Agriculture and forestry diseases and pests are a major factor that endangers the safety of agriculture and forestry. Therefore, in response to pests and diseases, the agricultural and forestry departments have been actively developing agricultural and forestry Internet of things in recent years. These new technologies have been used to improve the prevention and control of pests and diseases in agriculture and forestry. The application of IoT technology in modern agriculture has a significant effect on improving the production management level of traditional agriculture, especially in the remote monitoring of diseases, and has played an important technological advantage, not only improving the response speed and the prevention and control ability of the plant protection department against pests and diseases, It also greatly eases the work pressure of the surveying personnel.
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The IoT network uses the IoT platform in conjunction with the agricultural and forestry microclimate information collection system, the pest information collection system, and the spore cultivation statistical analysis system to monitor the growth of plants by setting up various sensory terminals and assembling cameras in farm fields. The number and types of pests and diseases have enabled the plant protection personnel to use the mobile phone or computer to remotely monitor the farm crops without going deep into the field. This will increase the level of field management and at the same time make agriculture more accurate and efficient.
The application of the agriculture and forestry internet of things in the remote monitoring of diseases is not only the convenience provided by remote monitoring, but more importantly the sharing of information. It is equivalent to putting farms on the field with clairvoyant eyes, ears, and not only able to understand the fields in time. The information can also transmit and store these monitoring data, and these data can also be shared through the network, which can quickly and accurately forecast the occurrence and development of pests and diseases in monitoring areas, provide guidance for expert command and control and decision-making, and greatly promote the prediction and prediction of agricultural diseases and insect pests. Early warning work is standardized, networked, modernized, automated, and visualized.
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