Intelligent electronic informatization management system based on smart city

Abstract

The invention discloses an intelligent electronic informatization management system based on a smart city. The system comprises a data acquisition unit, a smart city management analysis unit, an intelligent traffic management unit, an environment monitoring and governance unit, a smart energy management unit and a public security monitoring unit. The data acquisition unit is used for acquiring city data in real time; the smart city management analysis unit is used for preprocessing the city data and then correspondingly sending the city data to the intelligent traffic management unit, the environment monitoring and governance unit, the smart energy management unit and the social security monitoring unit. According to the invention, intelligent collection, integration and application of urban resources are realized, traffic management, environmental monitoring and governance, smart energy management and public security monitoring are integrated, optimal configuration of the urban resources, efficient provision of public services and fine management of urban operation are realized, and the urban operation efficiency can be improved.

Description

Technical Field

[0001] This invention belongs to the field of smart city technology. Specifically, this invention relates to an intelligent electronic information management system based on smart cities. Background Technology

[0002] The concept of a smart city originated in the media field. It refers to the application of intelligent computing technologies such as the Internet of Things, cloud computing, big data, and geospatial information integration in urban planning, design, construction, management, and operation. This makes key infrastructure components and services of a city, including urban management, education, healthcare, real estate, transportation, public utilities, and public safety, more interconnected, efficient, and intelligent. As a result, it provides citizens with better living and working services, creates a more favorable business environment for enterprises, and empowers governments with more efficient operation and management mechanisms.

[0003] In the prior art, patent application number CN202211142278.3 discloses a cloud computing-based smart city management system, including a smart city management agency and a cloud computing platform. The cloud computing platform includes a cloud computing acquisition module, a cloud computing processing module, and a cloud computing output module. The smart city management agency includes a city operation unit, a city planning unit, a city construction unit, and a city emergency unit. The city operation unit consists of a traffic management module and a waste management module. In the smart city management agency of this invention, the cloud computing processing module can promptly process and classify urban management information, calculate and summarize the updated information of various aspects of the city, and provide relevant urban data when statistically analyzing the changes in various aspects of the city at the end of the year. The spatial planning module uses grid-like photography of urban spatial areas and compares and calculates the number of people gathered in urban spatial areas in the past using the cloud computing platform, which facilitates the management of changes in urban agglomeration and the control of urban agglomeration.

[0004] The aforementioned patents, when used, limit the scenarios that smart cities can meet, and smart cities do not integrate resources. Therefore, this invention proposes an intelligent electronic information management system based on smart cities. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and proposes an intelligent electronic information management system based on smart cities to achieve the following objectives: intelligent collection, integration and application of urban resources.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: an intelligent electronic information management system based on smart cities, the system comprising a data acquisition unit, a smart city management and analysis unit, an intelligent traffic management unit, an environmental monitoring and governance unit, a smart energy management unit, and a public security monitoring unit; wherein:

[0007] The data acquisition unit is used to collect urban data in real time and send it to the smart city management and analysis unit. The urban data includes traffic data, environmental data, energy consumption data, and public security data. Preferably, the public security data includes data on the gathering of people on roads and facial recognition data.

[0008] The smart city management and analysis unit is used to preprocess the traffic data, environmental data, energy consumption data, and public security data and then send them to the intelligent traffic management unit, environmental monitoring and governance unit, smart energy management unit, and public security monitoring unit, respectively.

[0009] The intelligent traffic management unit is used to intelligently schedule traffic lights based on the traffic data;

[0010] The environmental monitoring and management unit is used to monitor urban environmental indicators based on the environmental data, and to issue timely warnings and alarms.

[0011] The intelligent energy management unit is used to intelligently regulate and optimize energy based on the energy consumption data.

[0012] The social security monitoring unit is used to monitor the city's security situation in real time based on the social security data, and to promptly detect and report abnormal behaviors. Specifically, the social security monitoring unit identifies abnormal clustering by constructing an anomaly clustering identification model; this model is a hybrid model based on convolutional neural networks and recurrent neural networks, wherein the input data is fed into the convolutional neural network to obtain a feature vector, and this feature vector is then fed into the recurrent neural network to obtain the model output.

[0013] Preferably, the traffic data includes traffic flow, road conditions, and bus arrival times on urban roads.

[0014] Preferably, the environmental data includes the city's air quality, noise level, and water quality.

[0015] Preferably, the energy consumption data includes urban electricity, gas, and water resource consumption data.

[0016] Preferably, the method for constructing the anomaly clustering identification model includes the following steps:

[0017] Step S1: Obtain image samples of people gathering in historical roads;

[0018] Step S2: Annotate the images of abnormal crowd gathering in the road crowd gathering image samples to obtain annotated road crowd gathering image samples;

[0019] Step S3: Construct an anomaly clustering identification model and train it using the labeled images of people clustering in the road. Use the trained anomaly clustering identification model for anomaly clustering identification.

[0020] Preferably, the intelligent traffic management unit intelligently schedules traffic lights based on the traffic data, including:

[0021] When the road traffic flow is less than or equal to the preset road traffic flow threshold, reduce the brightness of the traffic lights on the corresponding road.

[0022] When the road traffic flow exceeds the preset road traffic flow threshold, the brightness of the traffic lights on the corresponding road will be restored and maintained.

[0023] The technical effects of this invention are as follows:

[0024] This invention integrates traffic management, environmental monitoring and governance, smart energy management, and public security monitoring to achieve optimized allocation of urban resources, efficient provision of public services, and refined management of urban operations. It can not only improve the efficiency of urban operations but also optimize the quality of public services, enhance urban safety and emergency response capabilities, and promote sustainable urban development. Attached Figure Description

[0025] Figure 1 This is a structural block diagram of an intelligent electronic information management system based on a smart city, provided as an embodiment of the present invention. Detailed Implementation

[0026] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. This is to help those skilled in the art to have a more complete, accurate, and in-depth understanding of the inventive concept and technical solutions of the present invention, and to facilitate its implementation. It should be noted that the terms "first," "second," etc., used in this application are only for the convenience of describing the technical solutions and to distinguish components; the corresponding component configurations may be the same or different, and are not intended to limit the scope of this application. To make the technical solutions of the present invention clearer, the present invention will be explained and illustrated through the following embodiments.

[0027] This embodiment provides an intelligent electronic information management system based on smart cities, such as... Figure 1 As shown, the system includes a data acquisition unit, a smart city management and analysis unit, an intelligent traffic management unit, an environmental monitoring and governance unit, a smart energy management unit, and a public security monitoring unit; wherein:

[0028] The data acquisition unit is used to collect urban data in real time and send it to the smart city management and analysis unit. The urban data includes traffic data, environmental data, energy consumption data, and public security data.

[0029] The smart city management analysis unit is used to preprocess the traffic data, environmental data, energy consumption data, and public security data and then send them to the intelligent traffic management unit, environmental monitoring and governance unit, smart energy management unit, and public security monitoring unit, respectively. The preprocessing includes data cleaning and noise reduction to ensure data reliability.

[0030] The intelligent traffic management unit is used to intelligently schedule traffic lights based on the traffic data;

[0031] The environmental monitoring and management unit is used to monitor urban environmental indicators based on the environmental data, and to issue timely warnings and alarms.

[0032] The intelligent energy management unit is used to intelligently regulate and optimize energy based on the energy consumption data.

[0033] The social security monitoring unit is used to monitor the city's security situation in real time based on the social security data, and to promptly detect and report abnormal behavior.

[0034] Specifically, the traffic data includes traffic flow, road conditions, and bus arrival times on urban roads. Traffic flow refers to the flow of pedestrians or vehicles on the road, which can be collected using devices such as geomagnetic sensors, video cameras, and RFID readers; road conditions refer to factors such as road humidity and temperature, which can be collected using road sensors; bus arrival times can be calculated by using a GPS positioning system to track the real-time location of buses.

[0035] Environmental data includes urban air quality, noise levels, and water quality. Real-time monitoring and data collection are conducted using equipment such as air quality monitoring stations, noise sensors, and water quality monitors.

[0036] Energy consumption data includes urban electricity, gas, and water consumption data. This data is collected through metering devices such as smart meters, gas meters, and water meters.

[0037] Public security data includes data on the gathering of people on urban roads and facial recognition data. Specifically, high-definition cameras are used for video surveillance to collect data on the gathering of people on roads, and facial recognition technology is used to collect facial data.

[0038] After acquiring diverse urban data, the data acquisition unit sends it to the smart city management and analysis unit. The smart city management and analysis unit categorizes, summarizes, and stores this data. Furthermore, it performs preprocessing steps such as noise reduction and cleaning to improve data reliability, including threshold settings. Simultaneously, the preprocessing by the smart city management and analysis unit extracts features from traffic data, environmental data, energy consumption data, and public security data to facilitate subsequent data use. This includes extracting peak traffic flow and average speed from traffic data; extracting spatiotemporal distribution characteristics of pollutant concentrations from environmental data; extracting energy consumption characteristics from energy consumption data; and extracting population density characteristics from public security data. Finally, the smart city management and analysis unit sends the preprocessed data to the corresponding intelligent traffic management unit, environmental monitoring and governance unit, smart energy management unit, and public security monitoring unit.

[0039] The intelligent traffic management unit is used to intelligently schedule traffic lights based on the traffic data, optimize traffic flow, and reduce congestion. One scheduling method includes:

[0040] When the road traffic flow is less than or equal to the preset road traffic flow threshold, reduce the brightness of the traffic lights on the corresponding road.

[0041] When road traffic flow exceeds a preset traffic flow threshold, the brightness of the traffic lights on the corresponding road will be restored and maintained. In practice, the traffic flow threshold can be flexibly selected according to the actual situation.

[0042] In a preferred embodiment of the present invention, after receiving traffic data from the smart city management and analysis unit, the intelligent traffic management unit can use existing traffic flow theory, queuing theory and other models to perform real-time analysis of the traffic data, predict traffic congestion trends, and then use existing adaptive traffic signal control algorithms to dynamically adjust the timing scheme of traffic lights according to real-time traffic conditions, such as using fuzzy control, reinforcement learning and other algorithms to achieve intelligent scheduling.

[0043] The environmental monitoring and control unit is used to monitor environmental indicators such as air quality, noise levels, and water quality in the city based on environmental data, and to issue timely warnings and alarms. Specifically, after receiving environmental data from the smart city management and analysis unit, the unit uses a threshold comparison method to monitor the environmental data in real time. When the data exceeds a preset threshold, a warning or alarm mechanism is triggered. For example, when environmental data shows that PM2.5 in a certain area exceeds the standard (>75 μg / m³), the unit will issue a warning or alarm. 3 When the system is activated, the corresponding air purification equipment (HEPA filter + negative ion generator) will be automatically started, and the environmental protection department will be notified automatically via wireless communication technology, such as SMS or email.

[0044] The smart energy management unit is used to intelligently regulate and optimize energy consumption based on energy consumption data, thereby improving energy efficiency, reducing energy waste, and achieving sustainable development. Specifically, the smart energy management unit receives energy consumption data from the smart city management analysis unit, then uses existing data mining and machine learning techniques to analyze the data, identify energy usage patterns and abnormal consumption, and finally formulates energy regulation strategies based on the analysis results, such as adjusting equipment operating times and optimizing energy allocation schemes, to achieve intelligent energy regulation and optimization.

[0045] The public security monitoring unit is used to monitor the city's security situation in real time based on public security data, and to promptly detect and report abnormal behavior. Regarding abnormal gatherings of people on city roads, this embodiment's public security monitoring unit is equipped with an abnormal gathering identification model. Specifically, for images of abnormal gatherings of people that need to be determined, images of city roads taken by the data acquisition unit are sent to the abnormal gathering identification model to obtain results on whether there is an abnormal gathering of people on the road.

[0046] Specifically, the method for constructing the anomaly clustering identification model includes the following steps:

[0047] Step S1: Obtain image samples of people gathering in historical roads;

[0048] Step S2: Annotate the images of abnormal crowd gathering in the road crowd gathering image samples to obtain annotated road crowd gathering image samples;

[0049] Step S3: Construct an anomaly clustering identification model and train it using the labeled images of people clustering in the road. Use the trained anomaly clustering identification model for anomaly clustering identification.

[0050] In this embodiment, the anomaly clustering identification model is a hybrid model based on convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Input data is fed into the CNN to obtain feature vectors, which are then fed into the RNN to obtain the model output. This allows the model to extract both spatial features and capture temporal changes from the image. The CNN is responsible for spatial feature extraction, identifying pedestrians in the image, their location, density, and basic pose. The RNN is responsible for temporal modeling, inputting the feature vectors extracted by the CNN in chronological order. This enables the RNN to understand dynamic patterns of feature changes, such as whether the crowd is slowly gathering or suddenly surging in, or whether it is stationary or moving.

[0051] For example, when abnormal clustering needs to be identified, road monitoring video can be input into the abnormal clustering identification model trained in this embodiment, thereby intelligently identifying abnormal clustering situations and sending them to the public security monitoring unit. When the public security monitoring unit identifies abnormal clustering, it establishes communication with the cloud server through wireless communication technology, thereby the cloud server sends alarm signals to the mobile terminals of preset departments accordingly.

[0052] In summary, the data acquisition unit of this invention integrates multiple IoT sensors to achieve real-time, multi-dimensional, and high-precision acquisition of urban operational status data, including traffic, environment, energy, and public security. The smart city management analysis unit of this invention, as the core of the system, is not only responsible for data preprocessing but also serves as a hub for data classification and distribution. This enables subsequent specialized units to conduct in-depth analysis and decision-making based on high-quality data.

[0053] The intelligent traffic management unit of this invention effectively alleviates congestion and improves road traffic efficiency by dynamically optimizing traffic light timing. The environmental monitoring and management unit achieves automatic early warning and coordinated control by setting thresholds, improving the response speed and handling capacity for environmental risks. The intelligent energy management unit optimizes control strategies by analyzing energy consumption patterns, helping to improve energy utilization efficiency and promote energy conservation and emission reduction. The public security monitoring unit utilizes a trained anomaly aggregation identification model to achieve intelligent identification and early warning of anomaly aggregation situations, transforming passive response into proactive prevention.

[0054] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution; or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A smart electronic information management system based on smart city, characterized in that: The system comprises a data acquisition unit, a smart city management analysis unit, an intelligent traffic management unit, an environmental monitoring and management unit, a smart energy management unit, and a social security monitoring unit. The data acquisition unit is configured to acquire city data in real time and send the city data to the smart city management analysis unit, wherein the city data comprises traffic data, environmental data, energy consumption data, and social security data. The smart city management analysis unit is configured to preprocess the traffic data, environmental data, energy consumption data, and social security data, and send the data to the intelligent traffic management unit, the environmental monitoring and management unit, the smart energy management unit, and the social security monitoring unit, respectively. The intelligent traffic management unit is configured to intelligently dispatch traffic signal lights based on the traffic data. The environmental monitoring and management unit is configured to monitor city environmental indicators based on the environmental data, and timely issue early warnings and alarms. The smart energy management unit is configured to intelligently regulate and optimize energy based on the energy consumption data. The social security monitoring unit is configured to monitor the security situation of the city in real time based on the social security data, and timely discover and alarm abnormal behaviors. 2.The smart electronic information management system based on smart city according to claim 1, characterized in that: The traffic data comprises traffic flow, road conditions, and bus arrival time of city traffic roads. 3.The smart electronic information management system based on smart city according to claim 1, characterized in that: The environmental data comprises air quality, noise level, and water quality of the city.

4. The intelligent electronic information management system based on smart city according to claim 1, characterized in that: The energy consumption data comprises city power, gas, and water consumption data.

5. The intelligent electronic information management system based on smart city according to any one of claims 1-4, characterized in that: The method for constructing the abnormal gathering recognition model comprises the following steps: Step S1: obtaining historical road personnel gathering image samples; Step S2: labeling pictures of abnormal personnel gathering in the road personnel gathering image samples to obtain labeled road personnel gathering image samples; Step S3: constructing an abnormal gathering recognition model, training the model with the labeled road personnel gathering image samples, and using the trained abnormal gathering recognition model for abnormal gathering recognition. 6.The smart electronic information management system based on smart city according to any one of claims 1-4, characterized in that: The intelligent traffic management unit intelligently dispatches traffic signal lights based on the traffic data, which comprises: When the road traffic flow is less than or equal to a preset road traffic flow threshold, the brightness of the traffic signal lights on the corresponding road is reduced; When the road traffic flow is greater than the preset road traffic flow threshold, the brightness of the traffic signal lights on the corresponding road is restored and maintained. 7.The smart electronic information management system based on smart city according to claim 6, characterized in that: When the social security monitoring unit identifies abnormal gathering, it establishes communication with the cloud server through wireless communication technology, and the cloud server correspondingly issues an alarm signal to the mobile terminal of the preset department.

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