Communications of the ACM
Researchers Devise More Effective Location Awareness for the Internet-of-(many)-Things
Researchers at Tufts University have developed an algorithm for localizing and tracking mobile devices that distributes the task among the devices themselves.
Credit: Tufts Now
Tufts University researchers have developed an enhanced algorithm for localizing and tracking mobile devices that distributes the task among the devices themselves.
This scalable solution could meet the demands of a projected 50 billion connected products that will comprise the Internet of Things by 2020, and would enable a widening range of location-based services.
The new method of distributed localization in a 5G network involves having the devices pinpoint themselves without every single device needing direct access to anchors. Sensing and calculations are conducted locally on the device, meaning there is no need for a central coordinator to collect and process the data.
The self-localization algorithm utilizes device-to-device communication, and therefore can work indoors, underground, underwater, or under thick cloud cover.
The researchers were able to simplify the self-localization process by substituting non-linear position calculations with a linear model that quickly and reliably converges on the accurate position of the device.
From Tufts Now
View Full Article
Abstracts Copyright © 2018 Information Inc., Bethesda, Maryland, USA
No entries found