Off-line smart city front-end equipment fault reason feedback and pre-judgment method and system

Abstract

The invention discloses an off-line smart city front-end equipment fault reason feedback and pre-judgment method and system, and the method comprises the steps: carrying out the data collection and processing through employing a detector array, so as to obtain first data; constructing a second communication channel; sending first data through the second communication channel; performing first attempt communication processing; continuously carrying out the second time of attempt communication, the third time of attempt communication,..., and the n-th time of attempt communication, and respectively carrying out the second time of positioning operation, the third time of positioning operation,..., and the n-th time of positioning operation; sending the data packet to a server; enabling the server to call the electronic map to obtain a marked map; according to the method, generating the fault causes, and estimating the fault range, so timely fault cause feedback and pre-judgment are realized, and the first-hand detection data can be fed back at the first time to ensure stable operation of the smart city.

Description

technical field [0001] The invention relates to the field of computers, in particular to an off-line smart city front-end equipment fault cause feedback and prediction method and system. Background technique [0002] Smart cities rely on a large number of front-end devices. These smart city front-end devices collect a large amount of data through the preset detector arrays on them, and feed them back to the server to generate smart city decisions and realize the normal operation of smart cities. [0003] Among them, the smart city front-end equipment refers to the equipment installed on site or at the front end. Its core is a detector, and its existence forms are, for example, street lights, traffic lights, etc. The number of front-end devices in these smart cities is huge, and it is difficult to timely report the cause of failure and predict the problem, especially in the case of premeditated sabotage (the purpose of which is to prevent some behaviors from being sensed by s...

AI Technical Summary

Problems solved by technology

The number of front-end devices in these smart cities is huge, and it is difficult to timely report the cause of failure and predict the problem, especially in the case of premeditated sabotage (the purpose of which is to prevent some behaviors from being sensed by smart city front-end devices, for example), it is even more difficult Fault cause feedback and prediction

Therefore, the existing technology lacks a solution for timely feedback and prediction of fault causes, and feedback of first-hand detection data in a fault environment

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