Environment monitoring method for non-public network area based on Internet of Things satellites

Abstract

The invention relates to an environment monitoring method for a non-public network area based on an Internet of Things satellite. The method comprises the following steps: S01, monitoring environment data of an area without public network coverage in real time by a plurality of environment monitoring sensors; s02, the ground satellite internet-of-things terminal preprocesses and stores the environmental data, and when the distance between the internet-of-things satellite and the ground satellite internet-of-things terminal reaches a specified distance, the stored environmental data is sent to the internet-of-things satellite by means of an L wave band; s03, when the Internet of Things satellites move to a public network coverage area, the environmental data are transmitted to a ground gateway station through a C-band downlink; and S04, the ground gateway station transmits the environmental data to a data center through a public network. According to the method, real-time monitoring of an extreme environment can be realized, monitoring of different environments can be realized at the same time, and effectiveness, real-time performance and quality of data transmission are ensured.

Description

technical field [0001] The invention relates to the field of data technology, in particular to an environment monitoring method in a non-public network area based on Internet of Things satellites. Background technique [0002] In recent years, as the impact of climate change and population growth on ecosystem pattern changes has gradually intensified, comprehensive analysis of multi-scale environmental changes to cope with the challenges posed by environmental changes to science has made the research status of extreme environment ecosystems more and more important. In some extreme environments without public network coverage, the monitoring of ecosystems is a key link in exploring and studying the natural and human processes in extreme areas, as well as the temporal and spatial evolution of climate. Extreme environments have the characteristics of no public network coverage or difficult access by humans, which brings huge challenges to the acquisition of ecosystem monitoring...

AI Technical Summary

Problems solved by technology

Extreme environments have the characteristics of no public network coverage or difficult access by humans, which brings huge challenges to the acquisition of ecosystem monitoring and monitoring data in such areas, which in turn leads to hydrothermal processes, biological processes, and climate changes in such areas. Insufficient monitoring of key parameters, therefore, it is difficult to form a continuous monitoring data set in time and space

[0003] At present, the acquisition of ecosystem monitoring data in extreme environments without public network coverage or inaccessible to humans mostly adopts manual collection methods, and it is difficult to achieve real-time transmission of extreme environment monitoring data by relying on manual collection methods

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