US 12,284,318 B2
Method, internet of things system, and medium for smart customer service management of smart gas call center
Zehua Shao, Chengdu (CN); Yaqiang Quan, Chengdu (CN); Xiaojun Wei, Chengdu (CN); Bin Liu, Chengdu (CN); and Yuefei Wu, Chengdu (CN)
Assigned to CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Chengdu (CN)
Filed by CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD., Sichuan (CN)
Filed on Mar. 25, 2024, as Appl. No. 18/616,136.
Application 18/616,136 is a continuation of application No. 18/321,767, filed on May 22, 2023, granted, now 11,985,271.
Claims priority of application No. 202310432156.6 (CN), filed on Apr. 21, 2023.
Prior Publication US 2024/0236236 A1, Jul. 11, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04M 3/00 (2024.01); G06Q 10/0631 (2023.01); G06Q 30/015 (2023.01); G06Q 50/06 (2012.01); H04M 3/51 (2006.01); H04M 3/523 (2006.01)
CPC H04M 3/5232 (2013.01) [G06Q 10/06311 (2013.01); G06Q 30/015 (2023.01); G06Q 50/06 (2013.01); H04M 3/5183 (2013.01); H04M 3/5238 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for smart customer service management of a smart gas call center, wherein the method is performed by a processor of a smart gas management platform in an Internet of Things system for smart customer management of a smart gas call center, and the method comprises:
obtaining gas usage data, the gas usage data including at least a historical gas usage rate;
generating, based on the gas usage data, a predicted call feature of a smart gas call center within a target time period;
generating, based on the predicted call feature, at least one group of candidate seat features;
performing at least one round of iterative optimization on the at least one group of candidate seat features, and determining a preferred seat feature of the smart gas call center within the target time period from the at least one group of candidate seat features, the preferred seat feature including a count of customer services in each of one or more time periods within the target time period; wherein the iterative optimization includes: calculating an evaluation value of the at least one group of candidate seat features; and performing an elimination screening on the evaluation value, wherein the evaluation value is related to a gas business feature of at least one user type, and the gas business feature of the at least one user type includes a gas usage frequency and a gas calorific sensitivity; and
transmitting the preferred seat feature to a terminal of the smart gas call center.