Network planning using mobile data collection devices and machine learning

A method for planning a utility network, comprising:

• deploying autonomous mobile data collection devices to a geographic area and causing the autonomous mobile data collection devices to collect data about the geographic area;
• determining, from the data about the geographic area, physical structures located in the geographic area;
• accessing address data for the geographic area, the address data specifying physical structures and locations of the physical structures, and determining whether physical structures located in the geographic area match physical structures specified in the address data for the geographic area;
• generating, from the data about the geographic area, a three dimensional model that represents the physical structures located in the geographical area, wherein the three dimensional model specifies deviations in the address data from the data about the geographic area collected from the autonomous mobile data collection devices;
• obtaining, at least from the data about the geographic area, data describing existing infrastructure on which components of the utility network can be installed;
• and
• generating, based on the three dimensional model and the data describing the existing infrastructure, a layout of the utility network using a trained network planning model.

A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising:

• receiving, from autonomous mobile data collection devices deployed to a geographic area, data about the geographic area collected by the autonomous data collection devices;
• determining, from the data about the geographic area, physical structures located in the geographic area;
• accessing address data for the geographic area, the address data specifying physical structures and locations of the physical structures, and determining whether physical structures located in the geographic area match physical structures specified in the address data for the geographic area;
• generating, from the data about the geographic area, a three dimensional model that represents the physical structures located in the geographical area, wherein the three dimensional model specifies deviations in the address data from the data about the geographic area collected from the autonomous mobile data collection devices;
• obtaining, at least from the data about the geographic area, data describing existing infrastructure on which components of the utility network can be installed;
• and
• generating, based on the three dimensional model and the data describing the existing infrastructure, a layout of the utility network using a trained network planning model.