This Sensing System Can Constantly Track Workers’ Performances

Cooky - Jul 11, 2019


This Sensing System Can Constantly Track Workers’ Performances

A research team has recently made what they call “a mobile-sensing system,” which can classify low and high performers at work

A research team has recently made what they call “a mobile-sensing system,” which can classify low and high performers at work. Researchers used this system to track 750 workers in America in one year. This sensing system has a high degree of accuracy – up to 80%.

classify-high-low-performer
This sensing system has a high degree of accuracy – up to 80%

According to the researchers, the ultimate goal is to provide employees with insight into behavioral, physical, and emotional well-being. However, this constant data flow has a drawback. If the system is abused, employees can be put under ubiquitous surveillance carried out by their companies.

Andrew Campbell, a computer science professor at Dartmouth University, is a member of the research team. He used to work on an application to monitor students, which lays the foundation for this app to track employee performance. He considers this system an excellent gateway to boost worker’s productivity.

sensing-system-track-worker
Sensing System tracking workers all the time

Capture

The researchers stated thatunlike self-evaluations and interviews, which is possibly subjective,  this system can measure the performances of workers more objectively, generating more reliable results.

This sensing system, which has been invented by the research team, has three different pieces. The first one is a smartphone which can track location, physical activity, ambient light, and phone use. The second piece is a fitness tracker which is able to monitor sleep, heart functions, body measurements such as calorie consumption, weight, and also stress. In office and home, there are location beacons providing information about the amount of time for working and even breaking.

After that, Cloud-based machine learning algorithms will be used to categorize employees according to their level of performance.

The study says that great performers didn't use phones too regularly. They also had more physical activities and slept deeply.

great-performer-sensing-system
Great performers did not use their phone too often. They also had more physical activities and slept deeply for more extended periods of time

The use of this tech in monitoring workers has raised concerns to labor advocates as well as privacy experts. But companies don't stop incentivizing workers to wear fitness track as an exchange for benefits such as insurance savings. Furthermore, there have been more new ways to keep track of employees’ performances introduced by start-ups.

wework-bought-euclid
WeWork bought Euclid, a data platform tracking people’s behavior and identity in the real world

In February, WeWork bought Euclid, a data platform monitoring people’s behavior and identity in the real world. The chief product officer of WeWork - Shiva Rajaraman said that Euclid, as well as its team, was going to be integrated into a package of software analytics. WeWork intends to sell the package to companies which want WeWork system in their own offices but do not want to rent WeWork’s space.

The research team says that while the system that continuously monitors through other devices like wearables is not available at the moment but it could appear in the near future. However, it is still unclear whether it is a reasonable guess or if this system is designed to be tested and launched as a product.

18
Dartmouth University

The research team includes experts from Carnegie Mellon University, the University of Texas at Austin, Irvine, University of California, University of Colorado Boulder, University of Washington, Georgia Institute of Technology, University of Notre Dame, and led by Dartmouth University.

The study will be described in detail in a paper on the Proceedings of the ACM on Interactive of Mobile Wearable and Ubiquitous Technology.

Comments

Sort by Newest | Popular

Next Story