Check patentability & draft patents in minutes with Patsnap Eureka AI!

Artificial intelligence insect pest situation prediction system and prediction method

A predictive system and artificial intelligence technology, applied to the device for capturing or killing insects, applications, animal husbandry, etc., can solve the problems of low equipment penetration rate, high system cost, and few farmers, so as to improve the level of prevention and control and reduce development costs. low, promising effect

Active Publication Date: 2021-08-20
米恩基(浙江)传感科技有限公司
View PDF21 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the use of ordinary image recognition technology, it is impossible to identify the types and quantities of bugs in large numbers
[0005] 2. The system usually needs to transmit local camera images, temperature and humidity, air pressure and other information back to the cloud platform. Due to the limitation of network traffic, the data is usually sent back at a long interval, and it is impossible to check the status of each insect detection and reporting light in time. real-time situation
[0006] 3. All insect light devices have no interconnection function, and a single device usually only serves a specific farmer, and there is no sharing of information between farmers
The system does not have a decision-making and suggestion function, and it cannot judge the regional or national pest situation based on the pest situation of equipment in various places, so as to achieve unified decision-making
[0007] 4. The penetration rate of equipment is low, and there are still few farmers using equipment
[0008] 5. Such a system is usually expensive, and a single device is as high as tens of thousands of yuan, which is unaffordable for ordinary farmers

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Artificial intelligence insect pest situation prediction system and prediction method

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment 1

[0068] Specific embodiment 1, in terms of insect situation prediction, a BP neural network with 7 nodes in the input layer, 1 node in the output layer, and 15 nodes in the middle hidden layer can be constructed. Replace P1 to P7 of the input layer with the following values ​​for their aspects:

[0069] P1: the number of detected pests;

[0070] P2: the time when the pest was detected;

[0071] P3: the spatial longitude of the pest location;

[0072] P4: spatial latitude of pest location;

[0073] P5: temperature at the location of the pest;

[0074] P6: Humidity of pest location;

[0075] P7: Atmospheric pressure where the pest is located;

[0076] while the output O 1 Then it can be replaced by the predicted number of the pest on the nth day, the activation function of the hidden layer in this model adopts the Relu function, and the activation function of the output layer adopts a linear function.

specific Embodiment 2

[0077] Specific embodiment 2 is used to predict the number trend of various pests on a certain day in the future. Assuming that there are M types of pests to be predicted, a BP neural network with an input layer of M+6 nodes, an output layer of M nodes, and an intermediate hidden layer of M+15 nodes can be constructed. Put the input layer P1 to P M Replaced by the number of input Mth pests, P M+1 to P M+6 Replaced with the following values ​​for its aspects:

[0078] P M+1 The time when the pest was detected this time,

[0079] P M+2 The spatial longitude of the detection location,

[0080] P M+3 The spatial latitude of the detection location,

[0081] P M+4 The temperature of the testing location,

[0082] P M+5 The humidity of the testing location,

[0083] P M+6 Atmospheric pressure at the location where the test was performed.

[0084] while the output O 1 to O M Then it can be replaced by the predicted number of the pest on the nth day. In this model, the...

specific Embodiment 3

[0085] Specific embodiment 3, for predicting any day in the coming year, the quantity development trend of multiple pests, four kinds of models trained (n=1, n=7, n=30 and n=365), merge into one model, And it can predict the trend of the number of pests in any one day. Assuming that there are M types of pests that need to be predicted, a BP neural network with an input layer of M+7 nodes, an output layer of M nodes, and an intermediate hidden layer of M+50 nodes can be constructed. Replace P1 to PM of the input layer with the number of input Mth pests, and replace PM+1 to PM+7 with the following values:

[0086] PM+1 the time when the pest was detected this time,

[0087] PM+2 the spatial longitude of the detection location,

[0088] PM+3 The spatial latitude of the detection location,

[0089] PM+4 The temperature of the location where the test was conducted,

[0090] PM+5 The humidity of the testing location,

[0091] PM+6 is the atmospheric pressure of the location whe...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an artificial intelligence insect pest situation prediction system and a prediction method. The artificial intelligence insect pest situation prediction system and the prediction method disclosed by the invention are particularly important for monitoring and early warning work of insect pests, so that the insect pest situation monitoring system provides a set of comprehensive management and analysis service based on big data for insect pest situation prediction work through networking, the occurrence rule of the insect pests can be better and deeply known, the pest control level is further improved, and the system serves green agriculture and organic agriculture and has a wide prospect; and the development cost of the system development is relatively low, a user can log in through a user client to check the equipment condition, operation can be conveniently carried out, and the cost is relatively low.

Description

technical field [0001] The invention relates to the technical field of intelligent insect infestation prediction, in particular to an artificial intelligence infestation infestation prediction system and a prediction method. Background technique [0002] The impact of pests and diseases on crops is even greater. In addition to the spraying and killing measures after the outbreak of insect disasters, the work of insect situation monitoring and reporting is the top priority in plant protection work. Whether the information of insect situation monitoring and reporting is timely, accurate and effective is the key to ensuring the effect of insect population sequestering food. We guide that once the right time is missed for pest control, crop losses will be great. The insect monitoring system integrates various information technologies, which can not only complete the real-time monitoring and forecasting of crop diseases and insect pests, but also transmit and analyze and process...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): A01M1/02
CPCA01M1/026Y02A90/10
Inventor 戴征武章晓敏章伟聪王福方韦福安
Owner 米恩基(浙江)传感科技有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com