Planning Tools for Large Scale Location Tracking: Difference between revisions
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Client: | Client: Pete Steggles, [[Ubisense]] <Pete.Steggles@ubisense.net> | ||
Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines, storing measurements and derived locations 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. Your task is to use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations. | Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines, storing measurements and derived locations 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. Your task is to use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations. | ||
Latest revision as of 07:26, 23 January 2020
Client: Pete Steggles, Ubisense <Pete.Steggles@ubisense.net>
Our sensor system (https://www.ubisensedimension4.com) can be used to locate tools and cars on production lines, storing measurements and derived locations 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. Your task is to use the stored data to characterize these functions, compare them across sites, and build a planning tool to optimize future installations.
