Research On The Key Technology Of Acquiring And Identifying Information From The Internet Of Things In Agriculture

As a new application form of the Internet of Things(IOT)in agriculture,the IOT in agriculture is being explored in the aspects of relevant theoretical research and practical practice.Although the IOT in agriculture is always taken as the application of radio frequency induction technology in the field,in order to ensure the efficient,accurate and secure inquiry and location of the relevant information of crops from the internet,the collection and identification of the weak information are the issues to be solved eventually in the physical environment of the IOT in crops.With the in-depth development in the agricultural engineering field,as well as the combination of IOT technology with information collection and identification technology,the relevant parameters are adjusted in time to implement the all-round real-time monitoring for the agricultural engineering,which can provide important impact on the growth of the crops and effectively enhance the increase of agricultural yield and income.In order to establish the frame and model of the information collection and identification in the IOT in crops on the basis of the performance analysis,the concerned key technology,as the research object of this paper,is studied and explored,and the main research work to be conducted are as follows.The self-organization scheme of wireless sensor network(WSN)of the IOT in agriculture is put forward for the network self-organization;a method of planning and treating the in-depth routing is provided for the route optimization and resource competition;the local network restructuring and leapfrog routing plan is presented to resolve the impact of node failure,increase and mobility on the network.In consideration of the characteristics of wavelet analysis in collecting and identifying the information from the IOT in crops,the model of information collection and identification in the IOT in crops is established on the basis of its performance with the formalization analysis of the key factors concerned to verify the effectiveness of the model and prove that it is an efficient theoretical model for the research on collecting and identifying the information from the IOT in crops.For the information collection and identification in the IOT in crops,through the wavelet analysis of the detection mechanism of crops information,a method is offered to pre-treat the image signals of crops,combined with the wavelet transform and Mallat wavelet algorithm,and the new method can be used to detect the detailed signals of Colletotrichum graminicola(Ces.)Wilson and calculate the simulated experimental data from filtering,enhance and denoise the image signals of blight on corn bracts,which provide an new method to enhance the efficient measurement of the information of crops features.As for the identification of crops pathological features,based on the characteristic analysis of the signals from crops pathological image,and optimal wavelet packet basis,a method is put forward to extract the signal features and realize the feature extraction and identification of crops pathological image by matching the images.For the collection and identification of weak information from crops under the physical environment of the IOT in agriculture,the wavelet transform algorithm is presented as a new technology for the information collection and identification of IOT in crops,and the Daubechies wavelet is applied to decompose and reconstruct the weak information from crops,the weak information from crops can be identified clearly in the atmosphere of noises,the signal identification,with good filtering treatment,is taken as a new technology for the development of sensor nodes,which realize the intelligent control of the parameters from sensor nodes for the collection and identification of the massive information from agriculture production bases,and provide an effective method for monitoring the information of crops and accurate management.