Planning and construction of the national large鄄scale coal鄄fired power bases are one important department of Twelfth Five鄄Year Plan., and it is also an important measure of development strategy of China忆s future energy. With the development of social economy, people pay more attention on the assessment of ecological effects on human activities. So the assessment of ecological effects on the national large鄄scale coal鄄fired power base is an important way ensuring the regional sustainable development of the national large鄄scale coal鄄fired power base. The national large鄄scale coal鄄fired power bases are always distributed in arid and semi鄄arid regions in the north of China. The regional ecological environment direct impact on ecological safety of Beijing, Tianjin, Northeast urban agglomeration, and two of major grain production bases, even the
As the construction of coal鄄fired power bases in China accelerates, the amount of ecological damage and environmental pollution caused by this and their subsequent operation and servicing becomes more serious. It should be a priority to establish the ecological and environmental risks posed by coal鄄fired power bases, to assess their impact on ecosystems and human health, and to develop reasonable strategies for the protection, governance, and restoration of the environment. A sustained and methodical program of ecological and environmental monitoring is the basis for solving these problems. However, currently, the monitoring of technical systems still presents several operational shortcomings, such as low levels of automation, high operating costs, and poor spatial and temporal coverage. At the same time, significant developments in the Internet of Things are improving both the production efficiency of data collection and the way in which data are captured. Accordingly, we believe that the Internet of Things could be one of the more effective ways of solving the problems inherent in the current monitoring of technical systems, in respect of the sensing layer, transport layer, supporting layer, application layer, and client layer. For the study area in the current work, we used Xilinguolemeng in Inner
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