A method is provided. An unmanned aerial vehicle (UAV) is operated. A position of the UAV is determined while in flight, and a nonce is generated. A Merkel root is generated based at least in part on a timestamp and the position of the UAV. A current block is calculated based at least in part on a previous block, the Merkel root, and the nonce, and the current block, the timestamp, the nonce, the prior block, and the position of the UAV are transmitted.

In some examples, a method of vector-raster data fusion includes receiving vector data for a geographical location, and statistically analyzing the vector data to obtain vector statistics. In some examples the method further includes rasterizing the vector statistics, and storing at least one of the vector data and the rasterized vector statistics together in a key-value store together with previously stored raster data for the geographical location. In some examples, the vector data further includes metadata, and the method further includes storing the metadata in at least one of the key-value store or a separate vector database.

In some examples, a method of vector-raster data fusion includes receiving vector data for a geographical location, and statistically analyzing the vector data to obtain vector statistics. In some examples the method further includes rasterizing the vector statistics, and storing at least one of the vector data and the rasterized vector statistics together in a key-value store together with previously stored raster data for the geographical location. In some examples, the vector data further includes metadata, and the method further includes storing the metadata in at least one of the key-value store or a separate vector database.

A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.

A response system may be provided. The response system may include a security system and an autonomous drone. The security system includes a security sensor and a controller. The drone includes a processor, a memory in communication with the processor, and a drone sensor. The processor may be programmed to receive the deployment request from the security system, navigate to the one or more zones of the coverage area included in the deployment request, collect drone sensor data of the one or more zones of the coverage area using the at least one drone sensor, determine that an incident has occurred, and/or transmit the collected drone sensor data and incident verification to the security system, wherein, in response to receiving the collected drone sensor data and incident verification, the security system is configured to generate a command for responding to the incident.

Systems and methods for obstacle detection and state information determination are provided. In some embodiments, a movable object may carry one or more imaging devices. The imaging devices may be arranged on the movable object so as to have a field of view oriented vertically relative to the movable object. The arrangement of the imaging device may complement or supplant existing arrangement schemes and provide efficient, multi-functional and cost-effective means of arranging imaging devices on movable objects.

A camera control apparatus of the present disclosure includes an interface and a controller. The interface receives first image data generated by a first camera performing image capturing, second image data generated by a second camera performing image capturing, and altitude information relating to altitude, the altitude information being output by an altitude sensor, and transmits a drive signal to a first actuator capable of changing an image capturing direction of the first camera and to a second actuator capable of changing an image capturing direction of the second camera. The controller outputs the drive signal driving at least one of the first actuator and the second actuator to the interface so that an image capturing region of composite image data in which the first image data and the second image data are combined is narrower when the altitude indicated by the altitude information is lower.

Disclosed is a method and apparatus for detecting and ranging cloud features. The method comprises: obtaining image data(e.g. using a camera (200); classifying, as a cloud feature, an image segment (502-508) of the image data; determining a plurality of moments of the image segment (502-508); using the determined plurality of moments, determining a geometric representation of that image segment (502-508); and, using the geometric representation, determining a distance between the cloud feature represented by that image segment (502-508) and an entity that obtained the image data.

The present invention discloses a partition satellite mission planning method for earliest completion of regional target coverage, which includes the following steps: 1. partitioning a to-be-observed rectangular region; 2. allocating observation resources to different regions and selecting certain coverage opportunities and coverage modes thereof to minimize completion time corresponding to a formed coverage solution. The present invention can obtain a satisfactory solution capable of finishing complete coverage of regional targets as early as possible with sufficient observation resources through suitable calculation resources and achieve balance between the consumption of calculation resources and optimality of solutions, so that satellite resources can be fully used to conduct the quick and effective coverage search for important regional targets in a real environment.

The present invention discloses a partition satellite mission planning method for earliest completion of regional target coverage, which includes the following steps: 1. partitioning a to-be-observed rectangular region; 2. allocating observation resources to different regions and selecting certain coverage opportunities and coverage modes thereof to minimize completion time corresponding to a formed coverage solution. The present invention can obtain a satisfactory solution capable of finishing complete coverage of regional targets as early as possible with sufficient observation resources through suitable calculation resources and achieve balance between the consumption of calculation resources and optimality of solutions, so that satellite resources can be fully used to conduct the quick and effective coverage search for important regional targets in a real environment.