The Pest Monitoring System Based On The Internet Of Things

Forest pests and diseases occur every year in China,which has caused huge losses to the development of forestry economy.Therefore,it is extremely urgent to adopt effective control measures.For effective prevention and control,monitoring of forest pests and diseases must be in place.However,traditional means can no longer effectively protect forests and need to study more effective monitoring methods to deal with them.This paper is mainly to break through the traditional monitoring methods of forest pests and diseases,and to combine deep learning teconology to achieve the pest monitoring system based on the Internet of Things,it will solve the problem of traditional methods of spending a lot of human and material resources,and improve the efficiency.The system mainly implements functions such as image collection,image recognition,and map location monitoring with dendroctonus valens.The image collection and recognition of dendroctonus valens can help to remotely obtain the insect situation of the traps at each collection point,while the map location monitoring enables the staff to monitor the insects at various coordinate points in the forest area and grasp the dynamics of the insects in time.The Internet of Things system monitors the insects of each coordinate trap in the forest area through remote operation,and can quickly and timely know the changes of the insects and make quick response measures,reducing the consumption of manpower and material resources.The scientific decision-making and scientific management of workers are of great significance.