CN-122015962-A - Intelligent orchard multisource information fusion monitoring system and method

CN122015962ACN 122015962 ACN122015962 ACN 122015962ACN-122015962-A

Abstract

The invention relates to the technical field of intelligent agriculture and industrial data processing, and particularly discloses an intelligent orchard multisource information fusion monitoring system and method. According to the invention, heterogeneous sensing terminals are deployed to collect multidimensional data of meteorological conditions, soil, plant diseases and insect pests and growth states of fruit trees, and the multidimensional data are subjected to standardized analysis and space-time association fusion, and flow-type and distributed computing engines are called to conduct real-time cleaning and historical analysis, so that the problems of inconsistent data standards, insufficient fusion, weak processing capacity and data island are solved, and the collaborative utilization rate and intelligent management level of multi-source information of an orchard are improved.

Inventors

CHANG YUANSHENG
ZHENG WENYAN
WANG SEN
WANG YONGXU
HE PING
HE XIAOWEN
WANG HAIBO
LI LINGUANG

Assignees

山东省果树研究所

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. An intelligent orchard multisource information fusion monitoring system, which is characterized by comprising: The multi-source data acquisition module is used for acquiring multi-dimensional monitoring data through a plurality of heterogeneous sensing terminals deployed on an orchard site, wherein the multi-dimensional monitoring data comprise meteorological data, soil data, plant disease and insect pest image data and fruit tree growth state data; The data standardization module is used for analyzing the multi-dimensional monitoring data to obtain an original data field containing a monitoring value and a data tag, executing format conversion and semantic normalization processing according to a preset unified data protocol based on the original data field, and outputting unified format data; The multi-source information fusion module is used for aligning the unified format data by adopting a data association method based on the time stamp and the space position, and executing feature level fusion and decision level fusion to generate multi-source fusion data; The industrial information and data processing module is used for calling the flow type computing engine to carry out real-time cleaning and anomaly detection on the multi-source fusion data, calling the distributed computing framework to carry out batch processing analysis on the historical multi-source fusion data, and outputting an analysis result comprising real-time state and trend prediction; And the decision support module is used for calling a preset decision rule base according to the analysis result to generate an orchard management decision instruction aiming at precise irrigation, variable fertilization and pest and disease damage early warning.
2. The intelligent orchard multi-source information fusion monitoring system according to claim 1, wherein the multi-source data acquisition module comprises a wireless sensor network, and the wireless sensor network is composed of the heterogeneous sensor terminal and a gateway node and is used for uploading the multi-dimensional monitoring data to the data standardization module.
3. The intelligent orchard multisource information fusion monitoring system of claim 2, wherein the data normalization module is further configured to verify the original data field and append a data quality tag to the verified original data field, and the format conversion and semantic normalization processing is performed based on the data quality tag.
4. The intelligent orchard multisource information fusion monitoring system according to claim 3, wherein the data association method based on time stamps and space positions in the multisource information fusion module is specifically used for performing space-time matching on the unified format data according to data acquisition time and preset orchard geogrid codes.
5. The intelligent orchard multisource information fusion monitoring system of claim 4, wherein the industrial information and data processing module performs real-time cleaning and anomaly detection on the multisource fusion data, including statistical outlier detection based on sliding time windows.
6. The intelligent orchard multisource information fusion monitoring system of claim 1, wherein the decision support module further comprises a decision optimization unit, wherein the decision optimization unit is used for dynamically updating the decision rule base based on feedback decision execution effect data.
7. The intelligent orchard multisource information fusion monitoring system of claim 1, further comprising a visual interaction module, wherein the visual interaction module is used for receiving and displaying the analysis results and the orchard management decision instruction and receiving operation feedback of a user.
8. The intelligent orchard multisource information fusion monitoring system of claim 7, wherein the visual interaction module is displayed in a manner including a monitoring data space distribution diagram, a historical data trend curve and a decision instruction execution status panel based on an electronic map.
9. The intelligent orchard multisource information fusion monitoring system according to claim 4, wherein the multisource information fusion module calculates fusion weights by adopting an adaptive fusion algorithm based on dynamic credibility and space-time correlation when feature level fusion is performed; the adaptive fusion algorithm calculates the fusion weight w_i (x, t) of the ith data source for a particular monitoring parameter x at time t by the following formula: Wherein, the Representing the fusion weight of the ith data source for the monitoring parameter x at time t; the historical data reliability evaluation value of the ith data source at the time t is represented, and the historical data reliability evaluation value is obtained through data backtracking verification; an intrinsic confidence coefficient representing the ith data source type; the value range is 0 to 1 for the dynamic weight adjusting factor; representing the difference between the current time t and the latest data timestamp of the ith data source; Is a time decay coefficient; representing the average data difference degree of the ith data source and other data sources in the fusion in time and space; Punishment coefficients for the degree of difference; Representing the total number of data sources participating in the fusion.
10. An intelligent orchard multisource information fusion monitoring method is characterized by comprising the following steps: Collecting multi-dimensional monitoring data through a plurality of heterogeneous sensing terminals deployed on an orchard site, wherein the multi-dimensional monitoring data comprise meteorological data, soil data, plant disease and insect pest image data and fruit tree growth state data; Analyzing the multi-dimensional monitoring data to obtain an original data field containing a monitoring value and a data tag, executing format conversion and semantic normalization processing according to a preset unified data protocol based on the original data field, and outputting unified format data; Aligning the unified format data by adopting a data association method based on time stamps and space positions, and executing feature level fusion and decision level fusion to generate multi-source fusion data; Calling a stream computing engine to carry out real-time cleaning and anomaly detection on the multi-source fusion data, calling a distributed computing framework to carry out batch processing analysis on the historical multi-source fusion data, and outputting an analysis result comprising real-time state and trend prediction; And according to the analysis result, calling a preset decision rule base to generate an orchard management decision instruction aiming at precise irrigation, variable fertilization and pest and disease damage early warning.

Description

Intelligent orchard multisource information fusion monitoring system and method Technical Field The invention relates to the technical field of intelligent agriculture and industrial data processing, in particular to an intelligent orchard multisource information fusion monitoring system and method. Background Along with the rapid development of modern agriculture to the intelligent direction, the orchard fine management provides higher requirements for multidimensional information monitoring. The current orchard monitoring mainly relies on manual inspection or single-function monitoring equipment to respectively acquire information such as weather, soil, plant diseases and insect pests, fruit tree growth states and the like, and data standards of all acquisition terminals are not uniform and lack of effective fusion mechanisms, so that monitoring data from different sources are difficult to cooperatively use, and a data island is formed. Meanwhile, the existing system has weak processing capability on the aspects of industrial information and data processing, is limited in calculation resources in the face of massive heterogeneous data generated in a large-scale orchard, lacks an efficient real-time analysis architecture, has insufficient data value mining depth, and cannot provide timely and reliable technical support for accurate irrigation, fertilization decision and pest and disease damage early warning. The dual limitation of the information fragmentation and processing capability severely restricts the intelligent level and the practical effect of the orchard monitoring system, and technical breakthrough is realized by multi-source information fusion and improvement of the processing capability of industrial data. Disclosure of Invention In order to solve the technical problems, the invention provides an intelligent orchard multisource information fusion monitoring system and method. In a first aspect, the invention provides an intelligent orchard multisource information fusion monitoring system, which has the following technical scheme: The multi-source data acquisition module is used for acquiring multi-dimensional monitoring data through a plurality of heterogeneous sensing terminals deployed on an orchard site, wherein the multi-dimensional monitoring data comprise meteorological data, soil data, plant disease and insect pest image data and fruit tree growth state data; The data standardization module is used for analyzing the multi-dimensional monitoring data to obtain an original data field containing a monitoring value and a data tag, executing format conversion and semantic normalization processing according to a preset unified data protocol based on the original data field, and outputting unified format data; The multi-source information fusion module is used for aligning the unified format data by adopting a data association method based on the time stamp and the space position, and executing feature level fusion and decision level fusion to generate multi-source fusion data; The industrial information and data processing module is used for calling the flow type computing engine to carry out real-time cleaning and anomaly detection on the multi-source fusion data, calling the distributed computing framework to carry out batch processing analysis on the historical multi-source fusion data, and outputting an analysis result comprising real-time state and trend prediction; And the decision support module is used for calling a preset decision rule base according to the analysis result to generate an orchard management decision instruction aiming at precise irrigation, variable fertilization and pest and disease damage early warning. Further, the multi-source data acquisition module comprises a wireless sensor network, wherein the wireless sensor network consists of the heterogeneous sensor terminal and a gateway node and is used for uploading the multi-dimensional monitoring data to the data standardization module. Further, the data normalization module is further configured to verify the original data field, attach a data quality tag to the verified original data field, and perform the format conversion and the semantic normalization processing based on the data quality tag. Furthermore, the data association method based on the time stamp and the space position in the multi-source information fusion module specifically performs space-time matching on the unified format data according to the data acquisition time and a preset orchard geogrid code. Further, the industrial information and data processing module performs real-time cleaning and anomaly detection on the multi-source fusion data, including statistical outlier detection based on a sliding time window. Further, the decision support module further comprises a decision optimizing unit, and the decision optimizing unit is used for dynamically updating the decision rule base based on the feedback decision execution effect data. Further, th