Ice region profile temperature-depth simultaneous monitoring Internet-of-Things system

Abstract

The invention discloses an ice region profile temperature-depth simultaneous monitoring Internet-of-Things system. A temperature-depth integrated sensor is connected to an input end of a data acquisition module, an output end of the data acquisition module is connected to an on-site collection host, the on-site collection host is connected to a DTU module, the DTU module is connected to a server, the data acquisition module transmits temperature sensor detection data acquired by channels to the on-site collection host, the on-site collection host displays and stores data, the server receives and stores temperature-depth data transmitted by the DTU module through setting IP and carries out web publishing. The system can adjust the number of the temperature-depth integrated sensors according to actual demands, has strong applicability, realizes automatic measurement, storage and network transmission of temperature and depth data in a large range, realizes remote monitoring through automatic sending of monitoring data in the network coverage area, has a high automation degree and good man-machine interface friendliness, realizes ice region profile temperature-depth monitoring based on Internet of Things, realizes unmanned monitoring and has the characteristics of simple structure, low cost and strong stability.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to a water temperature and water depth monitoring system. Background technique [0002] Due to factors such as high specific heat capacity, illumination changes, and sea ice coverage, there is a large difference in seawater temperature, especially in ice areas in winter, and it is difficult to predict seawater temperature changes and icing conditions based on local air temperature. For industries such as marine transportation and offshore oil resource exploitation, the freezing of seawater will directly affect their normal production activities, and the freezing of seawater is directly related to the change of seawater temperature. Therefore, if the temperature changes of different sections of seawater can be monitored, it can be Predict the freezing of seawater; for some high-latitude reservoirs and rivers, synchronous monitoring of temperature and depth can simulate...

AI Technical Summary

Problems solved by technology

[0003] At present, satellites are mostly used in China to measure the surface sea temperature of the whole sea area. There is a lack of water temperature data of sea water profiles at different depths, which cannot provide effective support for the study of sea water stratification.

And for remote semi-enclosed waters such as marine farms, there is often a big difference between the water temperature measured by the satellite cloud image and the water temperature in the farm. Therefore, many water temperature sensors in the farm monitor the water temperature, but the monitoring area of ​​such sensors is small. It is impossible to realize long-term and large-scale automatic monitoring, and it is impossible to call and query relevant data remotely, and the real-time performance is poor, which is not conducive to the farm to take real-time countermeasures against water temperature changes

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