254 results about "Pedestrian flow" patented technology

The invention discloses an intelligent emergency and management and control method for a stadium, and belongs to the technical field of stadium safety management and control. According to the method, video stream data are collected through a monitoring camera array, and coverage areas of all cameras in the array have 15%-20% of overlapping areas; inputting the data into a pre-trained people density identification model to generate a real-time people flow distribution thermodynamic diagram; the retention index of each partition is calculated, and an emergency evacuation mode is activated in combination with a preset safety threshold value; in the emergency mode, the infrared sensor group monitors the instantaneous pedestrian flow speed, and an optimal evacuation path is generated by a dynamic path planning algorithm; the path is converted into a control instruction to drive an electromagnetic access control gate, emergency lighting and an electronic guide identifier, feedback data triggers a path re-calculation mechanism, and a two-dimensional code scanning device counts the number of evacuated people so as to start manual re-checking. Real-time situation awareness, dynamic risk assessment and intelligent evacuation guidance of the stadium are achieved, emergency response and evacuation efficiency is effectively improved, and crowd safety is guaranteed.

The invention discloses an optimal scheduling and safety early warning intelligent aid decision-making method based on tourist attraction people flow prediction, and the method employs an advanced machine learning model to carry out the people flow prediction through integrating historical tourist data, holiday and festival information and other data sources. Based on the prediction result, the dynamic resource optimization scheduling is realized, such as reasonable arrangement of workers, facility opening and traffic guidance, so that the tourist experience is improved. Meanwhile, a safety early warning mechanism is established, and when the predicted visitor flow rate exceeds a set threshold value, management personnel can receive a monitoring result in time, issue early warning information and start an emergency plan, so that the safety of tourists is ensured. The invention aims to improve the management level and service quality of the tourist attractions through an intelligent means, and is suitable for management and operation of various tourist attractions.

The invention belongs to the technical field of intelligent building energy management, and particularly discloses and provides a dual-mode cold storage air conditioning system based on human flow dynamic cooperative regulation, which comprises the following steps: acquiring dynamic human flow thermodynamic diagram data in real time, and accurately calculating a multi-region linkage cold load demand value based on a density change correlation coefficient and a heat conduction model; the real-time sensing of the flow density fluctuation and the dynamic refrigeration demand matching are realized; the phase change state of the coolant of the cold storage tank and the power consumption data of the refrigerating unit are collected in real time, the cold storage release proportion, the refrigerating power increment and other key parameters are dynamically adjusted, and the energy utilization rate is increased; the inherent defect of non-uniform cold and heat in zone control is overcome by calculating inter-zone cooling capacity migration parameters; temperature feedback data and a people flow thermodynamic diagram are collected in real time, the proportionality coefficient of the fan rotating speed and the air valve opening degree is dynamically adjusted, a closed-loop learning mechanism is formed, and the matching precision of a temperature control strategy and people flow distribution is continuously optimized.

The invention is suitable for the technical field of people flow density detection, and provides a scenic spot people flow density detection and early warning method and system, and the method comprises the steps: collecting real-time passenger flow data through an intelligent device disposed at a key node of a scenic spot; preprocessing the collected data and then constructing a multi-dimensional feature analysis model, wherein the multi-dimensional features comprise people flow composition features, behavior pattern features and environment coupling features; constructing a sample set based on feature vectors output by the multi-dimensional feature analysis model, outputting the sample set to a deep learning model to calculate a people flow density index, and triggering graded early warning when the people flow density index exceeds a first preset threshold value; generating multi-language voice early warning information according to the graded early warning, and performing regionalized broadcasting through directional sound field equipment; and when the people flow density index exceeds a second preset threshold value, generating a tourist shunting scheme including optimized path planning, thereby effectively improving the accuracy of people flow density detection and the timeliness of early warning.

The invention relates to the field of security inspection management, and particularly discloses a public place security inspection management system based on Internet of Things, which is characterized in that a plurality of fixed inspection nodes are arranged in a key inspection area according to public place types and layout identification, and the rationality of the arrangement of the fixed inspection nodes is ensured; each to-be-selected inspection route of the inspection equipment is formulated according to a fixed inspection node, a historical emergency location and current pedestrian flow distribution, and an optimal inspection route is screened according to an inspection coverage degree and an inspection equipment energy consumption evaluation index, so that the dynamic planning and adjustment of the inspection route of the inspection equipment are realized, and the inspection efficiency is improved; according to the method, video data and measurement data collected by fixed inspection nodes and inspection equipment are extracted, hidden danger points in a public place are identified and safety risk levels are evaluated and corresponding early warning is performed in combination with a safety event sample map library and an environment parameter range, multi-source data fusion is realized, and the judgment precision of safety risks in a complex scene is improved.

The invention provides an advertisement pushing method and system based on multi-modal data fusion. The method comprises the following steps: determining a user staying event of each position according to intensity peak value distribution of a user foot heat radiation signal of each position in continuous N time windows; performing frequency domain decomposition on the user foot heat radiation signals at the plurality of positions so as to extract a people flow density component and a staying time length component which are synchronous with a timestamp of a user staying event; calculating a discrete difference degree between the people flow density component and the staying duration component by adopting a variable coefficient method; and according to the discrete difference degree, adjusting a content playing queue of an advertisement screen in the offline commercial place, so that the playing content is matched with the commodity category corresponding to the shelf vertex. According to the technical scheme provided by the invention, the user staying event can be intelligently identified, the content of the advertisement screen is dynamically matched, precise commodity marketing is realized, and a consumption scene is adapted.

The invention relates to the technical field of pedestrian environment perception, and discloses a pedestrian floor tile environment perception method based on multi-modal fusion. The method comprises the following steps: acquiring a multi-mode sensing data sequence of pedestrian floor tiles in a preset monitoring area, wherein the multi-mode sensing data sequence comprises pressure distribution, a surface texture image and an environment temperature and humidity data sequence; then, combining a preset environmental parameter dynamic threshold value and target sensing area spatial characteristics, and screening a dynamic sensing target area through positive equilibrium relation matching, the former being pre-configured based on historical sensing data statistical distribution and a preset environmental anomaly judgment rule; the latter is calculated based on floor tile laying density, a pedestrian flow density peak value and an abnormal region thermodynamic diagram distribution range; dividing a plurality of continuous sensing time windows according to the boundary position of the target area and the multi-modal sensing node distribution topology; and finally, according to a window sequence, window sensing operation is completed in a gradual multi-source data fusion mode, and comprehensive sensing of the environment state of the pedestrian floor tiles is realized.

The invention discloses a processing method for dynamically adjusting a traffic light signal scheme according to traffic flow, which comprises the following steps of: deploying sensors including a ground induction coil, a camera and a pedestrian button at each traffic intersection, and preprocessing collected traffic flow and pedestrian flow data; and predicting trends of traffic flow, non-motor vehicle flow and pedestrian flow of each intersection in a short period, modeling traffic light states of each intersection into a dynamic system, calculating an optimal traffic light adjustment strategy, and adjusting the traffic light states in real time. By dynamically adjusting the traffic light signals, the system can more effectively respond to the actual on-site conditions including the flow of pedestrians and non-motor vehicles, more reasonable signal duration distribution is achieved, waiting time is shortened, traffic efficiency is improved, meanwhile, the pedestrians and the non-motor vehicles are considered, the safety of the system can be improved through an optimized signal control strategy, and the traffic light control method is suitable for popularization and application. The signal lamp is adjusted to provide more transition time for pedestrians and non-motor vehicles, so that the accident risk is reduced.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention relates to the technical field of intelligent traffic, and particularly discloses a pedestrian movement track prediction method and system based on visual information and a storage medium, and the method comprises the following steps: unmanned aerial vehicle data collection, coordinate projection transformation, coordinate sampling and track aggregation, sampling of pedestrian ground real coordinates after projection transformation, and tracking of the pedestrian movement track. Aggregating the coordinate data into trajectory information of a plurality of pedestrians; spatial visual information and time information are combined, a global interactive directed topological graph is constructed, then spatial feature and time feature extraction is performed, time sequence features of pedestrian motion are efficiently extracted through a multilayer convolution structure, and finally the future motion trail of pedestrians is predicted. Through the method, pedestrian motion in a complex scene can be predicted more efficiently, and the application effect of the model in pedestrian flow management and public safety planning is enhanced. The future movement condition is predicted by analyzing the historical trajectory of pedestrians, the pedestrian flow management is obviously optimized, and the safety level of public places is improved.

The invention relates to an advertisement putting and broadcasting system, and the system comprises a display module which is disposed outside a vehicle, and can dynamically update and display the advertisement content; the advertisement management server is used for storing, distributing and managing advertisement contents, communicating with a plurality of vehicle terminals, analyzing advertisement putting requirements and selecting proper vehicles to put the advertisement contents; the environment sensing module is used for collecting environment information of the position of the vehicle. According to the advertisement putting and broadcasting system, a linkage mechanism of the display module, the environment sensing module and the advertisement control module is arranged, so that the problem that the audience range of a traditional vehicle-mounted advertisement is limited is solved; the dynamic display screen outside the vehicle can expand the advertisement display range to the outside of the vehicle, the system can automatically match the advertisement content and dynamically adjust the playing strategy to greatly improve the advertisement reaching efficiency in combination with the data such as the people flow density and the geographic position collected by the environment sensing module in real time, and resource waste caused by blind putting is reduced.

The invention provides a V2X-based traffic situation early warning method, system and device, and the method comprises the steps: obtaining traffic data collected by a plurality of data sources, and carrying out the preprocessing of the received traffic data; corresponding traffic indexes are determined according to the preprocessed traffic data, and the traffic indexes at least comprise the vehicle pedestrian flow, the vehicle average speed and the lane traffic situation; wherein the lane traffic situation at least comprises a corresponding grade representing a road congestion condition in a preset time period, and the corresponding grade at least comprises one of unblocked, mild congestion, moderate congestion and serious congestion; and evaluating a corresponding traffic situation condition according to the traffic index, and if the traffic situation condition is abnormal, outputting corresponding risk early warning information. Through the real-time data monitoring technology, the urban traffic management efficiency is improved, the traffic jam problem is relieved, and the comprehensiveness and accuracy of information are ensured.

The invention relates to a pedestrian flow modeling and real-time simulation method, system and device and a medium, and the method comprises the following steps: carrying out the probability analysis of the moving direction of pedestrians in a railway platform environment based on a cellular automaton theory, and carrying out the modeling; based on the probability model of the pedestrian moving direction, according to the pedestrian decision-making process, modeling the pedestrian decision-making process by adopting a modeling method based on a multi-agent system; and simulating the pedestrian decision model by using an iterative vector quantization Q-Learning algorithm to obtain the overall distribution condition of the pedestrian flow for the next intelligent analysis of the digital twin system. The method can be widely applied to the computer and automation field and the railway video monitoring field.

The invention discloses a cruise path planning system and method for an intelligent shifting vehicle, and the method comprises the steps: collecting static and dynamic obstacle information in real time through a laser sensor, a monocular camera and a depth camera, and carrying out the processing through Kalman filtering, thereby obtaining precise obstacle information; a static path planning algorithm is adopted on a known map, and an initial path is found; historical pedestrian flow information in different time periods and seasons is collected, and the predicted pedestrian density on a specific route in a future period of time is analyzed by using a convolutional neural model; and optimizing path planning according to the predicted pedestrian density and the accurate obstacle information. Static and dynamic obstacle information in the environment is collected in real time through multiple sensors, Kalman filtering is used for data fusion and processing, historical pedestrian flow information is collected, deep learning analysis is carried out through a convolutional neural network, path planning is made to be based on current obstacle information, the pedestrian high density is predicted, and path planning precision is improved. Congested road sections are avoided in advance, and the perspectiveness and rationality of path planning are improved.

The invention relates to the technical field of direct-current lighting, in particular to a lighting method based on a direct-current lighting system, and the method comprises the steps: collecting a lighting area image of each street lamp at each moment in a rainy day and an ambient light intensity value at each moment; identifying umbrellas in the illumination area image to obtain umbrella areas in the illumination area image; key points of the umbrella areas are extracted based on the shape features of the umbrellas; determining detail richness and pattern contrast of each key point; constructing a feature descriptor of each key point, and determining a pedestrian flow evaluation value of each street lamp at each moment; determining the reflection intensity of each key point; the illumination area image at each moment is equally divided into image blocks, and the rain silk possibility of each image block is determined; screening feature image blocks in all the image blocks at each moment; determining the rain vigor evaluation intensity at each moment; and the brightness of the street lamp is adjusted by using a PWM (Pulse Width Modulation) dimming technology. The flexibility of street lamp illumination brightness adjustment is improved.

The invention discloses an urban intelligent street lamp control method and system. The method comprises the following steps: acquiring road environment parameters (PM2.5 concentration, humidity, environment illumination and SO2 concentration) and traffic state parameters (traffic flow, pedestrian flow, average lane speed and lane occupancy); constructing a brightness adjustment model and a color temperature adjustment model, performing combined weighting through an entropy weight method and an analytic hierarchy process, introducing a dynamic weight correction factor and fusing real-time wind speed data to perform diffusion compensation on SO2 concentration, and generating a brightness judgment value and a color temperature judgment value; and based on the judgment value, dividing a brightness adjustment level and a color temperature adjustment level, and dynamically adjusting the brightness and color temperature of the street lamp. According to the invention, fine adjustment of the brightness and the color temperature of the street lamp is realized, the scientificity, the accuracy, the real-time performance and the adaptability of the adjustment are improved, the street lamp illumination is ensured to meet the road illumination requirement, and the system can adapt to different traffic conditions and weather conditions.

The invention relates to the field of campus business management, discloses an AIoT-based campus business one-stop service system, and aims to solve the problems of low processing efficiency, serious information island, poor user experience, extensive energy consumption management and unintelligent equipment management of campus business in a traditional mode. An Internet of Things equipment integration unit of the system collects campus energy consumption, equipment state and people flow density data; the edge calculation unit preprocesses the data and identifies abnormity; the AI capability core unit provides natural language interaction and multi-modal analysis functions; the lightweight AI reasoning unit predicts equipment faults and gives maintenance suggestions; the dynamic model management unit realizes dynamic loading switching and framework expansion of multiple models; therefore, intelligent processing of campus business is realized, business processing efficiency is improved, information islands are broken, user experience is improved, energy consumption management is optimized, stable operation of equipment is guaranteed, and campus informatization management level is effectively improved.

The invention relates to an intelligent refrigeration area pedestrian flow and refrigeration power self-adaptive adjusting method which comprises the steps that temperature distribution data and pedestrian flow data are obtained from a sensor in a refrigeration area, and the external heat transfer amount is determined; according to the temperature distribution data and the external heat transfer amount, the inter-area cooling capacity distribution deviation is calculated, and the cooling capacity distribution proportion is determined; according to the cooling capacity distribution proportion, the fan air outlet angle and the air volume distribution proportion are adjusted, and an air volume distribution control signal is generated; according to the air volume distribution control signal, a cooling capacity delivery path is calculated, and the cooling capacity delivery direction is determined; according to the cooling capacity conveying direction and the regional cooling capacity distribution deviation, the compressor operation frequency and the air distribution proportion are adjusted, and cooperative control parameters are generated; and according to the cooperative control parameters, a cooling capacity distribution scheme is updated, a temperature uniformity index and a cooling capacity utilization rate are obtained, and a refrigeration efficiency index is determined.

The invention discloses an urban comprehensive park space-time network construction method and system based on crowd trajectory data. The method comprises the following steps: firstly, collecting, cleaning and dividing crowd trajectory data in a comprehensive park range; secondly, scenic spots in the comprehensive park are clustered, the number of optimal clusters is determined through clustering analysis, and all the clusters serve as all functional activity districts; then building a trajectory model through space projection and a shortest path algorithm, recovering a user moving trajectory path according to the crowd trajectory data, generating path node sequence data according to the timestamp of each trajectory point, and finally, taking the centroid of each functional activity area as each node of the space-time network, and combining each time period to obtain the user moving trajectory path. And constructing an undirected space-time network and a directed transfer network. The method has the advantages of efficient data processing, high modeling precision and perfect privacy protection, dynamic monitoring and space optimization analysis of the park people flow can be realized, and reliable data support and decision basis are provided for urban comprehensive park planning management.

The present invention relates to the field of store location recommendation, and discloses a store location recommendation method integrating multi-dimensional features, which includes the following steps: S10. Collect multi-dimensional data of the area where the candidate store location is located, and the multi-dimensional data includes: pedestrian flow, number of competing products, price, industry market size growth rate, regional planning trend, and consumer population change trend; S20. Preprocess the multi-dimensional data, including data cleaning and normalization processing; S30. Input the preprocessed multi-dimensional data into the store location recommendation model to obtain the recommendation value of each candidate store location; S40. After arranging the recommendation values of each candidate store location in descending order, obtain the store location recommendation sequence. The multi-dimensional data of the present invention is used for store location recommendation and fully considers various key factors affecting store operation, more comprehensively depicts the business environment of the candidate area, and thus can provide more accurate store location recommendations for stores, effectively improving the accuracy of location selection.

The invention discloses an emergency plan simulation method and system based on a digital twinborn technology, and the method comprises the steps: obtaining the physical parameters of a culture exhibition hall, the monitoring data of human traffic, and the environmental data; constructing a digital twinborn model of the cultural exhibition hall based on the physical parameters, and mapping the human traffic monitoring data into the digital twinborn model to obtain a target model; inputting the environment data into the target model to obtain a first parameter and a second parameter; according to the first parameter and the second parameter, determining a human traffic safety threshold value corresponding to each area in the cultural exhibition hall; when the human traffic of the target area exceeds a human traffic safety threshold corresponding to the target area, simulating an emergency scene through an artificial intelligence algorithm according to the human traffic of the target area and the target model to obtain a simulation result; and generating an emergency plan according to a simulation result. The emergency management efficiency can be improved.

The invention discloses a highway service area safety prevention and control method and system based on artificial intelligence, and relates to the technical field of highway service area safety prevention and control. Through an environment adaptive dynamic compensation mechanism, the problems of poor image quality, detail loss, high noise and the like under different light conditions are effectively solved, the details of the image are supplemented, and the image quality is improved; an image recognition detection algorithm is utilized to accurately record information such as pedestrian flow and vehicle types, and a reliable basis is provided for safety risk prevention and control; the vehicle circulation rate, the population circulation rate and the dangerous chemical risk degree are integrated to calculate the actual risk degree of the danger, and the potential risk of the service area can be comprehensively reflected, so that a scientific, reasonable and targeted safety risk prevention and control scheme is formulated. The speed reduction condition of the vehicle is monitored and reported in real time, the safety management efficiency of the service area is effectively improved, the accident rate is reduced, and safe operation of the expressway service area is guaranteed.

The invention discloses an unmanned aerial vehicle path planning method and system for a complex urban environment, and the method comprises the steps: collecting urban environment data, and obtaining the building distribution, public facility arrangement, average pedestrian flow and other information in a city; and respectively calculating an obstacle risk, an injury risk, a property loss risk and a weather influence existing in the urban environment, and finally obtaining a path of the unmanned aerial vehicle through an optimization algorithm. The method provided by the invention comprehensively considers the risks of obstacle collision, personal injury, property loss, weather influence and the like possibly caused by the operation of the unmanned aerial vehicle in the urban environment, is convenient to calculate, facilitates measurement or estimation of parameters, can quickly determine the path scheme of the unmanned aerial vehicle, and improves the working efficiency. Technical guarantee is provided for safe work of the unmanned aerial vehicle in a complex urban environment, energy conservation, improvement of the service life and improvement of the working efficiency.

The invention discloses a remote inspection method and system for stores, and relates to the technical field of remote inspection, and the method comprises the steps: determining the people flow state of each store according to the personnel distribution condition of a street sales area and the position of each store; the remote inspection system of the street sales area is determined according to the people flow state of each store, the position of each store and the area of the street sales area, and the accuracy of the remote inspection system of the street sales area is improved. In the remote inspection system, the abnormal area of the corresponding store is determined based on the remote inspection of each store, and the abnormal event of the store is determined according to the abnormal area and the store type of the corresponding store; the safety prevention and control area is determined based on the multiple abnormal events and the positions of the corresponding stores, and the corresponding safety prevention and control measures are determined based on the safety prevention and control area, the multiple abnormal events and the people flow states of the stores, so that the accuracy of the safety prevention and control measures is improved, and the remote inspection effect of the stores is ensured.

The invention discloses a library people flow monitoring method and system based on multi-mode and trajectory fusion. The method comprises the steps of collecting a video stream, generating a weight image by using an attention mechanism to enhance a pedestrian area, extracting a pedestrian frame through YOLOv11 target detection, and positioning a pedestrian subject and separating a background in combination with a segmentation model; feature points and descriptors are extracted through SuperPoint, inter-frame motion parameters are calculated through feature matching, and tracks are predicted and verified by means of Kalman filtering; and finally, associating pedestrian tracks through unique IDs, and dynamically tracking in and out states to count the pedestrian flow. According to the method, the problems of shielding, small target missing detection and track drifting are effectively solved, and high-precision people flow statistics is realized; more accurate and robust pedestrian detection and tracking are realized through multi-modal data fusion and dynamic trajectory fusion; through the schemes of feature point extraction, Kalman filtering and the like, the prediction of pedestrian motion trails is optimized, and the real-time performance and precision of pedestrian flow monitoring are improved.

The invention provides a scenic spot visitor flow control method and device, equipment and a storage medium. The method comprises the following steps: acquiring traffic flow data of each traffic device of a scenic spot at a target moment; wherein the traffic flow data is the total flow of people entering the scenic spot through traffic equipment at each moment before a target moment within a preset time period, and the target moment is determined according to an actual prediction moment; according to a preset first relational expression, the traffic flow data of each traffic device, the traffic flow data coefficient corresponding to the target moment and a preset second relational expression, determining a pedestrian flow time distribution curve expression of the to-be-predicted time; determining a human traffic prediction value of the to-be-predicted region corresponding to each moment in the to-be-predicted time based on the human traffic time distribution curve expression; and performing human traffic control according to the human traffic prediction value of the to-be-predicted area corresponding to each moment in the to-be-predicted time. According to the method, the precision of scenic spot visitor flow control is improved.

The invention discloses a composite pollutant control system for high-risk space and ground, and belongs to the field of public health, environment disinfection and pollution control. The system integrates a purification air duct, a module complex (comprising an ultraviolet disinfection module, a photocatalysis enhancement module, an induction module, a control system module and the like), a safety protection module and an ultraviolet reflection suppression module. The air flow direction of the purification air channel is adjusted according to the pedestrian flow time interval distribution characteristics in the pedestrian flow dense state. In a discontinuous pedestrian flow state, the low-pressure mercury lamp is started to effectively kill microorganisms on the ground and in the air, and the killing efficiency is improved in combination with the photocatalytic enhancement module. The sensing module monitors the approaching situation of people in real time, ensures that the ultraviolet lamp is immediately turned off when people exist, and guarantees safety. And the ultraviolet reflection suppression module adopts an ultraviolet absorption material on the ground to avoid ultraviolet reflection, so that the injury to personnel is reduced. The system controls air and ground composite pollutants under man-machine coexistence, and is suitable for environmental safety guarantee of high-risk complex scenes.

The invention relates to an ultra-large space pedestrian flow simulation system, and relates to the technical field of pedestrian flow management technologies, and the system comprises an autonomous decision behavior simulation module which simulates the behavior decision of pedestrians in a complex space, and the behavior decision comprises path selection, speed adjustment and avoidance behaviors; the environment sensing module is used for identifying obstacles, channel layout, exit positions and other environment characteristics in the space; the time period flow simulation module simulates pedestrian flow density and distribution in different time periods, and analyzes and optimizes configuration of various service facilities; and the visual display module is used for displaying a simulation result through a thermodynamic diagram, a traffic matrix and evacuation path tracking. According to the method, factors such as pedestrian behaviors, environmental perception and density are comprehensively considered, the optimal path is generated, pace is dynamically adjusted, congestion and collision are avoided, and meanwhile, the system senses environmental changes in real time and predicts the future flow trend through sensor data fusion and machine learning technologies.

The invention relates to a big-data-based real-time monitoring, regulation and control method and system for brightness of lighting engineering, and relates to the technical field of lighting engineering, and the method comprises the steps: transmitting the illumination intensity, people flow, traffic flow and weather data of a current lighting area to a cloud server; the cloud server inputs the illumination intensity, the pedestrian flow, the traffic flow and the weather data to an illumination demand prediction model; the illumination demand prediction model outputs an illumination demand prediction result; the cloud server obtains an illumination brightness regulation and control strategy based on the illumination demand prediction result and with energy saving as an optimization target; and the cloud server generates an illumination regulation and control instruction based on the illumination brightness regulation and control strategy and sends the illumination regulation and control instruction to a controller of the illumination equipment in the current illumination area so as to realize adjustment of the brightness of the illumination equipment.

The present invention discloses a 5G communication network base station node management system based on cloud computing, which relates to the technical field of communication networks and includes a distributed base station node cluster, a cloud resource computing unit, an edge computing unit, and a resource scheduling unit; by setting up a distributed base station node cluster, the present invention densely deploys 5G communication network base stations according to the demand assessment based on the pedestrian flow data and vehicle flow data in the distribution area to improve the total network capacity, obtains the operation data of all 5G communication network base stations within the regional scope, performs three-dimensional pooling management on the computing, storage, and spectrum resources of the base stations, and simultaneously constructs a traffic prediction model based on historical data to predict the resource requirements of real-time traffic. Based on the resource requirement values, computing, storage, and network resources are dynamically allocated to each base station node to obtain each communication resource link, the communication data of the corresponding base station nodes are obtained, and link transmission evaluation is performed based on the communication data to ensure the security and stability during the transmission process.