Location intelligence is crucial to managing risk. WatchKeeper is using real time data feeds from a variety of different sources to monitor and mitigate risk and location is the thing that gives context to the data. In this interview, I talk with the founder of a company who has built a platform that ingests geospatial risk data feeds in real-time, applies rules-based decision-making to automate alerts on adverse events in close proximity to assets or employees and allows users to rewind and replay past events.
To put it simply, point clouds are a collection of XYZ points that represent some real world object of nearly any scale.They can be generated in a few ways. As geospatial scientists, we mostly work with LAS/LAZ data collected by aerial LiDAR (light detection and ranging) scanners at varying scales, from landscapes, down to project sites. We may also derive point clouds from highly detailed orthoimagery of an area, such as from the products of a drone flight.
As a data scientist, you don’t just go in and solve problems. You make recommendations to multi-faceted issues so that you get a fantastic model in the end. You’ll also be advocating a better use and understanding of the data while you do that.