With the rapid development of science and technology, the use of Internet of Things in the field of forestry is also gradually popularized. At present, the Intelligent Integrated Forestry Information Management Platform based on the Internet of Things can monitor the forestry production dynamics in an all-round and real-time way in the forestry production process, greatly ensuring the accuracy, scientificity and effectiveness of monitoring information, acquiring a large amount of information quickly and accurately, realizing the efficient and comprehensive monitoring of forests, and saving unnecessary manpower and material input. Effective prevention of various natural disasters, so as to improve the economic benefits of forestry resources.

Intelligent Forestry Informatization

When investigating the current situation of forest resources, we can fully use the Internet of Things technology to grasp the dynamic changes of forest resources. The unmanned aerial vehicle (UAV) based on cloud sensing and Internet of Things (IOT) has fast imaging technology, which can ensure that the current forest resources survey activities have a higher timeliness, can greatly improve the efficiency of the survey and ensure the quality of the survey. In the past, when using manual survey method to inventory forestry resources, most of them focus on the area and type of forestry resources, which can not achieve centralized and efficient management of forestry resources. On the one hand, it can use remote sensing digital image technology to scientifically and effectively analyze relevant data information, on the other hand, it can also understand the distribution of vegetation, so as to more accurately investigate and analyze the situation of forestry resources.

UAV

In recent years, the forestry bureau of Hubei Province has made some progress in the construction and protection of forest resources. The scale of forests has gradually expanded, and the types of forest resources have become more perfect and abundant. However, in terms of its ecosystem, it is still in a relatively weak situation. There are many factors affecting the normal growth of trees, and pests and diseases are one of the more serious factors. Using cloud sensing Internet of things multi function cameras can better monitor forestry pests and diseases. Under the action of the visible light camera device, it can monitor effectively the pests and diseases in the monitored areas. After identifying the pests accurately, it can timely and effectively control such pests and diseases of forest trees, and can hang corresponding pesticide sprayers on pine trees.
Forest fires have great destructive effect and strong suddenness, and it is difficult to rescue and prevent, which seriously restricts the normal growth of forests. In the management and management of forestry resources, the monitoring and prevention of forest fire is a very important and necessary work. In forest areas where forest fires often occur, the role of cloud-sensing Internet of Things dual-light camera can be fully played to effectively prevent and accurately predict forest fires, and the situation of forest areas after fires can be effectively analyzed by means of intelligent forestry information integrated management platform.

Forest fire prevention

When investigating woodland resources, cloud-sensing Internet of Things UAV was used to photograph tree crowns, which prompted them to form remote sensing images of tree crowns, so as to effectively estimate individual tree biomass in forest areas. Based on the analysis of remote sensing images, the area of individual tree canopy can be obtained by using object-oriented classification method, and the corresponding model can be established according to the measured DBH. Finally, the biomass information of tree trunk can be obtained by using the empirical equation of trunk area and related biomass. Relevant biomass information obtained by traditional artificial technology has some uncertainties, which can not effectively guarantee its measurement accuracy and efficiency, due to the factors such as high labor intensity, low efficiency, long time to obtain information, high cost, cumbersome operation, small work area and slow progress.