Optimized layout of the soil moisture sensor in tea plantations based on improved dijkstra algorithm

Based on the clustering center of data, this paper optimizes the data transmission path, and proposes an improved Dijkstra algorithm, which is applied to the path optimization of soil moisture sensors in tea plantations. Firstly, the date of soil moisture in tea plantation is collected under the condition of full coverage of the sensor network. Then, the AP clustering algorithm is used to cluster collected data to obtain the cluster center. Secondly, the dissimilarity values of the soil moisture data and the weighted combination of distance between the sensor nodes are used to identify the edge weights and calculate the adjacency matrix of the Dijkstra algorithm. Finally, with the clustering center as the starting point and the convergence point of wireless sensor network as the end point, Dijkstra algorithm is used to search the path. In order to verify the superiority of the proposed algorithm, the algorithm is compared with the ant colony optimization algorithm. In this paper, the data dissimilarity on the path is 25.0652, the total cost of the path is 0.3613, and the difference between the average soil moisture of the tea plantation is 0.1872 and the number of sensors required is 6, The ant colony algorithm obtained the data dissimilarity on the path of 20.4538, the total cost of the path is 0.5483, and the difference between the average soil moisture of the tea plantation is 0.7321 and the number of sensors required is 9. The test results show that the date of path obtained by this method has the largest dissimilarity and the shortest path, and the data collected by this method is representative, which can accurately reflect the distribution of soil moisture in tea plantations. At the same time, the number of sensors is reduced from 25 to 6, reducing the cost of the system.