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CN-121995021-A - Based on intelligent unmanned aerial vehicle crowd coastal zone pollution collaborative monitoring and traceability platform

CN121995021ACN 121995021 ACN121995021 ACN 121995021ACN-121995021-A

Abstract

The invention discloses an intelligent unmanned aerial vehicle group-based coastal zone pollution collaborative monitoring and tracing platform which is characterized by comprising a heterogeneous unmanned aerial vehicle group module, a multi-mode environment sensing module, a pollution tracing analysis module, a self-organizing communication network module and an edge-cloud collaborative computing framework, wherein the heterogeneous unmanned aerial vehicle group module comprises a monitoring unmanned aerial vehicle, a sampling unmanned aerial vehicle and a communication relay unmanned aerial vehicle and has dynamic task allocation capability, the multi-mode environment sensing module is provided with a multi-spectral sensor, an infrared thermal imager and a water quality sampling device, the collaborative decision and control module is used for realizing dynamic path planning by adopting an improved ant colony algorithm, the pollution tracing analysis module is used for positioning a pollution source based on a space-time diffusion model and a Bayesian network, and the self-organizing communication network module is used for supporting 5G/satellite dual-mode communication and dynamic topology reconstruction.

Inventors

  • YU QIU

Assignees

  • 江苏海洋大学
  • 江苏旷瑞海洋科技有限公司

Dates

Publication Date
20260508
Application Date
20260121

Claims (10)

  1. 1. The coastal zone pollution collaborative monitoring and tracing platform based on the intelligent unmanned aerial vehicle group is characterized by comprising a heterogeneous unmanned aerial vehicle group module, wherein the heterogeneous unmanned aerial vehicle group module comprises a monitoring unmanned aerial vehicle, a sampling unmanned aerial vehicle and a communication relay unmanned aerial vehicle and has dynamic task allocation capability; The multi-mode environment sensing module is provided with a multi-spectrum sensor, an infrared thermal imager and a water quality sampling device; The collaborative decision-making and control module adopts an improved ant colony algorithm to realize dynamic path planning; The pollution tracing analysis module is used for positioning a pollution source based on the space-time diffusion model and the Bayesian network; The self-organizing communication network module supports 5G/satellite dual-mode communication and dynamic topology reconstruction; And the edge-cloud cooperative computing architecture realizes the fusion analysis of data real-time processing and deep learning.
  2. 2. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform according to claim 1, wherein the dynamic task allocation capability comprises a distributed negotiation mechanism based on an improved contract network protocol, wherein a multi-objective optimization model of unmanned aerial vehicle endurance, sensor precision and environmental disturbance is integrated, and a priority strategy is preempted for emergency tasks of sudden pollution events.
  3. 3. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform based on the invention of claim 1 is characterized in that the multi-mode environment sensing module adopts a space-time registration technology of hyperspectral imaging and laser radar point cloud, and meanwhile, an abnormal pollution area autonomous recognition algorithm based on deep learning can dynamically adjust sampling density according to a pollutant concentration gradient by utilizing a self-adaptive sampling strategy.
  4. 4. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform according to claim 1 is characterized in that the improved ant colony algorithm introduces a path cost function of ocean flow field correction factors, and a dynamic pheromone updating mechanism based on wind speed prediction is used for a three-dimensional obstacle avoidance constraint model of coastal zone topography.
  5. 5. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform based on the invention of claim 1 is characterized in that the pollution tracing analysis module comprises a hybrid model of coupling fluid dynamics and pollutant diffusion, and an online correction mechanism of unmanned aerial vehicle real-time monitoring data is introduced in a reverse tracing process through a transregional pollution characteristic matching method based on transfer learning.
  6. 6. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform according to claim 1, wherein the self-organizing communication network module is provided with a dynamic spectrum allocation strategy based on Q learning, combines with a multi-path fading resistance coding technology of an offshore environment, and improves topology self-healing capability of unmanned aerial vehicle nodes in fault.
  7. 7. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform based on claim 1 is characterized in that the edge-cloud collaborative computing architecture is based on a federal learning distributed data processing framework, and an edge lightweight anomaly detection model compression technology is enhanced by combining a real-time synchronization mechanism of a cloud digital twin model.
  8. 8. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform based on the invention of claim 1 is characterized by further comprising a multi-source data fusion module, wherein the multi-source data fusion module comprises satellite remote sensing data, buoy monitoring data and a historical pollution database, and the characteristic weighting fusion algorithm based on an attention mechanism is used for selecting different fusion strategies of different pollution types.
  9. 9. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform according to claim 1, wherein the platform deployment comprises a blockchain-based monitoring data certification system, a visual decision board supporting a multi-department collaborative access control mechanism and a pollution diffusion prediction result.
  10. 10. The intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform according to claim 1, wherein the unmanned aerial vehicle group module comprises an autonomous charging scheduling system based on reinforcement learning, a modularized load interface resistant to salt spray corrosion and a fault tolerant flight control system of complex sea conditions.

Description

Based on intelligent unmanned aerial vehicle crowd coastal zone pollution collaborative monitoring and traceability platform Technical Field The invention relates to the technical field of environmental monitoring data processing, in particular to a coastal zone pollution collaborative monitoring and tracing platform based on an intelligent unmanned aerial vehicle group. Background The coastline of China is long, and the ocean resources are rich. The development and utilization of ocean resources are all the key contents of the social and economic development of China. In recent years, along with the rapid development of economy in China, environmental problems are also gradually highlighted. Environmental monitoring technology plays a vital role in environmental protection. The environmental monitoring technology in China has a plurality of problems such as insufficient monitoring means, low reliability of monitoring data and the like. Measures are urgently needed to strengthen the environment monitoring technology, provide more reliable data support for environmental protection and promote the development of environmental treatment work. In the prior art, the unmanned aerial vehicle carrying the optical sensor is used for carrying out periodical cruising, so that the problems of large monitoring blind area and low response speed exist, the water quality sensor array is arranged to realize continuous monitoring, but the continuous monitoring is limited by the distribution density and the ocean current influence, the coverage range is enlarged by adopting a plurality of unmanned aerial vehicles of the same type, and the repeated coverage and communication interruption easily occur under complex sea conditions due to the lack of a task cooperative mechanism. Therefore, it is necessary to provide a platform for collaborative monitoring and tracing of pollution of coastal zones based on an intelligent unmanned aerial vehicle group to solve the above-mentioned technical problems. Disclosure of Invention This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application. The present invention has been made in view of the above-described problems occurring in the prior art. The invention provides a technical scheme based on an intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform, which is characterized by comprising a heterogeneous unmanned aerial vehicle group module, a monitoring unmanned aerial vehicle, a sampling unmanned aerial vehicle and a communication relay unmanned aerial vehicle, wherein the heterogeneous unmanned aerial vehicle group module comprises a monitoring unmanned aerial vehicle, a sampling unmanned aerial vehicle and a communication relay unmanned aerial vehicle and has dynamic task allocation capability; The multi-mode environment sensing module is provided with a multi-spectrum sensor, an infrared thermal imager and a water quality sampling device; The collaborative decision-making and control module adopts an improved ant colony algorithm to realize dynamic path planning; The pollution tracing analysis module is used for positioning a pollution source based on the space-time diffusion model and the Bayesian network; The self-organizing communication network module supports 5G/satellite dual-mode communication and dynamic topology reconstruction; And the edge-cloud cooperative computing architecture realizes the fusion analysis of data real-time processing and deep learning. The dynamic task allocation capability specifically comprises a distributed negotiation mechanism based on an improved contract network protocol, a multi-objective optimization model integrating unmanned aerial vehicle endurance, sensor precision and environmental disturbance, and an emergency task preemption priority strategy for sudden pollution events. The multi-mode environment sensing module adopts a space-time registration technology of hyperspectral imaging and laser radar point cloud, and simultaneously utilizes a self-adaptive sampling strategy to dynamically adjust the sampling density by utilizing an abnormal pollution area autonomous identification algorithm based on deep learning. As a preferable scheme of the intelligent unmanned aerial vehicle group coastal zone pollution collaborative monitoring and tracing platform, the improved ant colony algorithm introduces a path cost function of ocean flow field correction factors, and a dynamic pheromone updating mechanism based on wind speed prediction is used for a three-dimensional obstacle avoidance constraint model of coastal zone topography. The pollution tracing analysis module comprises a hybrid model for coupling fluid dynamic