufficient manning will seriously affect the safety of water navigation. To better monitor the ship's manning situation, a maritime regulatory department developed a ship manning management system to realize self-service verification, self-service appointment and dismissal of ship manning and other functions. System operation collects massive amounts of ship manning data. To full mine the value of data, a manning data analysis platform is implemented. It implements the acquisition of ship manning data based on Canna and Kafka, builds a data warehouse through Hive, realizes automatic scheduling of tasks through DolphinScheduler, and realizes data visualization through Vue + Echarts. The analysis of ship manning data will help the maritime regulatory authorities real-time ship manning, analyze ship navigation conditions, and improve water traffic management.
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