Measuring the Performance of Robots and the Data Derived from Them: Part 2

Author: | Category: General BI | Tags: using robots to automate data gathering; using robots to automate data analysis; measuring robot performance | Published: 10/23/2015

Measuring the Performance of Robots and the Data Derived from Them: Part 2

In my previous post, Measuring the Performance of Robots and the Data Derived from Them, I talked about how robots are increasingly used to perform tasks in many work environments, such as the airline, construction, and space industries. Despite sociopolitical and economic concerns, it’s a growing trend that results in new ways to think about how we capture data, analyze it, and measure productivity.

Along with certain operational tasks becoming automated, robots are also automating—or improving the efficiency of—data gathering and analysis from onboard sensors and high-resolution cameras.

Here are five examples:

  1. Unmanned aerial vehicles (UAVs), can collect data via sensors to monitor workflow, identify potential safety issues, and respond to emergencies.
  2. There are certainly many cases where it’s beneficial to automate data gathering with robots. The farming industry might use drones equipped with high-resolution cameras that pinpoint where pesticides should be sprayed, and subsequently use drones to spray. This targeted view obtained from data can reduce the overall use of pesticides, and spare workers from having to spray them.(1)
  3. Robots can also be used in search-and-rescue operations, bomb squads, and reconnaissance missions, where it can be dangerous or difficult to have a human on the scene monitoring the environment. With sensors attached to a robot in hazardous environmental conditions, the robot can survey the conditions and provide crucial information that might otherwise be impossible to obtain.
  4. Data sensors from robots and high-resolution cameras can be used for scanning and inspecting the surfaces of bridges. They can gather images and look for signs of degradation in ways and places that humans cannot. Data analysis algorithms can also be set up to detect cracks, for instance.(2)
  5. Remote-operated vehicles (ROVs) can be used in submarine rescues and in exploring the seafloor, where it can be impossible or dangerous for divers to get to. Through sonars and videos, these ROVs capture data and images, which can then be viewed on a screen onboard a ship.(3)

In addition to the above examples of automated data collection, automating or improving the efficiency of data analysis can also have payoffs. Employees can spend their time on other strategic areas and improvements. Human judgment should come into play in order to interpret, add context, and make intelligent decisions based on the data collection and analysis. In short, instead of humans being replaced, robots can reveal information that humans would find difficult or impossible to obtain. The idea is to enhance employees’ creativity and ability to do their jobs, not to take away from that capacity.

And as for any other type of worker, robotic performance should be regularly evaluated. Measuring the performance of a robot can take various forms including:

  • The speed to complete a task
  • The degree to which a robot falls behind the expected times
  • Expected quality of data acquisition compared to actual, both in terms of the nature of the data and the speed of acquisition
  • The degree to which a robot fails to perform a task in the manner expected

The use of robots to automate mundane, repeatable, or dangerous tasks is a reality. By harnessing these robots to improve on or automate data collection and analysis, the scope of human problem solving and decision making can be expanded, rather than replaced, in many creative ways.

Related resources

  1. Measuring the Performance of Robots and the Data Derived from Them
  2. Robotic Farming for the Future
  3. Data analysis and visualization for the bridge deck inspection and evaluation robotic system
  4. Remotely Operated Vehicle Jason/Medea
  5. Follow Pyramid Analytics on LinkedIn.
  6. Follow @PyramidAnalytics on Twitter.
  7. Subscribe to our blog's feed.

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