Aggregating location data of a transaction device and a user device associated with a user to determine a location of the user

A device, comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, to:
• receive, from a transaction device, transaction data associated with a transaction performed by a user via the transaction device;
• receive first location data indicating a location of a mobile user device associated with the user;
• receive, from a stationary user device associated with the user, browser data associated with online activity of the user;
• determine second location data based on the browser data,
• wherein the second location data indicates a location of the stationary user device;
• determine third location data based on the transaction data,
• wherein the third location data indicates a location of the transaction device;
• assign a first weight to the first location data, a second weight to the second location data, and a third weight to the third location data;
• assign a first time stamp to the first location data, a second time stamp to the second location data, and a third time stamp to the third location data;
• aggregate the first location data, the second location data, and the third location data, based on the first weight, the second weight, the third weight, the first time stamp, the second time stamp, and the third time stamp, to generate aggregated location data;
• process the aggregated location data, with a machine learning model, to predict a particular location of the user at a particular time;
• receive, from a third-party user device, a query for the particular location of the user at the particular time;
• and
• provide, to the third-party user device and based on the query, information generally indicating the particular location of the user at the particular time without revealing the particular location to the third-party user device.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to:
• receive first location data indicating a location of a mobile user device associated with a user;
• receive second location data indicating a location of a stationary user device associated with the user;
• receive, from a transaction device, third location data indicating a location of the transaction device,
• wherein the user conducted a transaction via the transaction device;
• assign a first weight to the first location data, a second weight to the second location data, and a third weight to the third location data;
• assign a first time stamp to the first location data, a second time stamp to the second location data, and a third time stamp to the third location data;
• aggregate the first location data, the second location data, and the third location data, based on the first weight, the second weight, the third weight, the first time stamp, the second time stamp, and the third time stamp, to generate aggregated location data;
• process the aggregated location data, with a machine learning model, to predict a particular location of the user at a particular time;
• provide information identifying the particular location of the user at the particular time to the mobile user device and/or the stationary user device;
• and
• provide information generally indicating the particular location of the user at the particular time without revealing the particular location to a third-party user device.