Intelligent termite monitoring system driven by internet of things and used for water conservancy project

Abstract

The invention discloses an internet-of-things-driven intelligent termite monitoring system for a water conservancy project, and relates to the technical field of water conservancy monitoring. Comprising the steps that termite activity sound wave signals, soil vibration data and environmental parameters are collected in real time, and after preprocessing such as sliding window filtering and cubic spline interpolation, a temperature and humidity-soil disturbance-wood damage three-dimensional correlation entropy matrix is constructed; a fuzzy Bayesian neural network model based on random forest feature weight distribution can output low / medium / high risk probability distribution, and regional risk quantification is performed in combination with water level fluctuation, a soil permeability coefficient and a facility importance coefficient. And fusing the facility abnormal use coefficient and the diffusion enhanced structure risk coefficient, generating a priority index through a dynamic early warning adjustment model, and triggering a hierarchical response strategy. A pesticide spraying path is planned through a genetic algorithm, and 72-hour diffusion thermodynamic prediction and precise prevention and control are achieved. According to the system, the termite monitoring recognition rate is increased, the energy consumption is reduced, and the intelligent management and protection level of hydraulic engineering facilities is improved.

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