Planning Tools for Large Scale Location Tracking: Difference between revisions
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Creating Planning tools for Large Scale Location Tracking | Creating Planning tools for Large Scale Location Tracking | ||
Client: Ubisense | Client: Andy Ward, [[Ubisense]] <Andy.Ward@ubisense.net> | ||
This project uses large-scale data to optimize sensor networks. Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines (e.g. https://www.youtube.com/watch?v=6UBhGaxhORo). Measurements and derived locations are stored for audit purposes; every day each factory generates ~2e8 locations from ~1e9 raw measurements. There is an environment-dependent function from tag-to-sensor distance/bearing to sensor measurement probability/error, and an environment-independent function from a set of sensor measurements/errors to the probability of a ‘good’ tag location. You will use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations. | This project uses large-scale data to optimize sensor networks. Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines (e.g. https://www.youtube.com/watch?v=6UBhGaxhORo). Measurements and derived locations are stored for audit purposes; every day each factory generates ~2e8 locations from ~1e9 raw measurements. There is an environment-dependent function from tag-to-sensor distance/bearing to sensor measurement probability/error, and an environment-independent function from a set of sensor measurements/errors to the probability of a ‘good’ tag location. You will use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations. |
Revision as of 16:53, 8 November 2019
Creating Planning tools for Large Scale Location Tracking
Client: Andy Ward, Ubisense <Andy.Ward@ubisense.net>
This project uses large-scale data to optimize sensor networks. Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines (e.g. https://www.youtube.com/watch?v=6UBhGaxhORo). Measurements and derived locations are stored for audit purposes; every day each factory generates ~2e8 locations from ~1e9 raw measurements. There is an environment-dependent function from tag-to-sensor distance/bearing to sensor measurement probability/error, and an environment-independent function from a set of sensor measurements/errors to the probability of a ‘good’ tag location. You will use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations.