Scenario-based dynamic monitoring and early warning method for refined oil inventory in gas stations under the Internet of Things environment

Abstract

The invention belongs to the technical field of monitoring and early warning of inventories, and provides a method for dynamically monitoring and early warning the product oil inventory of a gas station based on a scene in an IOT environment. Early warning is realized through a system for dynamically monitoring and early warning the product oil inventory of the gas station based on the scene in the IOT environment; multiple dynamically changed situational factors related to the abnormal inventory can be comprehensively considered; furthermore, the current state and the future consumption trendof the product oil inventory scene of the gas station are sufficiently considered; and thus, an oil cut-off event can be prevented while the relatively low product oil inventory level of the gas station is kept.

Description

technical field [0001] The invention relates to a scenario-based dynamic monitoring and early warning method for refined oil inventory in a gas station under the Internet of Things environment, and belongs to the technical field of inventory monitoring and early warning. Background technique [0002] Refined oil is an important means of production and living. If the abnormal inventory of refined oil products at the gas station cannot be warned in time, it may lead to the occurrence of oil outages at the gas station, or even cause a chain reaction of oil outages at multiple gas stations, which will seriously affect social life and production order. [0003] At present, the abnormal monitoring and early warning of refined oil inventory in gas stations is generally carried out by dispatchers based on the actual gas station refined oil inventory data and manual experience of the gas station liquid level meter inventory monitoring system. Inventory monitoring and early warning p...

AI Technical Summary

Problems solved by technology

However, there are nearly 100,000 gas stations across the country, and the total safety stock at all of these stations combined is extremely expensive to store

The existing static and empirically-set early-warning threshold methods for refined oil inventories, like the inventory monitoring and early warning in most other fields, only judge whether the inventory level is abnormal based on the real-time read inventory, without taking Impact of scenario elements closely related to the rate of inventory depletion and the inventory replenishment process

For example, when the inventory level is low, if the inventory consumption rate is extremely slow, and the inventory replenishment vehicle is already on the road, and the remaining inventory is sufficient to cope with the arrival of the replenishment vehicle, even if the inventory level reaches the warning threshold, no warning is required; Conversely, sometimes the inventory level is high, but the inventory consumption rate is extremely high. If you wait until the threshold is reached before warning, it may be too late for replenishment

To sum up, it is unreasonable in many scenarios to perform static early warnings for inventory abnormalities based on the safety stock thresholds set in advance.

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