Method and system for scheduling operation and maintenance personnel based on internet of things (IoT) system for smart gas installation management

Patent metadata

Field	Value
Publication number	US-12530638-B2
Application number	US-202418587889-A
Country	US
Kind code	B2
Filing date	Feb 26, 2024
Priority date	Oct 14, 2022
Publication date	Jan 20, 2026
Grant date	Jan 20, 2026

Abstract

The embodiments of the present disclosure provide methods and systems for scheduling operation and maintenance personnel based on an Internet of Things (IoT) system for smart gas installation management. The method may include: obtaining user installation information of at least one operation and maintenance area; determining target installation information of the at least one operation and maintenance area; determining a door-to-door service plan for the at least one operation and maintenance area; obtaining collection data of a gas device configured in the operation and maintenance area; determining a count of on-call personnel of the at least one operation and maintenance area; determining a scheduling capability value of the at least one operation and maintenance area; determining a real-time scheduling instruction; and in response to compensation time off information, updating the scheduling capability value, and adjusting the real-time scheduling instruction.

First claim

What is claimed is:

1 . A method for scheduling operation and maintenance personnel based on an Internet of Things (IoT) system for smart gas installation management, wherein the Internet of Things system includes a smart gas user platform, a smart gas service platform, a smart gas operation management platform, a smart gas sensor network platform, and a smart gas object platform that interact in sequence, the smart gas user platform is configured as a terminal device, the terminal device includes a desktop computer, a tablet computer, a laptop computer, and a mobile phone, the smart gas service platform is a platform for receiving and transmitting data and/or information, the smart gas data center aggregates and stores all operation data of the IoT system for smart gas installation management, the smart gas indoor installation management sub-platform includes an installation requirement management module, an engineering plan management module, and a business tracking management module, the smart gas sensor network platform is configured as a communication network and a gateway, the smart gas object platform is configured as a gas device and a device related to implementation of installation engineering, the smart gas object platform includes a smart gas indoor installation engineering object sub-platform and a smart gas indoor device object sub-platform, the method is implemented based on the smart gas operation management platform, and the method comprises:
obtaining user installation information of at least one operation and maintenance area uploaded by the smart gas user platform through the smart gas service platform; determining, based on the user installation information and an acceptance condition, target installation information of the at least one operation and maintenance area, generating a personnel query instruction, and sending the personnel query instruction to the smart gas indoor installation engineering object sub-platform for execution, the personnel query instruction being used to obtain an operation and maintenance personnel scheduling condition of the at least one operation and maintenance area; processing historical service data, a historical operation and maintenance personnel availability degree, current building information, and a current count of operation and maintenance personnel using a distribution prediction model to determine distribution of a count of requirements per unit time and distribution of a count of services per unit time, wherein the distribution prediction model is a machine learning model, the distribution prediction model is obtained based on a plurality of first training samples with first labels, and a training of the distribution prediction model includes:
inputting the plurality of first training samples with the first labels to an initial distribution prediction model, constructing a loss function from the first labels and a result of the initial distribution prediction model, and updating parameters of the initial distribution prediction model iteratively based on the loss function by gradient descent, obtaining a trained distribution prediction model when a preset condition is satisfied;
the plurality of first training samples include the historical service data, historical building information, the historical operation and maintenance personnel availability degree, and a total count of historical operation and maintenance personnel over a historical time period; and
the first labels include an interval of the count of requirements in which an actual average count of requirements per unit time is located and an interval of the count of services in which an actual average count of services per unit time is located in the historical time period;
determining overall service intensity based on the distribution of the count of requirements per unit time and the distribution of the count of services per unit time, the overall service intensity referring to work intensity of the IoT system for smart gas installation providing a door-to-door service; based on the overall service intensity, adjusting a count of operation and maintenance personnel and updating the operation and maintenance personnel scheduling condition; determining, based on user requirement and an updated operation and maintenance personnel scheduling condition, a door-to-door service plan for the at least one operation and maintenance area, the door-to-door service plan including a door-to-door time, door-to-door personnel, and a door-to-door service content corresponding to the target installation information; determining, based on the target installation information and a historical comprehensive count of on-call personnel of the at least one operation and maintenance area, an important point and a secondary point of the at least one operation and maintenance area, as well as a first collection frequency of a gas metering device configured at the important point, and a second collection frequency of a gas metering device configured at the secondary point; wherein the important point is related to a target installation address corresponding to the target installation information, and the secondary point is related to other reporting location in the operation and maintenance area; obtaining collection data of the gas device configured in the operation and maintenance area uploaded by the smart gas indoor device object sub-platform through the smart gas sensor network platform, and determining a gas-related feature of the operation and maintenance area based on the collection data; determining a count of on-call personnel of the at least one operation and maintenance area based on the gas-related feature of the at least one operation and maintenance area, the target installation information, and the door-to-door service plan; in response to a determination that there is at least one operation and maintenance area satisfying a preset scheduling condition, constructing an area map based on relevant information of the at least one operation and maintenance area, wherein the area map includes a plurality of nodes and a plurality of edges, the nodes represent the at least one operation and maintenance area, and the edges represent a relationship between two connected nodes, features of each of the nodes include a count of on-call personnel of an operation and maintenance area corresponding to the node, features of each of the edges include a distance between two nodes connected by the edge and a weight value, the weight value is related to household features of the two nodes connected by the edge; determining an initial scheduling capability value of each of the nodes in the area map, performing a plurality of rounds of iterative update on the initial scheduling capability value, wherein when the scheduling capability value being updated meets a preset end condition, the update ends, a scheduling capability value of each of the nodes is obtained, the scheduling capability value reflects an ability to dispatch operation and maintenance personnel to other operation and maintenance areas, and the plurality of rounds of iterative update include: in a first round: determining the initial scheduling capability value of each of the nodes in the area map, and a scheduling capability value to be updated of each of the nodes is the initial scheduling capability value of each of the nodes in the area map; and in a t th round (t being larger than 1): updating the scheduling capability value to be updated of each of the nodes based on a preset algorithm, using an updated scheduling capability value of each of the nodes in the t th round as a scheduling capability value to be updated of each of the nodes in a (t+1) th round, wherein an updated scheduling capability value of a node in the t th round is determined based on an updated scheduling capability value of the node in the (t−1) th round, a change

Assignees

• Chengdu Qinchuan Iot Tech Co Ltd

Inventors

• Shao Zehua
• Zhou Junyan
• Wei Xiaojun
• Zhang Lei
• Li Yong
• Liang Yongzeng

Classifications

• G06Q50/06

  Energy or water supply · CPC title

• G16Y10/35

  Utilities, e.g. electricity, gas or water · CPC title

• G06Q10/20

  Administration of product repair or maintenance · CPC title

• G16Y40/10

  Detection; Monitoring · CPC title

• G06Q10/06315

  Needs-based resource requirements planning or analysis · CPC title