196 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 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 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 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 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 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 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 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 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.

The invention discloses a traffic signal control system based on traffic flow prediction, and relates to the technical field of traffic signal control, and the traffic signal control system comprises an edge calculation unit which is deployed at each intersection and is used for bearing the following modules: a digital twin module which is used for providing data and topological information for a graph transformation flow prediction module; the graph transformation flow prediction module is used for carrying out combined prediction on the vehicle flow and the pedestrian flow of a plurality of adjacent intersections in the future 1-2 minutes through a multi-head self-attention mechanism and position coding; and the local twinborn simulation module is used for simulating short-term congestion, queuing length and average delay effect of various signal timing strategies in a second level by adopting a simulation time step length smaller than or equal to 5s. By designing an edge digital twinning and graph transformation prediction closed loop, short-time multi-intersection flow combined prediction is realized, the problems of high time delay, low prediction precision and single-intersection decision isolation in central cloud computing are solved, the prediction precision and response speed are improved, the communication delay is reduced, and end-side autonomous decision is realized.

The invention discloses a traffic safety early warning method for a pedestrian crossing and a related device, and relates to the technical field of intelligent traffic, and the method comprises the steps: carrying out the vehicle driving analysis through a radar echo signal based on multi-dimensional Fourier transform, and obtaining the vehicle driving information; performing face positioning and multi-layer filtering processing by using the plurality of frames of target images based on shielding analysis to obtain a target face set; based on the target face set, carrying out two-way people flow analysis to obtain two-way people flow data; performing pedestrian passing time prediction on the pedestrian crosswalk based on the two-way pedestrian flow data and the plurality of frames of target images; analyzing recommended driving information of the vehicle in the early warning area based on the pedestrian passing time prediction data and the vehicle driving information; and based on the recommended driving information, performing voice generation by using the voice token and rhythm analysis, and obtaining target voice information to perform passage early warning. According to the method, the recommended driving information of the vehicle can be accurately analyzed, so that more reliable passing early warning is provided for the vehicle and the pedestrian.

The invention discloses a self-adaptive control method and platform for an intelligent traffic signal lamp, and relates to the technical field of intelligent control, and the method comprises the steps: collecting traffic flow data in real time through a multi-source sensing module, including the number of vehicles, the vehicle speed, the vehicle type and the pedestrian flow; according to the data, traffic condition prediction is carried out by using a traffic flow model, and traffic pressure values of roads in all directions are calculated and generated; and based on the traffic pressure value, determining the phase duration of the signal lamp in each direction, performing signal lamp control analysis, generating a corresponding signal control instruction, and executing adaptive control of the traffic signal lamp. The technical problems of low traffic efficiency and serious traffic jam caused by the fact that the existing traffic signal lamp control method cannot dynamically adjust the time length of the signal lamp according to the real-time traffic condition are solved, and the purposes of dynamically optimizing the phase time length of the signal lamp and giving consideration to the requirements of pedestrians are achieved. The traffic efficiency is improved; and the congestion is relieved.

The invention relates to the technical field of traffic signal management, in particular to an intelligent traffic signal management regulation and control system based on machine learning, which comprises a memory, a processor and a computer program stored in the memory and running on the processor, when the processor executes the computer program, the following steps are realized: aiming at any phase of a target intersection at a to-be-predicted moment, acquiring at least one front intersection of the target intersection at any phase, and according to a possibility index of the traffic flow of each front intersection passing through the target intersection at the to-be-predicted moment, calculating the traffic flow of each front intersection; obtaining a traffic flow prediction value of any phase at a to-be-predicted moment, and obtaining a total flow prediction value by combining the traffic flow prediction value of any phase at the to-be-predicted moment; the total flow prediction value of each phase of the target intersection at the to-be-predicted moment is obtained, the green light duration of each phase of the target intersection at the to-be-predicted moment is dynamically regulated and controlled, the timeliness of traffic signal management is ensured, and the traffic jam problem is reduced.

The invention relates to a thermal exposure risk calculation method based on urban trip people flow and built environment dynamics, and the method comprises the steps: obtaining the average radiation temperature calculation input data of an urban environment, and calculating the average radiation temperature of the urban environment according to the average radiation temperature calculation input data; calculating general thermal climate index distribution of the urban environment based on the average radiation temperature, and determining a thermal exposure time period based on the general thermal climate index distribution so as to obtain thermal exposure duration according to the thermal exposure time period; and acquiring the hourly travel pedestrian flow of the urban environment, counting the accumulated travel pedestrian flow in the thermal exposure time period based on the hourly travel pedestrian flow and the thermal exposure time period, and calculating the thermal exposure risk according to the accumulated travel pedestrian flow. Therefore, the problems that in the related technology, due to dependence on static population data, the people flow dynamic state of urban day and night travel with high temporal-spatial resolution is difficult to reflect, and a thermal risk calculation result based on the static population data cannot meet the requirements of urban space environment exposure refined analysis and early warning are solved.

The invention discloses a vehicle path planning method and device, and the method comprises the steps: obtaining the future state prediction data and prediction environment data of a preset region, and obtaining the path data of a target vehicle in the preset region; performing fusion coding based on the future state prediction data and the path data to obtain a fusion feature vector; based on a preset geographically weighted regression model, the preset region and the fusion feature vector, performing people flow popularity prediction to obtain a people flow popularity prediction map of the preset region; and obtaining a current position and a destination position of the target vehicle, and performing path planning based on the current position and the destination position by using the people flow heat prediction map to obtain a driving route of the target vehicle. The problems that in the prior art, a cycle driving automobile scheduling method is used, the driving route of the automobile cannot be changed for coping with the accident, and the scheduling flexibility is low are solved.

1. The name of this design product: Hoisting Gate. 2. Purpose of this design product: used to manage pedestrian flow and regulate pedestrian entry and exit. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The invention provides a prediction model training method, a pedestrian flow prediction method and device, equipment, a medium and a program product, and relates to the technical field of big data, and the method comprises the steps: obtaining sample road network information and sample pedestrian flow information in a sample region; wherein the sample road network information comprises the adjacency relation of sample base stations in the sample area; the sample visitor flow information is used for representing the visitor flow in a sample base station range in a historical time period; inputting the sample road network information and the sample visitor flow rate information into an initial prediction model, and determining a first dependency feature of the visitor flow rates of sample base stations with different distances in pairs under the influence of public opinion types and a second dependency feature of the visitor flow rates of the sample base stations in different time periods under the influence of public opinion life cycles; and iteratively training the initial prediction model based on the first dependency feature and the second dependency feature, and stopping training until a preset training condition is met to obtain a preset prediction model.

The present invention discloses a method for detecting small targets of urban pedestrian flow based on a convolutional neural network. The image training dataset with detection frames of small portrait targets marked is subjected to Mosaic data augmentation and MixUp data augmentation. The augmented image training dataset is adjusted to the input picture size and input into the backbone network to obtain four kinds of feature maps of different sizes of the backbone network. The four kinds of feature maps are input into the feature fusion network BIAFPN for feature processing. The fused feature maps are respectively transmitted to their corresponding prediction heads, and after convolution in the classification branch and the regression branch respectively, they are connected along the channel part. Then the connected feature maps are stretched into one dimension, and then the stretched feature maps are connected to obtain the final feature map. The loss is calculated and backpropagation is carried out to update the network parameters, completing the training of the network. The present invention introduces shallow fine-grained features and then uses a feature fusion network to detect targets, which can effectively improve the accuracy of detecting small targets of urban portraits.

The application discloses a kind of crowd flow prediction method, device, electronic equipment and nonvolatile storage medium.Therein, the method includes: determining the grid area corresponding to target scenic spot, wherein the grid area includes grid unit, each grid unit corresponds a scenic spot in target scenic spot;According to the video image corresponding to grid unit, determine the crowd space-time parameter of target unit in grid unit in first time period;Using target model, according to crowd space-time parameter, obtain the crowd flow of target unit in second time period, wherein the second time period is the next time period of first time period.This application solves the technical problem that the related art can not specifically predict the crowd flow of each scenic spot in the scenic area when counting the crowd flow of tourists in the scenic area, only based on the data of the entrance guard of the scenic area, resulting in low crowd flow prediction accuracy and poor tourist experience.

The application discloses a traffic light control method and system, the traffic light control method comprises the following steps: determining a control mode, a pedestrian flow factor and a vehicle flow factor; determining a state parameter according to the control mode; determining control data according to the state parameter, the pedestrian flow factor and the vehicle flow factor; and controlling the traffic light according to the control data. Compared with the prior art, the application has the following beneficial effects: by determining the pedestrian flow factor and the vehicle flow factor, the control data of the traffic light can be dynamically adjusted according to real-time traffic conditions, the waiting time of vehicles and pedestrians can be reduced, the operation efficiency of the overall traffic system can be improved, traffic flow can be more effectively managed, and congestion can be reduced; by combining the control mode and the state parameter, the accuracy of determining the control data can be improved, the control of the traffic light is more refined, and the needs of different traffic scenes can be met.

1. Name of the Design Product: Graphical User Interface for Security Perception Evaluation and Control of Electronic Devices. 2. Use of the Design Product: For electronic devices. 3. Design Key Points of the Design Product: Lies in the graphical user interface. 4. Picture or Photo that Best Illustrates the Design Key Points: Front View of Design 1. 5. Design 1 is designated as the basic design. 6. Use of the Graphical User Interface: For traffic security perception evaluation and control of large-scale events. Clicking the function buttons in the interface in the front view of each design can achieve corresponding operations. For example, clicking "Pedestrian Flow" at the bottom can view pedestrian flow information. 7. The coated areas of Parts A, B, C, and D are the content screens, and X represents replaceable text.

The invention relates to the technical field of traffic regulation and control, and discloses an AI-based global traffic adaptive regulation and control method and system, and the method comprises the steps: determining the type of information needing to be collected for a target intersection based on a current date and a current time period, and collecting the multi-dimensional information of the target intersection based on the information type; and according to the multi-dimensional information of the target intersection and a traffic control AI model which is trained to converge in advance, generating a target traffic light control parameter for the target intersection, and executing a corresponding traffic light control operation based on the target traffic light control parameter corresponding to the target intersection. And the traffic flow congestion condition and the pedestrian flow congestion condition of the target intersection are slowed down through the adjusted traffic light. Therefore, the accuracy and the reliability of the traffic light control parameters can be improved, the traffic regulation and control accuracy, the reliability, the efficiency and the convenience of the intersection are further improved, and the vehicle driving smoothness and the road safety of the intersection and related roads are improved.

The invention relates to the technical field of computers, in particular to an equipment control method, electronic equipment, a computer readable medium and a program product. At least one electric device included in a target area of a building is determined through an electronic device, and device parameters of the electric device included in the target area are adjusted based on people flow data in the target area and / or weather data of an external environment. The current environment of the target area can meet the comfort requirement based on the adjusted electric equipment, and energy conservation and consumption reduction are achieved.