System and method for improving real-time estimates of visitor volume to places
OwnerCree Lawsoninventor
Life of this patent
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Abstract
The present invention is a system and method for improving the accuracy with which human behavioral insights regarding visitor volume to places can be predicted. The process aligns at least two different data sets and normalizes the information by removing statistical bias. In a particular implementation motor vehicle data is collected from a known subset of road-borne vehicles and compared to data collected from unknown vehicles. The data is then increased or discounted to remove biases present in the known subset. The system analyzes the normalized data and returns a report including predictions to a human user.
Claims12
A method for improving estimates of visitor volume to places, comprising:
- collecting a first data set in response to a first sensor triggering event comprising vehicle location data from one or more devices associated with occupants of a known motor vehicle, the first data set representing known characteristics of said occupants in a motor vehicle panel data set;
- collecting one or more second data sets in response to a second sensor triggering event comprising activating a geographically placed traffic sensor, the one or more second data sets representing characteristics of occupants of known and unknown motor vehicles;
- aggregating said first data set and at least one of the one or more second data sets into a data set comprising known and unknown vehicles;
- identifying a known, empaneled vehicle in the first data set and at least one of the one or more second data sets by comparing synchronized timestamps recorded with each first data set and one or more second data sets and labeling all other vehicles in said aggregated data set as not empaneled;
- calculating the presence of one or more statistical biases associated with said empaneled vehicles;
- normalizing the one or more statistical biases and producing a resulting data set comprising one or more results that apply to all vehicles within said aggregated data set;
- analyzing the resulting aggregated data set for human behavioral insights for all vehicles within said aggregated data set and providing a report upon said human behavioral insights to a user.
A system for improving estimates of visitor volume to places, comprising:
- a server with a processor in communication with one or more digital devices;
- said server collecting a first data set in response to a first sensor triggering event comprising vehicle location data from one or more devices associated with occupants of a known motor vehicle, the first data set representing known characteristics of said occupants in a motor vehicle panel data set;
- said server collecting one or more second data sets in response to a second sensor triggering event comprising activating a geographically placed traffic sensor, the one or more second data sets representing characteristics of occupants of known and unknown motor vehicles;
- said server aggregating said first data set and at least one of the one or more second data sets into an aggregated data set comprising known and unknown motor vehicles;
- said server identifying a known, empaneled vehicle in the first data set and at least one of the one or more second data sets by comparing synchronized timestamps recorded with each first data set and one or more second data sets and labeling all other vehicles in said aggregated data set as not empaneled;
- said server operative to calculate the presence of one or more statistical biases associated with said empaneled vehicles;
- said server normalizing the one or more statistical biases and producing a resulting data set comprising one or more results that apply to all vehicles within said aggregated data set and storing said results within an electronic storage element within said server;
- said server analyzing the resulting data set for human behavioral insights for all vehicles within said aggregated data set and providing a report upon said human behavioral insights to a user.
Dependencies are inferred from the claim text.