WO2020239088A1 - 一种保险理赔处理方法及装置 - Google Patents

一种保险理赔处理方法及装置 Download PDF

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Publication number
WO2020239088A1
WO2020239088A1 PCT/CN2020/093388 CN2020093388W WO2020239088A1 WO 2020239088 A1 WO2020239088 A1 WO 2020239088A1 CN 2020093388 W CN2020093388 W CN 2020093388W WO 2020239088 A1 WO2020239088 A1 WO 2020239088A1
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Prior art keywords
photos
drone
insurance
complete
report
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PCT/CN2020/093388
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English (en)
French (fr)
Inventor
刘坤
吴晓卿
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深圳市聚蜂智能科技有限公司
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Publication of WO2020239088A1 publication Critical patent/WO2020239088A1/zh
Priority to US17/537,369 priority Critical patent/US20220084133A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C39/00—Aircraft not otherwise provided for
    • B64C39/02—Aircraft not otherwise provided for characterised by special use
    • B64C39/024—Aircraft not otherwise provided for characterised by special use of the remote controlled vehicle type, i.e. RPV
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography

Definitions

  • the present invention relates to the field of insurance claims, in particular to an insurance claim processing method and device.
  • the UAV can be operated remotely for the first time to achieve data collection on the spot.
  • the automatic flight operation minimizes the interference of human factors and ensures the high quality and consistency of the collected data.
  • the inspection report is automatically formed, which greatly shortens the processing cycle of claim settlement cases, and minimizes risks and costs in the process of claims settlement for insurance companies.
  • the automatic flight detection process technology through drones has been promoted and used in insurance claims in the United States, mainly for post-disaster claims after large-scale forest fires and wind and flood disasters, such as the forest fire in California in November 2018 .
  • the second largest home insurance company in the United States has adopted drone automatic flight technology and systems to collect data on large-scale house damage, and take photos through the system Analyze, determine and save the loss, and accept the report generated by the system as the basis for claim settlement.
  • LovelandInnovationLLC and Kespry respectively cooperated with the top ten housing insurance companies in the United States to use drones to collect claims data, improve the processing cycle of insurance claims, and gradually promote them in the industry.
  • the application of drone technology in insurance claims still has two major shortcomings. The first is to collect the necessary data for automatic flight of houses of different shapes, sizes, and contours; the second is to automatically process photo information. Photo information is automatically converted into reports required for insurance claims.
  • the manual processing of photo information is the current processing method adopted by most insurance, claims, and housing companies.
  • the labor cost is high, and it is easy to misjudge or lose part of the damaged information.
  • the embodiments of the present invention provide an insurance claim processing method and device, so as to at least solve the technical problem of slow image data processing speed in the existing insurance claim process.
  • an insurance claims processing method which includes the following steps:
  • the user makes a claim application
  • the method also includes:
  • the drone is equipped with an automatic flight algorithm of the drone.
  • the automatic flight algorithm of the drone adjusts the flight trajectory of the drone according to the set flight parameters and the shape and size of the claim, and the most comprehensive one is with the least number of photos taken. Covers the entire claim; the complete photo is used to identify and mark the damage of the claim through the drone's automatic flight algorithm.
  • flight parameters of the drone include: the outermost boundary of the land where the claim is located, the outer boundary of the claim itself, the number of layers of the claim, and the estimated height of the highest obstacle around the claim.
  • the modes for taking photos of the claims include: overview map shooting, 360-degree flight shooting, overall claims shooting, and close-up shooting of claims details;
  • the height settings for taking photos of the claims are: overview map shooting is the highest point shooting, 360-degree flight shooting is the second highest point shooting, overall claims shooting is the third highest point shooting, and close-up details of the claims are the lowest point shooting .
  • the drone's automatic flight algorithm determines the height and angle of the photo collection according to its empirical formula when the details of the claims are taken at close range.
  • the claim settlement is a house, and the number of photos taken of the house is 30-100.
  • the claims platform will perform 3D point cloud reconstruction and denoising section processing of the complete photos, and conduct a preliminary review of the complete photos. After the preliminary review is passed, the claims will be measured After the initial review fails, the claims platform informs the drone of the missing photo information and controls the drone to collect secondary photo data.
  • an insurance claims processing device including:
  • Claim application unit for users to make claims application
  • the photographing unit is used to allocate a drone to take photos of the claim at the location according to the location information in the claim application, obtain the complete photo required for the claim, and identify and mark the complete photo for damage to the claim;
  • the claim report generating unit is used to upload the complete photos after the damage identification and labeling of the claims, and to measure and evaluate the damage according to the uploaded complete photos, and form a claim report.
  • the device also includes:
  • the claim report submission unit is used to review the claim report and submit the claim report to the insurance company after the review is passed.
  • the automatic flight acquisition technology of the UAV of the present invention does not require any modification to the UAV.
  • the automatic flight algorithm and flight mode of the UAV are integrated into the mobile phone application terminal, and the user can directly download and install it.
  • the one-time data collection retains the complete data correlation, and the marked data during the flight speeds up the post-processing time.
  • Figure 1 is a flow chart of the insurance claim processing method of the present invention
  • Figure 2 is a preferred flow chart of the insurance claims processing method of the present invention
  • Figure 3 is the presentation diagram of the UAV automatic flight data collection mode on the mobile phone application side
  • Figure 4 is a simulation diagram of the automatic flight data collection mode of the UAV
  • Figure 5 is a diagram of the claim information page of a claim settlement case
  • Figure 6 is the entire flow chart of the insurance claims method
  • Figure 7 is a diagram of four shooting modes in the automatic flight of the drone.
  • Fig. 8 is a diagram of relative flying heights of the four shooting modes in Fig. 7;
  • FIG. 9 is the first mode diagram in FIG. 7;
  • Figure 10 is the second mode diagram in Figure 7;
  • FIG. 11 is a third mode diagram in FIG. 7;
  • Figure 12 is the fourth mode diagram in Figure 7;
  • Figure 13 is a three-dimensional measurement result diagram formed based on the high-definition photos collected by the drone;
  • Figure 14 is the UAV obtaining all the photos and classification information map
  • Figure 15 is a page diagram for viewing and downloading reports
  • Figure 16 is a diagram of the bidding page of the claims platform
  • Figure 17 is a page diagram of manual task assignment
  • Figure 18 is a block diagram of the insurance claims processing device of the present invention.
  • Figure 19 is a preferred module diagram of the insurance claims processing device of the present invention.
  • a method for processing insurance claims includes the following steps:
  • S102 According to the location information in the claim settlement application, assign a drone to take a picture of the claim settlement at that location, obtain the complete photo required for the settlement, and identify and mark the damage of the claim settlement on the complete photo;
  • S103 Upload the complete photo after the damage identification and labeling of the claim settlement object on the Internet, measure and evaluate the damage of the claim settlement object according to the uploaded complete photo, and form a claim settlement report.
  • the UAV automatic flight acquisition technology of the present invention does not require any modification to the UAV, the UAV automatic flight algorithm and flight mode are integrated into the mobile phone application terminal, and the user can directly download, install and use.
  • the one-time data collection retains the complete data correlation, and the marked data during the flight speeds up the post-processing time. All high-definition pictures can be uploaded automatically without taking out the UAV storage card.
  • the construction of the process of this method, automatic damage recognition algorithm and automatic report generation reduce the post-processing time of claims to the shortest and greatly reduce the cost of claims.
  • the method further includes:
  • S104 Review the claims report, and submit the claims report to the insurance company after passing the review.
  • the user applies for claims through the mobile phone application and sets the flight parameters of the drone;
  • the drone is equipped with an automatic flight algorithm of the drone.
  • the automatic flight algorithm of the drone adjusts the flight trajectory of the drone according to the set flight parameters and the shape and size of the claim, and the most comprehensive one is with the least number of photos taken. Covers the entire claim; the complete photo is used to identify and mark the damage of the claim through the drone's automatic flight algorithm.
  • the flight parameters of the drone include: the outermost boundary of the land where the claim is located, the outer boundary of the claim itself, the number of layers of the claim, and the estimated height of the highest obstacle around the claim.
  • the modes for taking photos of the claims include: overview map shooting, 360-degree flight shooting, overall claims shooting, and close-range shooting of claims details;
  • the height settings for taking photos of the claims are: overview map shooting is the highest point shooting, 360-degree flight shooting is the second highest point shooting, overall claims shooting is the third highest point shooting, and close-up details of the claims are the lowest point shooting .
  • the drone automatic flight algorithm determines the height and angle of the photo collection according to its empirical formula when the details of the claims are taken at close range.
  • the claim settlement is a house, and the number of photos taken of the house is 30-100.
  • the complete photos after the damage identification and labeling of the claims are uploaded online, and the compensation is measured and damaged according to the uploaded complete photos, and the claims report is formed including:
  • the claims platform will perform 3D point cloud reconstruction and denoising section processing of the complete photos, and conduct a preliminary review of the complete photos. After the preliminary review is passed, the claims will be measured After the initial review fails, the claims platform informs the drone of the missing photo information and controls the drone to collect secondary photo data.
  • the method of the present invention innovatively develops a set of algorithms and processes in the automatic flight of drones, and is developed into a mobile phone application. After the user simply enters a few necessary parameters, the user can take off with one key and complete the data collection in one go. The drone automatically returns to home and automatically uploads data. This improvement avoids incomplete data that may be caused by human data collection, and at the same time, all photo data is marked by algorithms, which greatly improves the speed and accuracy of post-data processing.
  • the present invention will provide the customer with a complete damage assessment report within 1-3 minutes after the drone photo is returned to its processing platform (claims platform). For each captured photo, Identify and mark the damage. For damage caused by strong wind and hail, the recognition rate of the method provided by the present invention can reach more than 95%.
  • the present invention mainly includes the following contents:
  • the insurance claim settlement method of the present invention includes the overall process of data acquisition, data processing, and final completion report submission to the insurance company.
  • the drone automatic flight algorithm of the present invention can adjust the flight trajectory according to the set parameters, so as to achieve the most comprehensive coverage of the entire house with the least number of photos, thereby providing Complete claims report.
  • Figure 3 is a rendering of the UAV automatic flight data collection mode on the mobile phone application side.
  • the user needs to use the mobile app to define the four flight parameters of the drone before taking off.
  • the first is the outermost boundary of the land where the house is located (the solid line of the outer circle), and the second is the outer boundary of the house itself ( The solid line in the inner circle), the third is the number of floors of the house, and the last is the estimated height of the tallest obstacle around the building.
  • the drone's automatic flight algorithm will automatically calculate the drone's optimal flight route and the shooting angle required for each photo.
  • Figure 4 is a simulation diagram of the drone's automatic flight data collection mode. It can be seen the definition of the height of the house and surrounding obstacles.
  • the house is generally a whole with a physical boundary line.
  • the height of the surrounding obstacles refers to the bottom of the house to the periphery
  • the vertical distance of the highest point of the obstacle can help the UAV automatically avoid the obstacle, so that the UAV automatic flight algorithm can give the optimal shooting height.
  • Figure 7 is a diagram of four shooting modes in the automatic flight of the drone.
  • the definition of these modes is a summary of experience obtained by classifying, comparing, and optimizing photos collected from the flight of thousands of houses.
  • Generally include overview map shooting (top-down overview map shooting of the house building), 360-degree flight shooting (360-degree flight shooting around the house building), and overall roof shooting (scanning the details of the entire roof above the roof of the house building) As well as close-up shots of roof details (collecting the most detailed close-up shots on the roof of a house building), etc.
  • Figure 8 is the relative flight height map of the four shooting methods in Figure 7, in which the overview map is taken at the highest point, the 360-degree flight shot is taken at the second highest point, the whole roof is taken at the third highest point, and the roof details are taken at close range Shoot for the lowest point.
  • Figure 9 is the first mode diagram in Figure 7, which is a top-down overview of the house construction.
  • the photos taken in this flight mode will be used as a map of the house.
  • all the detected damage will be projected to this picture, thus giving the insurance company a global reference picture.
  • Figure 10 is the second mode diagram in Figure 7. It is a 360-degree flight around the building to capture pictures of different angles around the house. This kind of photo plays a vital role in the generation of house measurement data.
  • Figure 11 is the third mode diagram in Figure 7, which is a detailed picture of the entire roof scanned above the roof of a house building. This picture is used to connect and establish correlation between the pictures taken in the first and fourth modes Sex.
  • Figure 12 is the fourth pattern in Figure 7, which is the most detailed close-up photograph of the roof of a house building.
  • the empirical formula in the automatic flight algorithm of the drone determines the height and angle of the close-up photo collection, so as to obtain the clearest photo for automatic damage identification.
  • Figure 13 is a three-dimensional measurement result diagram formed based on the high-definition photos collected by the drone. It includes four processing steps, which are image acquisition, 3D point cloud reconstruction, denoising section, and measurement report generation.
  • the measurement accuracy of the unmanned aerial vehicle photos collected in the automatic flight mode of the present invention exceeds 99.5% of the linear accuracy and the area accuracy exceeds 99%.
  • the insurance claims industry in the United States is generally accepted and recognized. In terms of processing time, the technology of the present invention is far ahead of other similar technologies.
  • the photos will be automatically uploaded to the claims platform, which integrates the various functions and application interfaces required in the process.
  • Figure 5 is a diagram of the claims information page of a claims case, which contains the address of the house to be settled, the head of the household, insurance information, inspection arrangements and other related content, and allows users to select the type of report required under this page.
  • Figure 14 is the UAV to obtain all the photos and classification information map. Users can upload, download, delete, and add photos related to claims settlement on this page.
  • Figure 15 is a page diagram for viewing and downloading reports. This page clearly displays all the reports required by the user. The user can download the report directly, or share the report directly from the claims platform by filling in the email to others.
  • the claims settlement platform of the present invention is a multifunctional platform, and different page designs can be carried out according to the nature and requirements of different enterprises.
  • the three pages mentioned above are designed for insurance claims.
  • Figure 16 is a picture of the bidding page of the claims platform, which is specially designed for house maintenance companies and is also a direction for the platform to expand its use.
  • Figure 6 is the entire flow chart of the insurance claims method.
  • the method will search for drone pilots within 50 kilometers of the surrounding buildings based on the location of the building, automatically select the appropriate pilot based on the previous pilot’s rating and service range, and assign the task to that pilot. Flying hand.
  • the pilot can accept or reject tasks through the mobile app. If the task is rejected, the manager will step in for manual assignment and confirmation.
  • Figure 17 is a page diagram of manual task assignment.
  • the pilot After accepting the task, the pilot needs to contact the head of the household within 24 hours to confirm the inspection time, and arrive at the scene on time at the agreed inspection time for data collection and drone photo upload.
  • the drone's automatic flight algorithm will automatically detect from multiple angles whether the photos meet the requirements and whether the information required for claims is complete. If the preliminary review of the method is passed, the method will automatically start processing the house measurement and damage assessment, and finally form a complete claims report. If the preliminary review is not passed, the pilot will be notified of the missing information and the pilot will conduct secondary data collection.
  • an insurance claims processing device including:
  • a claim application unit 201 is used for a user to make a claim application, and the claim application unit 201 may be a mobile phone application terminal used by the customer;
  • the photographing unit 202 is configured to allocate a drone to take photos of the claim at the location according to the location information in the claim application, obtain the complete photo required for the claim, and identify and mark the complete photo for damage to the claim;
  • the claim settlement report generating unit 203 is configured to upload the complete photos after the damage identification and labeling of the claim settlements on the Internet, measure and evaluate the damages according to the uploaded complete photos, and form a claims settlement report.
  • the claim settlement report generating unit 203 may be the following claims settlement platform.
  • the UAV automatic flight acquisition technology of the present invention does not require any modification to the UAV, the UAV automatic flight algorithm and flight mode are integrated into the mobile phone application terminal, and the user can directly download, install and use.
  • the one-time data collection retains the complete data correlation, and the marked data during the flight speeds up the post-processing time. All high-definition pictures can be uploaded automatically without taking out the UAV storage card.
  • the construction of the device process, automatic damage recognition algorithm, and automatic report generation reduce the post-processing time of claims to the shortest and greatly reduce the cost of claims.
  • the device further includes:
  • the claims report submission unit 204 is configured to review the claims report, and submit the claims report to the insurance company after passing the review.
  • the device of the present invention innovatively develops a complete set of algorithms and processes in the automatic flight of drones, and is developed into a mobile phone application. After the user simply enters a few necessary parameters, it takes off with one key and completes data collection in one go. The drone automatically returns to home and automatically uploads data. This improvement avoids incomplete data that may be caused by human data collection. At the same time, all photo data is marked by algorithms, which greatly improves the speed and accuracy of post-data processing.
  • the present invention will provide the customer with a complete damage assessment report within 1-3 minutes after the drone photo is returned to its processing platform (claims platform). For each captured photo, Identify and mark the damage. For damage caused by strong wind and hail, the recognition rate of the method and device provided by the present invention can reach more than 95%.
  • the present invention mainly includes the following contents:
  • the insurance claim settlement device of the present invention includes the overall process of data acquisition, data processing, and final completion report submission to the insurance company.
  • the drone automatic flight algorithm of the present invention can adjust the flight trajectory according to the set parameters, so as to achieve the most comprehensive coverage of the entire house with the least number of photos, thereby providing Complete claims report.
  • Figure 3 is a rendering of the UAV automatic flight data collection mode on the mobile phone application side.
  • the user needs to use the mobile app to define the four flight parameters of the drone before taking off.
  • the first is the outermost boundary of the land where the house is located (the solid line of the outer circle), and the second is the outer boundary of the house itself ( The solid line in the inner circle), the third is the number of floors of the house, and the last is the estimated height of the tallest obstacle around the building.
  • the drone's automatic flight algorithm will automatically calculate the drone's optimal flight route and the shooting angle required for each photo.
  • Figure 4 is a simulation diagram of the drone's automatic flight data collection mode. It can be seen the definition of the height of the house and surrounding obstacles.
  • the house is generally a whole with a physical boundary line.
  • the height of the surrounding obstacles refers to the bottom of the house to the periphery
  • the vertical distance of the highest point of the obstacle can help the UAV automatically avoid the obstacle, so that the UAV automatic flight algorithm can give the optimal shooting height.
  • Figure 7 is a diagram of four shooting modes in the automatic flight of the drone.
  • the definition of these modes is a summary of experience obtained by classifying, comparing and optimizing photos collected from the flight of thousands of houses.
  • Generally include overview map shooting (top-down overview map shooting of the house building), 360-degree flight shooting (360-degree flight shooting around the house building), and overall roof shooting (scanning the details of the entire roof above the roof of the house building) As well as close-up shots of roof details (collecting the most detailed close-up shots on the roof of a house building), etc.
  • Figure 8 is the relative flight height map of the four shooting methods in Figure 7, in which the overview map is taken at the highest point, the 360-degree flight shot is taken at the second highest point, the whole roof is taken at the third highest point, and the roof details are taken at close range Shoot for the lowest point.
  • Figure 9 is the first mode diagram in Figure 7, which is a top-down overview of the house construction.
  • the photos taken in this flight mode will be used as a map of the house.
  • all the detected damage will be projected to this picture, thus giving the insurance company a global reference picture.
  • Figure 10 is the second mode diagram in Figure 7. It is a 360-degree flight around the building, capturing pictures of different angles around the house. This kind of photo plays a vital role in the generation of house measurement data.
  • Figure 11 is the third mode diagram in Figure 7, which is a detailed picture of the entire roof scanned above the roof of a house building. This picture is used to connect and establish correlation between the pictures taken in the first and fourth modes Sex.
  • Figure 12 is the fourth pattern in Figure 7, which is the most detailed close-up photograph of the roof of a house building.
  • the empirical formula in the automatic flight algorithm of the UAV determines the height and angle of the close-up photo collection, so as to obtain the clearest photo for automatic damage identification.
  • 30-100 photos are generally collected for a house.
  • Figure 13 is a three-dimensional measurement result diagram formed based on the high-definition photos collected by the drone. It includes four processing steps, which are image acquisition, 3D point cloud reconstruction, denoising section, and measurement report generation.
  • the measurement accuracy of the unmanned aerial vehicle photos collected in the automatic flight mode of the present invention exceeds 99.5% of the linear accuracy and the area accuracy exceeds 99%.
  • the insurance claims industry in the United States is generally accepted and recognized. In terms of processing time, the technology of the present invention is far ahead of other similar technologies.
  • the photos will be automatically uploaded to the claims platform, which integrates the various functions and application interfaces required in the process.
  • Figure 5 is a diagram of the claim information page of a claim settlement case, which contains the address of the house to be settled, the head of the household, insurance information, inspection arrangements, and other related content. At the same time, the user is allowed to select the required report type on this page.
  • Figure 14 is the UAV obtaining all photos and classification information map. Users can upload, download, delete, and add photos related to claims settlement on this page.
  • Figure 15 is a page diagram for viewing and downloading reports. This page clearly displays all the reports required by the user. The user can download the report directly, or share the report directly from the claims platform by filling in the email to others.
  • the claims settlement platform of the present invention is a multifunctional platform, and different page designs can be carried out according to the nature and requirements of different enterprises.
  • the three pages mentioned above are designed for insurance claims.
  • Figure 16 is a picture of the bidding page of the claims platform, which is specially designed for house maintenance companies and is also a direction for the platform to expand its use.
  • Fig. 6 is the entire flow chart of the insurance claim settlement device.
  • the device When receiving a claim, the device will search for drone pilots within 50 kilometers of the surrounding buildings based on the location of the building, automatically select the appropriate pilot based on the previous pilot’s rating and service range, and assign the task to that pilot. Flying hand. The pilot can accept or reject tasks through the mobile app. If the task is rejected, the manager of the device will step in for manual assignment and confirmation.
  • Figure 17 is a page diagram of manual task assignment.
  • the pilot After accepting the task, the pilot needs to contact the head of the household within 24 hours to confirm the inspection time, and arrive at the scene on time at the agreed inspection time for data collection and drone photo upload.
  • the drone's automatic flight algorithm will automatically detect from multiple angles whether the photos meet the requirements and whether the information required for claims is complete. If it passes the preliminary review of the device, the device will automatically start processing the house measurement and damage assessment, and finally form a complete claims report. If the device fails the preliminary review, the pilot will be notified of the missing information, and the pilot will conduct secondary data collection.
  • the automatic flight acquisition technology of the UAV of the present invention does not require any modification to the UAV.
  • the automatic flight algorithm and flight mode of the UAV are integrated into the mobile phone application terminal, and the user can directly download and install it.
  • the one-time data collection preserves the complete data correlation, and the marked data during the flight speeds up the post-processing time.
  • all high-definition pictures can be uploaded automatically without removing the UAV storage card.
  • the construction of the method and device process, automatic damage recognition algorithm and automatic report generation minimize the post-processing time of claims and greatly reduce the cost of claims.
  • the invention also has large-scale applications in insurance underwriting.
  • this technology can be applied.
  • the present invention and its drone automatic flight acquisition technology can be applied and expanded.

Abstract

本发明涉及保险理赔领域，具体涉及一种保险理赔处理方法及装置。该方法及装置首先由用户进行理赔申请，再根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注，最后将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。该方法及装置不需要对无人机进行任何改造，无人机自动飞行算法和飞行模式都集成到例如手机应用端，用户可以直接下载安装使用。一次性数据采集，保留了完整的数据相关性，同时飞行过程中标注好的数据加快了后期处理的时间。无需取出无人机储存卡即可自动上传所有的高清图片。

Description

一种保险理赔处理方法及装置 技术领域
本发明涉及保险理赔领域，具体而言，涉及一种保险理赔处理方法及装置。
背景技术
随着无人机技术的不断完善和飞控技术的更新迭代，利用无人机采集房屋建筑照片，通过系统的处理和分析，结合自动报告的技术，建立了一套完整的无人机检测流程并应用在保险行业当中。传统的理赔流程，依靠人力的检测、采样、分析，费事费力，且对检测人员有相当的风险。尤其是在极端天气多发地区，例如台风过后，检测人员无法第一时间达到现场进行数据采集，检测的过程当中因为各种天气或不可控的因素，可能会对检测人员的人身安全形成威胁，采集数据的质量也会受到各种因素的干扰。
通过无人机的自动飞行检测流程，可以第一时间远距离操作无人机达到现场进行数据采集，自动飞行操作最大程度降低了人为因素的干扰，保证所采集数据的高质量和一致性。再通过系统的分析和处理，自动形成检测报告，极大的缩短了理赔案子的处理周期，并且最大程度的为保险公司减低风险和降低理赔过程中的成本。
通过无人机进行自动飞行检测流程技术已经在美国的保险理赔中开始推广使用，主要是在大面积的森林大火和风灾水灾之后的灾后理赔工作，比如在2018年11月份美国加州发生的森林大火，2018年10月在美国北卡罗莱纳州发生的飓风，美国第二大房屋保险公司都有采用无人机自动飞行技术和系统进行大面积房屋损毁情况的数据采集，并通过系统对照片进行分析、定损和保存，并接受系统生成的报告作为理赔的依据。同时，LovelandInnovationLLC公司、Kespry公司都分别和美国前十大的房屋保险公司合作利用无人机来采集理赔数据、提高保险理赔的处理周期，并逐渐在业界推广。
目前无人机技术在保险理赔中的应用主要还存在两大缺点，第一，是针对不同形状、大小、轮廓的房屋建筑进行自动飞行采集必须的数据；第二，是自 动处理照片信息，将照片信息自动转化为保险理赔所需要的报告。
第一，针对无人机采集数据，有些企业采用改造无人机本身，让无人机加载更多的设备，同时添加配套设备来保证无人机的正常工作，这样首先无人机本身的成本就会大幅度提高，且受生产能力的限制，无法大规模推广使用。还有些企业则采用通过更换不同的设备或镜头，用无人机多次起飞降落来收集到足够多的数据，这样多次采集，因为数据之间的关联性下降，会增加后期处理照片的难度，且增加后期处理的时间周期。
第二，人工处理照片信息是目前据大多数保险、理赔、房屋企业所采取的处理方式，人工成本高，且容易误判或者丢失部分损伤的信息。
发明内容
本发明实施例提供了一种保险理赔处理方法及装置，以至少解决现有保险理赔过程中图片数据处理速度慢的技术问题。
根据本发明的一实施例，提供了一种保险理赔处理方法，包括以下步骤：
用户进行理赔申请；
根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。
进一步地，方法还包括：
对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
进一步地，用户通过手机应用端进行理赔申请，并设定无人机的飞行参数；
无人机内设置有无人机自动飞行算法，无人机自动飞行算法根据设定的飞行参数、理赔物的形状大小来调整无人机的飞行轨迹，以最少的拍摄照片数量来最全面的涵盖整个理赔物；其中完整照片通过无人机自动飞行算法进行理赔物损伤识别和标注。
进一步地，无人机的飞行参数包括：理赔物所在土地的最外围边界、理赔 物本身的外围边界、理赔物的层数，理赔物周边最高障碍物的估算高度。
进一步地，对理赔物进行拍照的模式包括：总览图拍摄、360度飞行拍摄、整体理赔物拍摄、理赔物细节近距离拍摄；
对理赔物进行拍照的高度设置为：总览图拍摄为最高点拍摄，360度飞行拍摄为第二高点拍摄，整体理赔物拍摄为第三高点拍摄、理赔物细节近距离拍摄为最低点拍摄。
进一步地，无人机自动飞行算法在理赔物细节近距离拍摄时根据其内的经验公式确定照片采集的高度和角度。
进一步地，理赔物为房屋，对房屋进行拍照的数量为30-100张。
进一步地，将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告包括：
将进行理赔物损伤识别和标注后的完整照片上传至理赔平台，理赔平台对完整照片进行3D点云重建、去噪切面处理，并对完整照片进行初步审核，初步审核通过后对理赔物进行测量和损伤评估，并形成理赔报告；初步审核未通过后，理赔平台告知无人机缺失的照片信息，控制无人机进行二次照片数据采集。
根据本发明的另一实施例，提供了一种保险理赔处理装置，包括：
理赔申请单元，用于用户进行理赔申请；
拍照单元，用于根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
理赔报告生成单元，用于将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。
进一步地，装置还包括：
理赔报告提交单元，用于对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
本发明实施例中的保险理赔处理方法及装置的有益效果为：
首先,本发明的无人机自动飞行采集技术，不需要对无人机进行任何改造，无人机自动飞行算法和飞行模式都集成到手机应用端，用户可以直接下载安装使用。
第二，一次性数据采集，保留了完整的数据相关性，同时飞行过程中标注好的数据加快了后期处理的时间。
第三，无需取出无人机储存卡即可自动上传所有的高清图片。
第四，该系统流程的搭建、自动损伤识别算法和自动报告生成，将理赔的后处理时间压缩到最短，大大降低理赔成本。
附图说明
图1为本发明保险理赔处理方法的流程图；
图2为本发明保险理赔处理方法的优选流程图；
图3是无人机自动飞行采集数据模式在手机应用端的呈现图；
图4是无人机自动飞行采集数据模式的模拟图；
图5是理赔案的理赔信息页面图；
图6是保险理赔方法的整个流程图；
图7是无人机自动飞行中的四种拍摄模式图；
图8是图7四种拍摄方式的相对飞行高度图；
图9是图7中的第一种模式图；
图10是图7中的第二种模式图；
图11是图7中的第三种模式图；
图12是图7中的第四种模式图；
图13是基于无人机所采集的高清照片而形成的三维测量结果图；
图14是无人机获取所有的照片及分类信息图；
图15是查看并下载报告的页面图；
图16是理赔平台的竞标页面图；
图17是手动分配任务的页面图；
图18为本发明保险理赔处理装置的模块图；
图19为本发明保险理赔处理装置的优选模块图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。
实施例1
根据本发明一实施例，提供了一种保险理赔处理方法，参见图1，包括以下步骤：
S101:用户进行理赔申请；
S102:根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
S103:将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。
本发明的无人机自动飞行采集技术，不需要对无人机进行任何改造，无人机自动飞行算法和飞行模式都集成到手机应用端，用户可以直接下载安装使用。一次性数据采集，保留了完整的数据相关性，同时飞行过程中标注好的数据加快了后期处理的时间。无需取出无人机储存卡即可自动上传所有的高清图片。该方法流程的搭建、自动损伤识别算法和自动报告生成，将理赔的后处理时间压缩到最短，大大降低理赔成本。
作为优选的技术方案中，参见图2，方法还包括：
S104:对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
作为优选的技术方案中，用户通过手机应用端进行理赔申请，并设定无人机的飞行参数；
无人机内设置有无人机自动飞行算法，无人机自动飞行算法根据设定的飞 行参数、理赔物的形状大小来调整无人机的飞行轨迹，以最少的拍摄照片数量来最全面的涵盖整个理赔物；其中完整照片通过无人机自动飞行算法进行理赔物损伤识别和标注。
作为优选的技术方案中，无人机的飞行参数包括：理赔物所在土地的最外围边界、理赔物本身的外围边界、理赔物的层数，理赔物周边最高障碍物的估算高度。
作为优选的技术方案中，对理赔物进行拍照的模式包括：总览图拍摄、360度飞行拍摄、整体理赔物拍摄、理赔物细节近距离拍摄；
对理赔物进行拍照的高度设置为：总览图拍摄为最高点拍摄，360度飞行拍摄为第二高点拍摄，整体理赔物拍摄为第三高点拍摄、理赔物细节近距离拍摄为最低点拍摄。
作为优选的技术方案中，无人机自动飞行算法在理赔物细节近距离拍摄时根据其内的经验公式确定照片采集的高度和角度。
作为优选的技术方案中，理赔物为房屋，对房屋进行拍照的数量为30-100张。
作为优选的技术方案中，将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告包括：
将进行理赔物损伤识别和标注后的完整照片上传至理赔平台，理赔平台对完整照片进行3D点云重建、去噪切面处理，并对完整照片进行初步审核，初步审核通过后对理赔物进行测量和损伤评估，并形成理赔报告；初步审核未通过后，理赔平台告知无人机缺失的照片信息，控制无人机进行二次照片数据采集。
本发明的方法创新性的在无人机自动飞行方面开发了一整套算法和流程，且开发成手机应用，在用户简单的输入几个必要的参数之后，一键起飞，一气呵成完成数据的采集，无人机自动返航并自动上传数据。如此改进避免了人为数据采集可能造成的数据不完整，同时所有照片数据都通过算法进行了标注， 从而大大提高后期数据处理的速度和准确度。
同时在自动处理照片信息方面，本发明在无人机照片传回其处理平台(理赔平台)后1-3分钟之内，会给客户提供完整的定损报告，针对每一张获取的照片，进行损伤的识别和标注。对于大风和冰雹造成的损伤，本发明提供的方法的识别率，可以达到95％以上。
下面以具体实施例，对本发明保险理赔处理方法进行详细说明：
本发明主要包括以下内容：
1.无人机自动飞行采集技术在保险理赔行业里的应用；
2.本发明的保险理赔方法，包括从数据获取、数据处理、最终形成完成报告提交给保险公司的整体流程。
无人机自动飞行采集技术：
针对不同类型的房屋形状大小，本发明的无人机自动飞行算法，可以根据所设定的参数来调整飞行轨迹，从而达到用最少的照片数量来最全面的涵盖整个房屋的信息，进而可以提供完整的理赔报告。
图3是无人机自动飞行采集数据模式在手机应用端的呈现图。用户需要在起飞之前使用手机应用端定义无人机的四个飞行参数，第一个是房屋建筑所在土地的最外围边界(外圈的实线)，第二个是房屋建筑本身的外围边界(内圈的实线)，第三个是房屋的层数，最后一个是房屋建筑周边最高障碍物的估算高度。当四个参数定义好之后，无人机自动飞行算法会自动计算出无人机最优的飞行路线和每张照片所需要的拍摄角度。
图4是无人机自动飞行采集数据模式的模拟图，可以看出房屋和周边障碍物高度的定义，房屋一般是具有实体边界线的整体，周边障碍物的高度指的是房屋底面到该周边障碍物最高点的垂直距离，可以帮助无人机自动避开障碍物，从而使得无人机自动飞行算法可以给出最优的拍摄高度。
图7是无人机自动飞行中的四种拍摄模式图。这些模式的定义，是通过对上千套房屋的飞行所采集回来的照片，进行分类、对比、优化，从而得出的经验总结。一般包括总览图拍摄(房屋建筑自上而下的总览图拍摄)、360度飞 行拍摄(绕着房屋建筑进行360度飞行拍摄)、整体屋顶拍摄(房屋建筑的屋顶上方扫描整个屋顶的细节拍摄)以及屋顶细节近距离拍摄(在房屋建筑的屋顶上采集最细致的近距离拍摄)等。
图8是图7四种拍摄方式的相对飞行高度图，其中总览图拍摄为最高点拍摄，360度飞行拍摄为第二高点拍摄，整体屋顶拍摄为第三高点拍摄以及屋顶细节近距离拍摄为最低点拍摄。
图9是图7中的第一种模式图，是房屋建筑自上而下的总览图，在房屋定损的过程中，这种飞行模式下拍摄所获取的照片会被用作房屋间的地图，最终所有检测到的损伤都会投影到这张图片，从而给保险公司一个全局参考图。
图10是图7中的第二种模式图，是绕着房屋建筑进行360度飞行，捕捉房屋外围各个不同角度的图片，对于房屋测量数据的生成，这种照片起到了至关重要的作用。
图11是图7中的第三种模式图，是在房屋建筑的屋顶上方扫描整个屋顶的细节图片，这种图片是为了将第一种和第四种模式下拍摄的图片进行对接和建立相关性。
图12是图7中的第四种模式图，则是对房屋建筑的屋顶采集最细致的近距离照片。无人机自动飞行算法里面的经验公式来决定近距离照片采集的高度和角度，从而获取最清晰的照片来进行自动损伤识别。受限于无人机镜头的清晰程度(4K镜头，不带变焦或仅有2倍变焦)，近距离采集的照片才可以用作损伤识别，并保证不低于90％的精度要求。综合以上四种拍摄方式，根据房屋面积的大小，一般一套房屋建筑需要采集30-100张照片。
图13是基于无人机所采集的高清照片而形成的三维测量结果图。包括四个处理步骤，分别为图像采集、3D点云重建、去噪切面、生成测量报告。本发明自动飞行方式下采集的无人机照片可以达到的测量精度比线性精度超过99.5％，面积精度超过99％。在美国的保险理赔行业被普遍接受认可，从处理时间上来考量，本发明的技术遥遥领先于其他相似的技术。
理赔平台：
在获取无人机照片之后，照片将自动上传到理赔平台，这个平台集成了流程中所需要的各项功能和应用界面。
图5是理赔案的理赔信息页面图，里面包含了被理赔房屋的地址、户主、保险信息、检测安排等相关的内容，同时允许用户在此页面下选择所需要的报告种类。
图14是无人机获取所有的照片及分类信息图。用户可以在此页面上传、下载、删减、添加与理赔案相关的照片。
图15是查看并下载报告的页面图。该页面上清晰的显示了用户需要的所有报告，用户可以直接下载报告，也可以直接从理赔平台将报告通过填写邮件的方式分享给他人。
本发明的理赔平台是一个多功能的平台，针对不同的企业性质和需求可以进行不同的页面设计。以上所提到的三个页面(图5、图14、图15的页面)是针对保险理赔设计的页面。
图16是理赔平台的竞标页面图，则是专门为房屋维修公司而设计的，也是平台拓展使用的一个方向。
保险理赔流程：
图6是保险理赔方法的整个流程图。
在接收到理赔案的时候，该方法会根据房屋建筑的位置寻找周边50公里内的无人机飞手，根据以往飞手的评分和服务范围自动选择合适的飞手，并将任务分配给该飞手。该飞手通过手机应用端可以接受或拒绝任务。如果任务被拒绝，管理人员则会介入进行手动分配和确认。图17是手动分配任务的页面图。
飞手在接受任务之后，则需要在24小时之内联系户主并确认检测时间，在约定的检测时间准时达到现场进行数据采集和无人机照片上传。
当无人机照片上传回理赔平台之后，无人机自动飞行算法会自动从多角度检测照片是否符合要求，理赔所需的信息是否完整。如果通过了该方法的初步审核，则该方法会自动开始处理房屋的测量和损伤评估，并最终形成完整的理 赔报告。如果没有通过初步审核，飞手将被告知缺失的信息，飞手将会进行二次数据采集。
理赔报告在通过审核之后，会直接提交给保险公司，便于保险公司进行后续的理赔事宜，方便快捷。
实施例2
根据本发明的另一实施例，提供了一种保险理赔处理装置，参见图18，包括：
理赔申请单元201，用于用户进行理赔申请，该理赔申请单元201可以为客户使用的手机应用端；
拍照单元202，用于根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
理赔报告生成单元203，用于将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。该理赔报告生成单元203可以为下述的理赔平台。
本发明的无人机自动飞行采集技术，不需要对无人机进行任何改造，无人机自动飞行算法和飞行模式都集成到手机应用端，用户可以直接下载安装使用。一次性数据采集，保留了完整的数据相关性，同时飞行过程中标注好的数据加快了后期处理的时间。无需取出无人机储存卡即可自动上传所有的高清图片。该装置流程的搭建、自动损伤识别算法和自动报告生成，将理赔的后处理时间压缩到最短，大大降低理赔成本。
作为优选的技术方案中，参见图19，装置还包括：
理赔报告提交单元204，用于对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
本发明的装置创新性的在无人机自动飞行方面开发了一整套算法和流程，且开发成手机应用，在用户简单的输入几个必要的参数之后，一键起飞，一气呵成完成数据的采集，无人机自动返航并自动上传数据。如此改进避免了人为 数据采集可能造成的数据不完整，同时所有照片数据都通过算法进行了标注，从而大大提高后期数据处理的速度和准确度。
同时在自动处理照片信息方面，本发明在无人机照片传回其处理平台(理赔平台)后1-3分钟之内，会给客户提供完整的定损报告，针对每一张获取的照片，进行损伤的识别和标注。对于大风和冰雹造成的损伤，本发明提供的方法及装置的识别率，可以达到95％以上。
下面以具体实施例，对本发明保险理赔处理装置进行详细说明：
本发明主要包括以下内容：
1.无人机自动飞行采集技术在保险理赔行业里的应用；
2.本发明的保险理赔装置，包括从数据获取、数据处理、最终形成完成报告提交给保险公司的整体流程。
无人机自动飞行采集技术：
针对不同类型的房屋形状大小，本发明的无人机自动飞行算法，可以根据所设定的参数来调整飞行轨迹，从而达到用最少的照片数量来最全面的涵盖整个房屋的信息，进而可以提供完整的理赔报告。
图3是无人机自动飞行采集数据模式在手机应用端的呈现图。用户需要在起飞之前使用手机应用端定义无人机的四个飞行参数，第一个是房屋建筑所在土地的最外围边界(外圈的实线)，第二个是房屋建筑本身的外围边界(内圈的实线)，第三个是房屋的层数，最后一个是房屋建筑周边最高障碍物的估算高度。当四个参数定义好之后，无人机自动飞行算法会自动计算出无人机最优的飞行路线和每张照片所需要的拍摄角度。
图4是无人机自动飞行采集数据模式的模拟图，可以看出房屋和周边障碍物高度的定义，房屋一般是具有实体边界线的整体，周边障碍物的高度指的是房屋底面到该周边障碍物最高点的垂直距离，可以帮助无人机自动避开障碍物，从而使得无人机自动飞行算法可以给出最优的拍摄高度。
图7是无人机自动飞行中的四种拍摄模式图。这些模式的定义，是通过对上千套房屋的飞行所采集回来的照片，进行分类、对比、优化，从而得出的经 验总结。一般包括总览图拍摄(房屋建筑自上而下的总览图拍摄)、360度飞行拍摄(绕着房屋建筑进行360度飞行拍摄)、整体屋顶拍摄(房屋建筑的屋顶上方扫描整个屋顶的细节拍摄)以及屋顶细节近距离拍摄(在房屋建筑的屋顶上采集最细致的近距离拍摄)等。
图8是图7四种拍摄方式的相对飞行高度图，其中总览图拍摄为最高点拍摄，360度飞行拍摄为第二高点拍摄，整体屋顶拍摄为第三高点拍摄以及屋顶细节近距离拍摄为最低点拍摄。
图9是图7中的第一种模式图，是房屋建筑自上而下的总览图，在房屋定损的过程中，这种飞行模式下拍摄所获取的照片会被用作房屋间的地图，最终所有检测到的损伤都会投影到这张图片，从而给保险公司一个全局参考图。
图10是图7中的第二种模式图，是绕着房屋建筑进行360度飞行，捕捉房屋外围各个不同角度的图片，对于房屋测量数据的生成，这种照片起到了至关重要的作用。
图11是图7中的第三种模式图，是在房屋建筑的屋顶上方扫描整个屋顶的细节图片，这种图片是为了将第一种和第四种模式下拍摄的图片进行对接和建立相关性。
图12是图7中的第四种模式图，则是对房屋建筑的屋顶采集最细致的近距离照片。无人机自动飞行算法里面的经验公式来决定近距离照片采集的高度和角度，从而获取最清晰的照片来进行自动损伤识别。受限于无人机镜头的清晰程度(4K镜头，不带变焦或仅有2倍变焦)，近距离采集的照片才可以用作损伤识别，并保证不低于90％的精度要求。综合以上四种拍摄方式，根据房屋面积的大小，一般一套房屋建筑需要采集30-100张照片。
图13是基于无人机所采集的高清照片而形成的三维测量结果图。包括四个处理步骤，分别为图像采集、3D点云重建、去噪切面、生成测量报告。本发明自动飞行方式下采集的无人机照片可以达到的测量精度比线性精度超过99.5％，面积精度超过99％。在美国的保险理赔行业被普遍接受认可，从处理时间上来考量，本发明的技术遥遥领先于其他相似的技术。
理赔平台：
在获取无人机照片之后，照片将自动上传到理赔平台，这个平台集成了流程中所需要的各项功能和应用界面。
图5是理赔案的理赔信息页面图，里面包含了被理赔房屋的地址、户主、保险信息、检测安排等相关的内容，同时允许用户在此页面下选择所需要的报告种类。
图14是无人机获取所有的照片及分类信息图。用户可以在此页面上传、下载、删减、添加与理赔案相关的照片。
图15是查看并下载报告的页面图。该页面上清晰的显示了用户需要的所有报告，用户可以直接下载报告，也可以直接从理赔平台将报告通过填写邮件的方式分享给他人。
本发明的理赔平台是一个多功能的平台，针对不同的企业性质和需求可以进行不同的页面设计。以上所提到的三个页面(图3、图12、图13的页面)是针对保险理赔设计的页面。
图16是理赔平台的竞标页面图，则是专门为房屋维修公司而设计的，也是平台拓展使用的一个方向。
图6是保险理赔装置的整个流程图。
在接收到理赔案的时候，该装置会根据房屋建筑的位置寻找周边50公里内的无人机飞手，根据以往飞手的评分和服务范围自动选择合适的飞手，并将任务分配给该飞手。该飞手通过手机应用端可以接受或拒绝任务。如果任务被拒绝，则该装置的管理人员则会介入进行手动分配和确认。图17是手动分配任务的页面图。
飞手在接受任务之后，则需要在24小时之内联系户主并确认检测时间，在约定的检测时间准时达到现场进行数据采集和无人机照片上传。
当无人机照片上传回理赔平台之后，无人机自动飞行算法会自动从多角度检测照片是否符合要求，理赔所需的信息是否完整。如果通过了该装置的初步审核，则装置会自动开始处理房屋的测量和损伤评估，并最终形成完整的理赔 报告。如果没有通过装置的初步审核，飞手将被告知缺失的信息，飞手将会进行二次数据采集。
理赔报告在通过装置的审核之后，会直接提交给保险公司，便于保险公司进行后续的理赔事宜，方便快捷。
本发明的创新技术点及有益效果至少在于：
首先，本发明的无人机自动飞行采集技术，不需要对无人机进行任何改造，无人机自动飞行算法和飞行模式都集成到手机应用端，用户可以直接下载安装使用。第二，一次性数据采集，保留了完整的数据相关性，同时飞行过程中标注好的数据加快了后期处理的时间。第三，无需取出无人机储存卡即可自动上传所有的高清图片。第四，该方法及装置流程的搭建、自动损伤识别算法和自动报告生成，将理赔的后处理时间压缩到最短，大大降低理赔成本。
实验证明，本发明的处理流程可以将原本2-4周的理赔周期降低到24-48小时，对于损伤的鉴定，尤其是大风和冰雹的识别，可以达到95％以上的精度，同时可以将理赔的成本降低90％以上。
本发明除了在保险理赔方面的应用，在保险承保方面也有大规模的应用。除了在房屋建筑方面，可以应用此项技术，对于不同种类的保险，比如农业保险、油管和高压电巡检，可以将本发明及其无人机自动飞行采集技术进行应用和扩展。
上述本发明实施例序号仅仅为了描述，不代表实施例的优劣。
在本发明的上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (10)

  1. 一种保险理赔处理方法，其特征在于，包括以下步骤：
    用户进行理赔申请；
    根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
    将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。
  2. 根据权利要求1所述的保险理赔处理方法，其特征在于，所述方法还包括：
    对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
  3. 根据权利要求1所述的保险理赔处理方法，其特征在于，用户通过手机应用端进行理赔申请，并设定无人机的飞行参数；
    无人机内设置有无人机自动飞行算法，无人机自动飞行算法根据设定的飞行参数、理赔物的形状大小来调整无人机的飞行轨迹，以最少的拍摄照片数量来最全面的涵盖整个理赔物；其中完整照片通过无人机自动飞行算法进行理赔物损伤识别和标注。
  4. 根据权利要求3所述的保险理赔处理方法，其特征在于，所述无人机的飞行参数包括：理赔物所在土地的最外围边界、理赔物本身的外围边界、理赔物的层数，理赔物周边最高障碍物的估算高度。
  5. 根据权利要求3所述的保险理赔处理方法，其特征在于，对理赔物进行拍照的模式包括：总览图拍摄、360度飞行拍摄、整体理赔物拍摄、理赔物细节近距离拍摄；
    对理赔物进行拍照的高度设置为：总览图拍摄为最高点拍摄，360度飞行拍摄为第二高点拍摄，整体理赔物拍摄为第三高点拍摄、理赔物细节近距离拍摄为最低点拍摄。
  6. 根据权利要求5所述的保险理赔处理方法，其特征在于，无人机自动飞行算法在理赔物细节近距离拍摄时根据其内的经验公式确定照片采集的高度和角度。
  7. 根据权利要求3所述的保险理赔处理方法，其特征在于，所述理赔物为房屋，对房屋进行拍照的数量为30-100张。
  8. 根据权利要求1所述的保险理赔处理方法，其特征在于，所述将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告包括：
    将进行理赔物损伤识别和标注后的完整照片上传至理赔平台，理赔平台对完整照片进行3D点云重建、去噪切面处理，并对完整照片进行初步审核，初步审核通过后对理赔物进行测量和损伤评估，并形成理赔报告；初步审核未通过后，理赔平台告知无人机缺失的照片信息，控制无人机进行二次照片数据采集。
  9. 一种保险理赔处理装置，其特征在于，包括：
    理赔申请单元，用于用户进行理赔申请；
    拍照单元，用于根据理赔申请中的位置信息，分配无人机对该位置处的理赔物进行拍照，获取理赔所需的完整照片，并对完整照片进行理赔物损伤识别和标注；
    理赔报告生成单元，用于将进行理赔物损伤识别和标注后的完整照片进行网络上传，根据上传的完整照片对理赔物进行测量和损伤评估，并形成理赔报告。
  10. 根据权利要求9所述的保险理赔处理装置，其特征在于，所述装置还包括：
    理赔报告提交单元，用于对理赔报告进行审核，审核通过后将理赔报告提交至保险公司。
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