Location-based asset efficiency determination

Abstract

Methods, systems and apparatus, including computer programs encoded on computer storage media for determining asset efficiency. Unmanned Aerial Vehicles (UAVs) may be used to obtain aerial images of locations, property or structures. The aerial images may be geo-rectified, and a ortho-mosaic, digital surface model, or a point cloud may be created. In the context of an operation where mobile assets are used, such as construction or earth moving equipment, location-based event information may be obtained. The system determines efficiency clusters for particular assets, and provides an exploration interface to present and navigate via the efficiency cluster.

1 - 20 . (canceled) 
     
     
         21 . A method, comprising:
 generating a digital surface model of an environment in which one or more mobile assets are located using one or more images captured by an unmanned aerial vehicle; and   determining one or more structures within the environment as potential causes of the one or more mobile assets being idle based on a comparison of geo-spatial locations of the one or more mobile assets against the digital surface model.   
     
     
         22 . The method of  claim 21 , further comprising:
 outputting, to a display of a user device, a graphical user interface identifying the one or more structures as potential causes of the one or more mobile assets being idle.   
     
     
         23 . The method of  claim 21 , further comprising:
 determining a change to the one or more structures to reduce idleness of the one or more mobile assets.   
     
     
         24 . The method of  claim 21 , wherein the one or more structures are in a portion of the environment, and further comprising:
 predicting the portion of the environment from the one or more images captured by the unmanned aerial vehicle.   
     
     
         25 . The method of  claim 21 , wherein the one or more structures are in a first portion of the environment, and further comprising:
 determining a second portion of the environment that includes one or more features in common with the first portion of the environment.   
     
     
         26 . The method of  claim 21 , wherein the one or more structures are in a first portion of the environment, and further comprising:
 determining that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment.   
     
     
         27 . The method of  claim 21 , wherein the one or more mobile assets are associated with a cluster representation that represents a temporal-based idle amount for at least one of the one or more mobile assets. 
     
     
         28 . The method of  claim 21 , further comprising:
 navigating the unmanned aerial vehicle to capture the one or more images; and   using a photogrammetry process to associate the geo-spatial locations to one or more points about the one or more images.   
     
     
         29 . The method of  claim 21 , further comprising:
 outputting, to a display of a user device, a graphical user interface depicting the environment and idleness of the one or more mobile assets in the environment.   
     
     
         30 . A system, comprising:
 a memory; and   a processor configured to execute instructions stored in the memory to:
 generate a digital surface model of an environment in which one or more mobile assets are located using one or more images captured by an unmanned aerial vehicle; 
 compare a geo-spatial location of a subset of the one or more mobile assets against the digital surface model; and 
 determine, based on the comparison, one or more structures within the environment as potential causes of the subset of the one or more mobile assets being idle. 
   
     
     
         31 . The system of  claim 30 , wherein the processor is further configured to execute instructions stored in the memory to:
 output, to a display of a user device, a graphical user interface identifying the one or more structures as potential causes of the subset of the one or more mobile assets being idle.   
     
     
         32 . The system of  claim 30 , wherein the processor is further configured to execute instructions stored in the memory to:
 indicate a change to the one or more structures to reduce idleness of the subset of the one or more mobile assets.   
     
     
         33 . The system of  claim 30 , wherein the one or more structures are in a portion of the environment, and wherein the processor is further configured to execute instructions stored in the memory to:
 predict the portion of the environment from the one or more images captured by the unmanned aerial vehicle.   
     
     
         34 . The system of  claim 30 , wherein the one or more structures are in a first portion of the environment, and wherein the processor is further configured to execute instructions stored in the memory to:
 determine a second portion of the environment that includes one or more features in common with the first portion of the environment.   
     
     
         35 . The system of  claim 30 , wherein the one or more structures are in a first portion of the environment, and wherein the processor is further configured to execute instructions stored in the memory to:
 determine that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment.   
     
     
         36 . A non-transitory computer readable medium storing instructions operable to cause one or more processors to perform operations comprising:
 comparing a geo-spatial location of one or more mobile assets against a digital surface model of an environment in which the one or more mobile assets are located, wherein the digital surface model is generated from one or more aerial images obtained by an unmanned aerial vehicle; and   determining, based on the comparison, one or more surface structures within the environment as being potential causes of idleness for the one or more mobile assets in the environment.   
     
     
         37 . The non-transitory computer readable medium storing instructions of  claim 36 , the operations further comprising:
 outputting, to a display of a user device, a graphical user interface indicating a suggestion to modify the one or more surface structures to address the potential causes of idleness.   
     
     
         38 . The non-transitory computer readable medium storing instructions of  claim 36 , wherein the one or more surface structures are in a portion of the environment, the operations further comprising:
 predicting the portion of the environment from the one or more aerial images captured by the unmanned aerial vehicle.   
     
     
         39 . The non-transitory computer readable medium storing instructions of  claim 36 , wherein the one or more surface structures are in a first portion of the environment, the operations further comprising:
 determining a second portion of the environment that includes one or more features in common with the first portion of the environment.   
     
     
         40 . The non-transitory computer readable medium storing instructions of  claim 36 , wherein the one or more surface structures are in a first portion of the environment, the operations further comprising:
 determining that the one or more mobile assets will idle more in the first portion of the environment than in a second portion of the environment.