The Nielsen Comapny (us), LLC

Meryem Berrada

John Steven Stavropoulos

Ronny Lerch

John Zoldos

Alexander Pavlovich Topchy

Jeremey M Davis

Sandeep Tapse

James Petro

Robert Edward Taylor

James Anderson

Alan Lekah

Karem A Fernandez

Oscar Blanco

Holly McCoy

In one example, a method is described. The method includes: obtaining network traffic data characterizing network activity of devices coupled to a network at a media exposure measurement location, processing the network traffic data to generate, for each of multiple devices: activity parameters, each characterizing a network activity of the device, processing the activity parameters using an IoT classification model that includes a decision tree having: (i) multiple internal nodes, each internal node associated with an activity parameter threshold, and (ii) multiple leaf nodes, each leaf node associated with either the IoT device type or the other device type, based on the decision tree, selecting, from the device identifiers included in the network traffic data, a target device identifier corresponding to a leaf node in the decision tree that is associated with the IoT device type, and outputting the target device identifier.

Using network traffic data to identify internet of things devices

A method and system for media-exposure monitoring. An example method includes a computing system receiving digital query signature data representing a media content item presented at a panelist site. Further, the method includes the computing system identifying the media content item, with the identifying being based on matching of the received digital query signature data with reference signature data. Still further, the method includes the computing system determining a streaming-media service that streamed the identified media content item to the panelist site for presentation, with the determining of the streaming-media service including finding an intersection of (i) a first set of one or more streaming-media services known to offer streaming of the media content item and (ii) a second set of one or more streaming-media services to which the panelist site subscribes.

Use of credited content to deduce non-linear content source for monitoring media exposure

A system and method for attributing media-exposure to a particular media-delivery device, such as a media player, at a panelist site. An example system includes a first meter configured to detect media presentation by a media-presentation device at the panelist site, and a second meter configured to detect media transmission at the panelist site to the media-delivery device at the panelist site. Further, the example system includes program instructions stored in non-transitory data storage and executable by at least one processor to carry out operations including (i) correlating the detected media presentation at the panelist site with the detected media transmission at the panelist site to the media-delivery device at the panelist site and (ii) based on the correlating, associating the panelist media-exposure with the media-delivery device, such as by generating record indicating the association. This association may then be used as a basis to enhance audience ratings.

Tracking media-delivery-device in relation to media presentation and exposure

Methods, apparatus, systems and articles of manufacture to measure engagement of media consumers based on acoustic environment are disclosed. Example apparatus disclosed herein are to identify media device audio data and ambient environment audio data from sensed audio data collected from an environment, and determine classification data for the media device audio data and the ambient environment audio data. Disclosed example apparatus are also to process the classification data with a machine learning model to calculate an engagement metric. Disclosed example apparatus are further to determine whether at least one individual is engaged with media in the environment based on the engagement metric.

Engagement measurement of media consumers based on the acoustic environment

Methods, apparatus, systems, and articles of manufacture are disclosed to detect a presence status. An example apparatus includes media identification circuitry to generate first signatures representative of first audio data associated with a monitored media device, a comparator to obtain second signatures from a portable meter, the second signatures representative of second audio data sensed by the portable meter and compare the first signatures and the second signatures to determine a comparison result, presence detection circuitry to determine a presence status of a user based on the comparison result, the user associated with the portable meter, and network communication circuitry to transmit the presence status to a data processor to perform audience measurement based on the presence status.

Methods and apparatus to detect a presence status

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Clearwater, FL, United States of America

Meryem Berrada