CN-122022669-A - Food material inventory management method, device, equipment and medium based on time sequence data

CN122022669ACN 122022669 ACN122022669 ACN 122022669ACN-122022669-A

Abstract

The invention discloses a food material inventory management method, a device, equipment and a medium based on time sequence data, wherein the method comprises the steps of obtaining inventory time sequence data of food materials; the method comprises the steps of determining a data change point of inventory time sequence data, determining a front steady state data interval and a rear steady state data interval of the data change point in the inventory time sequence data, determining a front steady state data statistical value and a rear steady state data statistical value according to the front steady state data interval and the rear steady state data interval respectively, determining the change amount of food material inventory according to the front steady state data statistical value and the rear steady state data statistical value, updating the food material inventory according to the change amount of the food material inventory, and realizing automatic detection and quantification of food material inventory change, thereby reflecting actual consumption and supplement conditions of food materials in real time and accurately, helping users to accurately grasp real-time inventory level of the food materials, reducing food material expiration waste or influencing normal use conditions due to insufficient inventory, and bringing convenience to the users.

Inventors

OuYang Yaojin
LI SHAOBIN
WANG YUANZHAO
ZHEN ZHIJIAN
YANG FENGWEI

Assignees

珠海格力电器股份有限公司
珠海联云科技有限公司

Dates

Publication Date: 20260512
Application Date: 20251231

Claims (12)

1. A method for food material inventory management based on time series data, the method comprising: Acquiring inventory time sequence data of food materials; Determining a data change point of the inventory timing data; determining an preamble steady-state data interval and a subsequent steady-state data interval of the data change point in the inventory time sequence data; determining a preamble steady-state data statistic value and a subsequent steady-state data statistic value according to the preamble steady-state data interval and the subsequent steady-state data interval respectively; Determining the variation of the food material stock according to the preamble steady-state data statistic and the follow-up steady-state data statistic; And updating the food material stock according to the change quantity of the food material stock.
2. The method of claim 1, wherein determining a data change point of the inventory timing data comprises: filtering the inventory time sequence data to obtain filtered data; determining reference data of the inventory timing data according to the filtering data; and determining a data change point of the inventory time sequence data according to the filtering data and the reference data.
3. The method of claim 2, wherein determining a data change point of the inventory timing data based on the filter data and the reference data comprises: Comparing the reference data with each data point in the filtered data to determine at least one comparison result data; And taking the data points corresponding to the comparison result data which are larger than the preset change point threshold value as the data change points of the inventory time sequence data.
4. The method of claim 1, wherein determining a leading steady state data interval and a trailing steady state data interval for the data change point in the inventory time series data comprises: determining a first search window and a second search window according to the food materials; Determining an preamble steady-state data interval of the data change point in the inventory time sequence data according to the first search window; and determining a subsequent steady-state data interval of the data change point in the inventory time sequence data according to the second search window.
5. The method of claim 4, wherein determining a preamble steady state data interval of the data change point in the inventory timing data according to the first search window comprises: dividing a data interval before the data change point into at least one preceding data interval based on the first search window in the inventory time sequence data; Determining at least one preamble data statistic corresponding to the at least one preamble data interval; And taking the preamble data interval corresponding to the preamble data statistic value smaller than a preset steady state threshold value as a preamble steady state data interval.
6. The method of claim 4, wherein determining a subsequent steady state data interval of the data change point in the inventory time series data according to the second search window comprises: dividing the data interval after the data change point into at least one subsequent data interval based on the second search window in the inventory time sequence data; Determining at least one posterior data statistic corresponding to the at least one posterior data interval; And taking the subsequent data interval corresponding to the subsequent data statistic value smaller than a preset steady state threshold value as a subsequent steady state data interval.
7. The method of claim 1, wherein determining a preamble steady state data statistic and a following steady state data statistic based on the preamble steady state data interval and the following steady state data interval, respectively, comprises: carrying out statistical analysis on all data points in the preamble steady-state data interval to obtain preamble steady-state data statistical values; and carrying out statistical analysis on all data points in the subsequent steady-state data interval to obtain the subsequent steady-state data statistical value, wherein the preceding steady-state data statistical value and/or the subsequent steady-state data statistical value comprise at least one of a mean value, a median value or a truncated mean value.
8. The method of claim 7, wherein determining the amount of change in food material inventory based on the leading steady state data statistic and the trailing steady state data statistic comprises: And taking the difference value between the follow-up steady-state data statistic value and the preceding steady-state data statistic value as the variation of the food material stock.
9. The method of time series data based food inventory management according to claim 1, further comprising: after updating the food stock according to the variable quantity of the food stock, acquiring historical time sequence data and current time data of the food; and outputting inventory prompt information to a user according to the historical time sequence data, the current time data and the updated food material inventory, wherein the inventory prompt information comprises at least one of a consumption prediction report, a purchase suggestion and a historical consumption report of the food material.
10. A food inventory management device based on time series data, the device comprising: the time sequence data determining module is used for acquiring inventory time sequence data of the food materials; the data change point determining module is used for determining the data change point of the inventory time sequence data; The steady-state interval determining module is used for determining a preamble steady-state data interval and a follow-up steady-state data interval of the data change point in the inventory time sequence data; the data statistical value determining module is used for determining a preamble steady-state data statistical value and a subsequent steady-state data statistical value according to the preamble steady-state data interval and the subsequent steady-state data interval respectively; The change amount determining module is used for determining the change amount of the food material stock according to the front steady state data statistic value and the rear steady state data statistic value; And the stock determining module is used for updating the food material stock according to the change quantity of the food material stock.
11. An apparatus comprising a processor, a memory, and a program or instruction stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the time-series data-based food inventory management method of claims 1-9.
12. A readable storage medium, wherein a program or instructions is stored on the readable storage medium, which when executed by a processor, implements the steps of the time-series data based food inventory management method of claims 1-9.

Description

Food material inventory management method, device, equipment and medium based on time sequence data Technical Field The invention belongs to the field of food material inventory management, and particularly relates to a food material inventory management method, device, equipment and medium based on time sequence data. Background In the existing food material inventory management field, monitoring and updating of the quantity of the food materials often depend on manual recording or rough estimation, and it is difficult to accurately reflect the actual consumption and replenishment situation of the food materials in real time. In this way, the user is difficult to accurately grasp the real-time stock level of the food material, so that the food material is easy to expire and waste or normal use is influenced by insufficient stock, and inconvenience is brought to the user. Disclosure of Invention In view of the foregoing, embodiments of the present invention have been made to provide a method, an apparatus, a device, and a medium for food inventory management based on time series data, which overcome the foregoing problems in the existing food inventory management field, in which monitoring and updating of the amount of food is often dependent on manual recording or rough estimation, and it is difficult to accurately reflect the actual consumption and replenishment of food in real time, or at least partially solve the foregoing problems. In a first aspect, an embodiment of the present invention provides a method for food material inventory management based on time-series data, where the method includes: Acquiring inventory time sequence data of food materials; Determining a data change point of the inventory timing data; determining an preamble steady-state data interval and a subsequent steady-state data interval of the data change point in the inventory time sequence data; determining a preamble steady-state data statistic value and a subsequent steady-state data statistic value according to the preamble steady-state data interval and the subsequent steady-state data interval respectively; Determining the variation of the food material stock according to the preamble steady-state data statistic and the follow-up steady-state data statistic; And updating the food material stock according to the change quantity of the food material stock. Optionally, the determining the data change point of the inventory timing data includes: filtering the inventory time sequence data to obtain filtered data; determining reference data of the inventory timing data according to the filtering data; and determining a data change point of the inventory time sequence data according to the filtering data and the reference data. Optionally, the determining a data change point of the inventory timing data according to the filtering data and the reference data includes: Comparing the reference data with each data point in the filtered data to determine at least one comparison result data; And taking the data points corresponding to the comparison result data which are larger than the preset change point threshold value as the data change points of the inventory time sequence data. Optionally, the determining the preamble steady state data interval and the following steady state data interval of the data change point in the inventory time sequence data includes: determining a first search window and a second search window according to the food materials; Determining an preamble steady-state data interval of the data change point in the inventory time sequence data according to the first search window; and determining a subsequent steady-state data interval of the data change point in the inventory time sequence data according to the second search window. Optionally, the determining, in the inventory time sequence data, a preamble steady-state data interval of the data change point according to the first search window includes: dividing a data interval before the data change point into at least one preceding data interval based on the first search window in the inventory time sequence data; Determining at least one preamble data statistic corresponding to the at least one preamble data interval; And taking the preamble data interval corresponding to the preamble data statistic value smaller than a preset steady state threshold value as a preamble steady state data interval. Optionally, the determining, in the inventory time series data, a subsequent steady state data interval of the data change point according to the second search window includes: dividing the data interval after the data change point into at least one subsequent data interval based on the second search window in the inventory time sequence data; Determining at least one posterior data statistic corresponding to the at least one posterior data interval; And taking the subsequent data interval corresponding to the subsequent data statistic value smaller than a preset st