Abstract: A system for predicting injuries includes a plurality of sensors configured to generate sensor data and an apparatus having an input-output interface and a processor coupled to the input-output interface and wherein the processor is coupled to a memory, the memory having stored thereon executable instructions that when executed by the processor cause the processor to effectuate operations including receiving the sensor data, applying analytics to the sensor data, based on the applying step, predicting a likely injury, and transmitting a report based on the predicting step.

Abstract: A system for predicting injuries includes a plurality of sensors configured to generate sensor data and an apparatus having an input-output interface and a processor coupled to the input-output interface and wherein the processor is coupled to a memory, the memory having stored thereon executable instructions that when executed by the processor cause the processor to effectuate operations including receiving the sensor data, applying analytics to the sensor data, based on the applying step, predicting a likely injury, and transmitting a report based on the predicting step.

Abstract: A system for predicting injuries includes a plurality of sensors configured to generate sensor data and an apparatus having an input-output interface and a processor coupled to the input-output interface and wherein the processor is coupled to a memory, the memory having stored thereon executable instructions that when executed by the processor cause the processor to effectuate operations including receiving the sensor data, applying analytics to the sensor data, based on the applying step, predicting a likely injury, and transmitting a report based on the predicting step.

Abstract: Aspects of the subject disclosure may include, for example, determining a coverage area associated with an advertising display device, monitoring presence and motion of a plurality of communication devices with respect to the coverage area to determine a viewing time and a trajectory within the coverage area for each communication device, and associating each device with a user profile that comprises demographic data and preference data. Each user profile is assigned weighting factors based the viewing time and the trajectory for the associated device, thereby generating a weighted user profile for each of a plurality of users. The weighted user profiles are then aggregated to generate a time-dependent audience profile for the coverage area that is associated with an item of advertising content at the advertising display device. The audience profile is analyzed; a new item of advertising content can be selected and displayed. Other embodiments are disclosed.

Abstract: A system for predicting injuries includes a plurality of sensors configured to generate sensor data and an apparatus having an input-output interface and a processor coupled to the input-output interface and wherein the processor is coupled to a memory, the memory having stored thereon executable instructions that when executed by the processor cause the processor to effectuate operations including receiving the sensor data, applying analytics to the sensor data, based on the applying step, predicting a likely injury, and transmitting a report based on the predicting step.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: Aspects of the subject disclosure may include, for example, determining a coverage area associated with an advertising display device, monitoring presence and motion of a plurality of communication devices with respect to the coverage area to determine a viewing time and a trajectory within the coverage area for each communication device, and associating each device with a user profile that comprises demographic data and preference data. Each user profile is assigned weighting factors based the viewing time and the trajectory for the associated device, thereby generating a weighted user profile for each of a plurality of users. The weighted user profiles are then aggregated to generate a time-dependent audience profile for the coverage area that is associated with an item of advertising content at the advertising display device. The audience profile is analyzed; a new item of advertising content can be selected and displayed. Other embodiments are disclosed.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.