Verint Americas Inc.

Airviz Inc.

Carnegie Mellon University

Witness Systems, Inc.

Blue Pumpkin Software, Inc.

Other

Axxon Robotics, LLC

Axonn Robotics, LLC

Illah R Nourbakhsh

Serdar Uckun

Jason Fama

David Andre

Ofer J Matan

Michael Allen Taylor

Edward Hamilton

Joseph Watson

Joshua Schapiro

Tyler Morse

Simon Shvarts

Tiffany D Boehmer

Cheryl Hite

Edward Reusser

Gregory Fichtenholtz

Jeff Iannone

Michael Robert Bourke

H Benjamin Brown, Jr

Kevin Hegebarth

Scott Veach

Alex Fukunaga

Dömötör Gulyás

Carolyn O'Brien

Clay Kunz

Thomas Willeke

Vinton Coffman, Iii

Chris Bartley

Garth John Zeglin

Charles D Litton

Sara Longo

Christopher Bartley

David Litton

An air quality management system comprises a plurality of air quality sensors to sense air quality within a building, a plurality of air cleaning devices, and a computer system in communication with the plurality of air quality sensors and the plurality of air cleaning devices. The plurality of air quality sensors is located at a particular location within the building. The computer system determines a correlational model of air quality for the building that indicates a correlational relationship between the sensed air quality, a spatial parameter, a temporal parameter, and operation of the air cleaning devices. The computer system controls the plurality of air cleaning devices to implement an air quality control policy based on one or more air quality management parameters.

Proactive building air quality management

An optical-particle sensor head comprises an electromagnetic radiation source to transmit electromagnetic radiation toward the detection chamber; one or more baffles, between the light source and the detection chamber, to restrain a spread of the electromagnetic radiation from the electromagnetic radiation source; and at least two off-angle photo-sensors.

Optical-particle sensor head

A low energy particle detection device comprises alight source, multiple photodetectors positioned at different scattering angles, and a microcontroller for computing a total mass concentration of fine and ultrafine particles and a mass fraction of ultrafine particles to fine particles in an incoming air particle airflow based on the ratio of the readings from the multiple photodetectors. The optical particle detection device also can determine surface area concentration of the air particle sample and the associated lung deposited surface area (LDSA) to measure and improve estimates of air quality.

Low energy ultrafine particle detector

Computer-based systems and methods characterize indoor air quality in a particular building having multiple locations therein. The system comprises a back-end data center, at least one indoor air quality sensor located inside the particular building, and a graphical display device. The indoor air quality sensor(s) transmits time-stamped air quality readings collected by it to the data center via a computer network. The data center computes spatiotemporal air quality measures for the particular building based on the time-stamped air quality readings from the indoor air quality sensor(s) and transmits the computed spatiotemporal air quality measures to the graphical display device for display to the user/resident.

Home air quality analysis and reporting

Systems and methods collect time and location indexed (spatiotemporal) air quality measurements for an individual and aggregate those measurements to obtain cumulative air quality exposures for the individual that are presented to the individual with an interactive graphical display. A plurality of air quality sensors each transmits air quality data to the data center. The air quality sensors can comprise both indoor and outdoor air quality sensors. The data center stores the temporally-indexed user location information and the spatiotemporally-indexed air pollution information from the air quality sensors. Based on this information, it calculates user air quality exposure measures and transmits them to a graphical display device associated with the individual so that the individual can visualize his/her pollution exposure over time. Where the data center has information on the individual's activities at certain times, it can compute and display for the individual air quality exposure measures by activity type. The calculations can use a K-nearest neighbor algorithm to compute the individual's air quality exposures.

Data fusion for personal air pollution exposure

Systems and methods batch calibrate environmental sensors. Candidate environmental sensors and a high-performance reference sensor are located in an enclosure with a particle excitation system that controls the particle concentration in the enclosure. The calibration process includes multiple phases with different particle concentrations, and the candidate and reference sensors continuously report their particle counts to a calibration server during these phases. Based on the collected data, the calibration server: (i) identifies for removal candidate sensors with outlying behavior through statistical analysis; and (ii) computes calibration values for the particle count estimation algorithms for the remaining candidate sensors that are optimized to minimize the error relative to the reference sensor(s).

Group calibration of environmental sensors

Air quality sensor comprises an optical particle sensor and a programmable processor circuit. The optical particle sensor detects particles having a size of 10 microns or less in diameter in ambient air of the optical particle sensor. The programmable processor circuit continuously computes updated air quality measures for the ambient air using an estimation algorithm based on pulses in an output signal from the particle sensor over time, such as a cumulative particle density value and/or a cumulative particle weight value. The optical particle sensor may comprise a LED and accordingly detect particles based on reflection of light energy from the LED by particles in a chamber of the sensor.

Air quality sensor

Complex recording triggers are provided. As an example of a system and method, the volume of call records can be reduced by complex recording triggers, thereby reducing the storage space allocated for call records.

Complex recording trigger

A system and method for generating a schedule for multiple employees in a complex environment. In one embodiment, the method includes generating a schedule for multiple employees with varying skill sets for a time period, wherein the plurality of employees have varying overlapping skill sets that enable them to perform various tasks, and wherein employees are shared across tasks within the time period. In one embodiment, the method includes receiving a plurality of user inputs to a scheduling program, including a number of employee designations that each refer to a unique employee, and a number of skill sets that each correspond to one of the employee designations. The method further includes receiving a user input that changes the number of employee designations by indicating at least one changed employee, and estimating an effect of the at least one changed employee on effective staffing levels for each of the various tasks. The method further includes generating estimated effective staffing levels for each of the various tasks.

System and method for complex schedule generation

Systems and methods for scheduling call center agents are provided. An exemplary system for scheduling call center agents includes an agent computing device that is capable of obtaining quality scores of agents. The quality score is a measurement of quality that the agents provide to a call center. The Agent computing device is capable of transmitting the quality scores of agents over a network. The system further includes a manager computing device that is capable of: receiving the quality scores of agents over the network, receiving a scheduled interval, receiving a quality goal for the scheduled interval, the quality goal being a desired measurement of quality that the agents collectively provide to the call center, determining a quality goal for the scheduled interval based on the received quality scores of agents, and determining a schedule for the agents based on the quality goal, the quality goal score, and the scheduled interval.

Systems and methods for scheduling call center agents using quality data and correlation-based discovery

Systems and methods for visualization of call center performance are provided. An exemplary method includes the steps of: obtaining quality performance of agents data that includes information on the quality of service and quality characteristics of the agent, obtaining call center operations data that includes information on statistics and details of a call center, correlating the quality performance of agents data and the call center operations data, identifying correlation-based discovery, and optimizing call center performance based on the correlation-based discovery.

A method and apparatus for generating an agent schedule for a multi-contact center that has immediate queues and deferred queues. In one embodiment, a method includes scheduling software receiving a plurality of scheduling data from a user interface, and the scheduling software generating a plurality of scheduling constraints. The method further includes a search engine using the plurality of scheduling constraints to generate a plurality of potential schedules including first potential schedules for immediate queues, and second potential schedules for deferred queues. The method further includes performing a first analysis on the first potential schedules to generate first estimated service levels, and performing a second analysis on the second potential schedules to generate second estimated service levels, wherein the first estimated service levels and the second estimated service levels are expressed in interchangeable units.

Method and apparatus for multi-contact scheduling

A method and system for handling real-time indications of resource scheduling conflicts. In one embodiment, the method includes a computer system including a user interface, display, processor, and some form of memory. Contained within the memory is a resource scheduling process that analyzes resource data, scheduling criteria, and work parameters to create a working schedule. In conjunction with the creation of a working schedule, the scheduling process detects resource conflicts that can inhibit the schedule's functionality. Once detected an identification process conveys the error to the user concurrently with the schedule process to provide the user with a real-time indication of resource conflicts. The indication is presented in an unobtrusive manner so as to not interfere or impede the scheduling process. In addition, should the specific resource causing the conflict be identifiable, the indication process conveys that information in a similar real-time methodology.

Method and system for concurrent error identification in resource scheduling

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Pgh, PA, United States of America

Illah R Nourbakhsh