A space-air-ground multi-source data fusion method and system for smart villages

By employing a strategy of spatiotemporal reconstruction and fusion of multi-source data from air, space, and ground, the heterogeneity and spatiotemporal differences of multi-source data in smart villages have been resolved. This has enabled efficient and robust environmental perception and disaster risk response, and improved the real-time decision-making capabilities of the agricultural management system.

CN121981847BActive Publication Date: 2026-07-14NINGBO UNIVERSITY OF TECHNOLOGY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NINGBO UNIVERSITY OF TECHNOLOGY
Filing Date
2026-04-01
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing multi-source data fusion technologies struggle to achieve real-time and efficient fusion of heterogeneous data with significant differences in spatiotemporal resolution and varying data quality in smart village scenarios. Furthermore, they lack robustness in capturing sudden environmental signals, leading to delayed disaster risk response.

Method used

By reconstructing and resampling multi-source monitoring data from space, air, and ground in a spatiotemporal grid and time, a standardized dataset is obtained. Then, by using algebraic reliability weighting and macroscopic curvature compensation data fusion strategies, and combining risk potential energy to obtain execution action instructions, the synergistic fusion of microscopic information sources and macroscopic trends is achieved.

Benefits of technology

While ensuring the accuracy of data fusion, it ensures that the executed action commands meet the current physiological needs of crops and adapt to environmental changes, thereby enhancing the defense capabilities and adaptive adjustment level of the smart rural agricultural management system.

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Abstract

The application belongs to the field of agricultural informatization and multi-source data processing technology, and particularly relates to a space-air-ground multi-source data fusion method and system for smart villages, which comprises the following steps: acquiring environment data through satellite remote sensing, unmanned aerial vehicles and ground Internet of Things and performing space-time grid reconstruction to establish a standardized data set; calculating algebraic confidence by using the current observation value of each micro source and the local spatial neighborhood mean and time difference value; subsequently, performing weighted calculation on the micro observation value, introducing the second-order difference value of macro data as a compensation term to obtain a collaborative fusion value; combining the fusion value at the previous moment and the crop physiological optimal target value to calculate risk potential and generate a nonlinearly coupled execution action instruction. The application suppresses noise and retains disaster mutation signals through an algebraic attenuation mechanism, solves the precision and robustness balance problem in heterogeneous data fusion, and realizes instant and accurate decision-making of risks in a smart village environment.
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Citation Information

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