Smart scenic spot recommendation method based on AIoT and computer vision
A technology of computer vision and scenic spots, applied in calculation, structured data retrieval, prediction, etc., can solve the problem of unsatisfactory scenic spots for tourists, and achieve the effect of improving comfort and accurate scoring results
Inactive Publication Date: 2021-01-08
河南颂达信息技术有限公司
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Problems solved by technology
[0002] The existing scenic spot recommendation method usually obtains tourist location information through terminal equipment, and only recommends scenic spots to tourists based on the distance of the scenic spot, while ignoring other factors that have a greater impact on the recommendation of scenic spots. The scenic spots recommended by this recommendation method Often unsatisfactory
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[0024] In order to realize the present invention, it is necessary to deploy a certain number of sensors in the smart scenic spot, including visual sensors, temperature sensors, and air quality sensors. It should be noted that the sensors should have communication functions and can transmit the collected information to the server. Specifically The implementer of the communication method can choose according to the actual situation.
[0025] The visual sensor is an RGB camera, which is deployed at the entrance of each scenic spot to collect images of tourists at the entrance of each scenic spot when the scenic spot is open. At least one RGB camera should be deployed in each scenic spot. The deployment location should have a certain height to capture the entire entrance area.
[0026] The image of tourists at the entrance collected by the RGB camera is sent to the density sensing network to obtain the density level of tourists; among them, the density sensing network includes two...
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The invention provides a smart scenic spot recommendation method based on AIoT and computer vision, and the method comprises the steps of processing a tourist image to obtain a tourist density level,and inputting a historical tourist density level into a time convolution network to obtain a predicted tourist density level; obtaining the scenic spot popularity of the current week according to theaverage tourist density level of the previous week; obtaining a journey experience grade according to the temperature data and the air quality data of the route between the tourist and each scenic spot, and inputting the historical journey experience grade into a time convolution network to obtain a predicted journey experience grade; obtaining the moving duration according to the distance information of the route between the tourist and each scenic spot and the pre-obtained average speed; and constructing a scenic spot recommendation scoring model according to the predicted tourist density level, the predicted journey experience level, the scenic spot popularity and the movement duration to obtain a score of each scenic spot. Scenic spot recommendation is carried out in combination with the journey experience level, and the comfort of tourists in the playing process can be improved.
Description
technical field [0001] The invention belongs to the field of artificial intelligence and scenic spot recommendation, and in particular relates to a method for recommending scenic spots in smart scenic spots based on AIoT and computer vision. Background technique [0002] The existing scenic spot recommendation method usually obtains tourist location information through terminal equipment, and only recommends scenic spots to tourists based on the distance of the scenic spot, while ignoring other factors that have a greater impact on the recommendation of scenic spots. The scenic spots recommended by this recommendation method Tourists are often not satisfied. Contents of the invention [0003] In order to solve the problems existing in the prior art, the present invention proposes a method for recommending scenic spots in a smart scenic spot based on AIoT and computer vision. The method includes: [0004] Step 1: Deploy visual sensors at the entrance area of each scenic ...
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IPC IPC(8): G06F16/9537G06F16/29G06Q10/04G06Q50/14G01D21/02
CPCG01D21/02G06Q10/04G06Q50/14G06F16/29G06F16/9537
Inventor 王晓春李灵芝
Owner 河南颂达信息技术有限公司