Smart city big data analysis and monitoring system

Abstract

The invention relates to a smart city big data analysis and monitoring system. According to the system, the arrangement of monitoring equipment is fully considered, redundant networks are constructed,meanwhile, data transmission and processing need cooperation of a plurality of data centers, moreover, the local server has a data instant uploading function, so that the data transmission is diversified, the data processing efficiency is improved, shunting of data on a network structure is realized, shunting of different types of data is also realized, different data analysis models are adoptedfor different types of data, data analysis is carried out before the data is transmitted to a data center, the data processing efficiency is improved, and the reliability of exception processing is ensured, the reliable processing mode is formulated according to the collected data, and the vehicle-mounted equipment is informed in time, so that a vehicle owner can know the road condition in time, the alertness is improved, and the driving safety is improved.

Description

technical field [0001] The invention relates to the field of big data monitoring, and specifically relates to a smart city big data analysis and monitoring system. Background technique [0002] At present, with the development of smart cities, various types of data collection and processing are faced, which makes the data center have greater data processing pressure. Although there are various data processing mechanisms, the data processing is in the Monitoring is carried out at the data center, and then analysis and processing are performed according to the monitoring results, resulting in high pressure on the data center; at the same time, although multiple data centers are used in the prior art to distribute data, the processing of data by the data center is usually independent. Rather than cooperating with each other, the reliability of the processing method cannot be guaranteed. At the same time, the current data collection and upload are all transmitted through a spec...

AI Technical Summary

Problems solved by technology

[0002]At present, with the development of smart cities, various types of data collection and processing are faced, which makes the data center have greater data processing pressure, although there are various There are various data processing mechanisms, but the data processing is monitored at the data center, and then analyzed and processed according to the monitoring results, resulting in high pressure on the data center; at the same time, although multiple data centers are used in the prior art to process data The distribution of data, but the processing of data by the data center is usually independent, rather than mutual cooperation, and the reliability of the processing method cannot be guaranteed

At the same time, the current data collection and uploading are all transmitted through a specific transmission network. The transmission method is relatively simple and cannot be dynamically adjusted according to the actual data transmission situation. Moreover, it is difficult to ensure the accuracy and reliability of the data during the transmission process. sex etc.

Moreover, each sensor of the monitoring equipment is under long-term monitoring, and there is no good scheduling mechanism

[0003] In smart cities, monitoring data, especially traffic data, account for a relatively large proportion, and whether the monitoring data is comprehensive and effective, and whether it can achieve the purpose of monitoring is a problem that needs to be solved; at the same time, current monitoring data is usually used for evidence collection after the event , it is impossible to achieve timely early warning, especially in the current scene where there are many people and non-motor vehicles (electric vehicles), when the light is dark, accidents occur frequently, and timely early warning cannot be achieved. The current data monitoring and analysis is still It is impossible to make a reasonable early warning through the analysis of big data

Images