Cornerstone OnDemand has been granted a patent for a method that enables the reproduction of vaping puffs using empirical data from multiple electronic vaping devices. The system collects reservoir configurations and operational parameters to generate vapors that mimic those produced during actual use by users. GlobalData’s report on Cornerstone OnDemand gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Cornerstone OnDemand, was a key innovation area identified from patents. Cornerstone OnDemand's grant share as of July 2024 was 36%. Grant share is based on the ratio of number of grants to total number of patents.
Reproducing vaping puffs using collected empirical data
The patent US12055532B2 outlines a method for reproducing vapor puffs from electronic vaping devices by utilizing empirical data collected during their use. The method involves receiving reservoir information, which indicates the configuration of a liquid reservoir, and operational parameters for each puff drawn by users. These parameters are measured by sensors within the vaping devices. The core of the method is to control an evaluation vaping device to generate vapors that closely mimic those produced by the original devices during actual usage. This is achieved by using the received data to adjust the operation of the evaluation device, ensuring that the reproduced vapors reflect the conditions under which the original puffs were taken.
Further claims detail the specific mechanisms for controlling the evaluation vaping device. This includes adjusting the heating element to convert liquid from the identified reservoir and establishing various operational settings based on the received parameters, which may include average or peak values. Additionally, the method allows for the introduction of the generated vapor into an analytical system to assess the chemical constituents present. Overall, the claims emphasize a systematic approach to replicating vaping experiences based on real-world data, enhancing the understanding of vapor characteristics and potentially informing product development and safety assessments in the vaping industry.
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