38 results about "Urban dweller" patented technology

The invention discloses an urban inland inundation prevention and control method based on water conservancy dispatching and pipe network cooperation, belongs to the technical field of urban inland inundation prevention and control, and aims to solve the problem of poor inland inundation prevention and control effect caused by independent operation of water conservancy facilities and drainage pipe networks and lack of cooperation in the prior art. A monitoring sensing network is constructed, and multi-source data are collected in real time and transmitted to a data processing center; a waterlogging prediction model is established through data cleaning and fusion processing in combination with big data and machine learning; according to the prediction result and the real-time water regimen, a water conservancy facility scheduling scheme is made, and meanwhile a drainage pipe network real-time monitoring and scheduling system is built to achieve cooperation of the two; emergency response is triggered automatically when waterlogging occurs, and decision support is provided by using GIS and three-dimensional visualization technology; continuously optimizing each system and scheme through a feedback mechanism; the method breaks the situation of'respective politics', optimizes resource allocation, improves drainage system efficiency and waterlogging prevention and control capability, effectively prevents and relieves waterlogging disasters, and guarantees life and property safety of urban residents and normal operation of cities.

The invention discloses an urban resident working duration extraction method based on long-time-sequence mobile phone signaling data. The method comprises the following steps: preprocessing original mobile phone signaling data; based on speed, distance and time threshold values, user track resident point identification is carried out; the residence place and the activity residence point of the core worker are identified; extracting context features, space-time attribute features, geographic semantic features, user personal information and call information of activity residence points of core workers; training a working state discrimination model based on a random forest; and based on the random forest model obtained by training, extracting the working duration of the urban residents. The invention aims to reduce the acquisition cost of the used data, and can solve the problem that the current method cannot comprehensively analyze the working state and duration of residents in a city in a large scale.

The invention discloses a method, a system, equipment and a medium for calculating and tracing truck emission exposure based on resident activity distribution, and belongs to the technical field of environment and traffic, and the method comprises the steps: building a microscopic air diffusion model based on the emission data of a vehicle, and simulating the concentration distribution of each pollutant after diffusion; capturing activity tracks of residents, considering activity characteristics of urban residents, combining pollutant concentration data with crowd activity distribution information data, and calculating dynamic and static exposure levels of resident pollutants in unit grids within a preset time; and establishing a risk assessment model, assessing and analyzing influence factors of pollutant exposure and an action mechanism of the influence factors, and executing a space treatment strategy. According to the method, the influence of truck emission on resident health is accurately measured and traced by combining a microscopic air diffusion model and mobile phone signaling data. According to the method, the activity track of residents is captured by simulating pollutant concentration distribution, and the dynamic and static exposure levels of the residents are calculated.

The invention relates to the technical field of city management, in particular to a smart city evaluation AI analysis system and an evaluation method. Comprising a data acquisition processing module, a data storage management module, a data analysis mining module, an artificial intelligence machine learning module, a visual report generation module, a public service optimization module, a behavior event analysis module and an environmental health monitoring module. The data acquisition and processing module is used for data acquisition and data cleaning; according to the invention, the system achieves the real-time monitoring and decision support through automatic data collection and analysis, can automatically collect and analyze data in multiple aspects, achieves the real-time monitoring and evaluation of the urban operation state, provides timely and accurate decision support for managers, and improves the management efficiency. The effect of comprehensively reflecting the city happiness is achieved through multi-dimensional comprehensive evaluation, the system adopts a multi-dimensional comprehensive evaluation method, comprehensive evaluation is carried out from multiple aspects of environment, traffic, safety, health, education and the like, and the happiness level of city residents is comprehensively reflected.

The invention relates to the technical field of geographic information science and spatial data analysis, in particular to an urban human settlement built-up environment assessment method combined with multi-source heterogeneous geographic big data, and the method comprises the steps: carrying out the data preprocessing of target city social and environmental data of a target city, so as to generate a multi-source heterogeneous geographic database, determining a city built-up environment assessment sub-framework corresponding to a target assessment module of the built-up environment assessment system in the target city; and based on the city built-up environment evaluation sub-framework, constructing a multi-dimensional city human settlement built-up environment evaluation model, so as to input the pre-investigated city resident space position information in the target city into the multi-dimensional city human settlement built-up environment evaluation model, thereby outputting a city human settlement built-up environment evaluation result. According to the embodiment of the invention, the method can achieve the multi-dimensional evaluation of the built environment of the urban residents, and improves the real-time performance, comprehensiveness and scientificity of the evaluation of the built environment of the urban residents.

The invention relates to the technical field of mobile communication, in particular to an urban resident lifestyle identification method based on Wi-Fi handshake data. Wi-Fi handshake data of the mobile terminal are collected; based on the Wi-Fi handshake data, identifying visit events of an individual at different points of interest (POI), and forming a continuous visit sequence according to a time sequence; compressing the visited sequence, and extracting a long-term repeated high-frequency sequence mode; calculating the similarity between the users based on a high-frequency sequence mode, and obtaining a user group cluster with similar lifestyles through clustering; and performing feature analysis on each user group cluster, extracting a core visit sequence, and generating a lifestyle group portrait. Through the technical combination of Wi-Fi handshake data acquisition, sequence compression clustering and sample representativeness correction, comprehensive optimization of urban resident lifestyle identification on coverage integrity, result accuracy, implementation efficiency and cost control is realized, and high-quality data support is provided for urban related decisions.

The present application discloses a personalized MaaS solution design and recommendation method, including: obtaining historical travel information of residents in a target city, the historical travel information including travel attributes and attribute levels; based on the historical travel information, using a clustering algorithm to extract travel features to obtain the attribute levels of each travel attribute of different groups of residents in the city, wherein the group types of urban residents include positive, neutral and negative types; based on the attribute levels of each travel attribute of any group of urban residents, constructing a travel solution selection scenario for the corresponding group; obtaining the historical travel information of a target user, judging the group type to which the target user belongs based on the historical travel information of the target user, and recommending a corresponding travel solution selection scenario to the target user based on the group type to which the target user belongs. The present application can classify users into different feature types according to their travel habits, so as to provide users with accurate and personalized MaaS travel solutions.

The invention belongs to the technical field of urban planning, and discloses an urban resident potential activity space evolution feature extraction method and system, and the method comprises the steps: obtaining original mobile phone signaling data, carrying out the preprocessing to recognize key activity resident points, and obtaining a key activity resident point track queue; dividing the track queue into at least two activity periods according to a time period or an event inflection point, constructing a potential activity space measurement model for each activity period, and measuring to obtain a corresponding potential activity space; calculating scale indexes and shape indexes of potential activity spaces in different activity periods, and extracting overall evolution characteristics of the potential activity spaces of the urban residents; and performing space superposition analysis on the potential activity spaces of the adjacent activity periods, determining and quantifying reserved areas, lost areas and newly added areas of the potential activity spaces, extracting the procedural evolution characteristics of the potential activity spaces of the urban residents, and realizing accurate extraction of the overall and procedural evolution characteristics of the potential activity spaces of the urban residents.

The present application relates to the technical field of city management, and particularly relates to a city interest point co-location pattern mining method and device. The present application uses a topic model to identify city functional areas based on the mobile trajectory of city residents; in the case of a given city road network, each POI is projected onto the road network, the distance between POIs is calculated by finding a shortest connection path, and the distance is stored in a distance matrix to establish a network distance matrix between city POIs; based on the network distance matrix between POIs in the city road network, co-location pattern mining of POIs is carried out within various functional areas to identify co-location patterns. Compared with traditional co-location pattern mining, the present application takes into account the existence of spatial heterogeneity, and co-location pattern mining is carried out on the premise of functional area identification, which more comprehensively and accurately reflects the actual situation.

1. Name of the product in this design: Scooter (XF-A02). 2. Purpose of this design: As a short-distance transportation tool for urban residents. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The present application relates to the technical field of urban disaster emergency management, and particularly relates to an emergency shelter layout optimization method and system based on a multi-objective particle swarm algorithm, and the steps are as follows: obtaining geographic information data, constructing an emergency shelter site selection optimization model with the objectives of minimizing evacuation distance, minimizing construction and evacuation cost, and maximizing distance from disaster hidden danger points, and an emergency shelter capacity optimization model with the objective of maximizing emergency shelter capacity; using a multi-objective particle swarm algorithm to jointly optimize the emergency shelter site selection optimization model and the emergency shelter capacity optimization model to obtain a Pareto solution set; and obtaining an emergency shelter layout scheme based on the Pareto solution set. The present application can form optimal emergency shelter layout schemes with different preferences according to the combination of geographic spatial characteristics and urban resident evacuation needs, so as to improve the overall emergency efficiency and scientificity of resource allocation of emergency shelters.

The application provides a kind of based on remote sensing image's classification building roof photovoltaic potential estimation method and device, belongs to artificial intelligence field, including: building classification system for photovoltaic potential evaluation is constructed, for obtaining building classification information on remote sensing image, classification system specifically is: building is divided into color steel tile roof industrial and commercial building, concrete roof industrial and commercial building, urban residential house, rural residential house four categories;Four kinds of building corresponding building samples are made;Based on building sample, fine-tune instance segmentation pre-training model extracts the total area of four kinds of building roofs in the region to be measured;According to the total roof area of each type of building and the roof area to be developed, the total photovoltaic potential and the photovoltaic potential to be developed of each type of roof are evaluated, wherein the utilization coefficient is obtained from the roof with installed photovoltaic panels.

The invention discloses an online and offline convenient facility site selection optimization method based on a knowledge graph, and relates to the field of facility optimization site selection, and the method comprises the steps: generating an urban facility knowledge graph, employing a neural network to carry out the aggregation simulation of complex environment information in the urban facility knowledge graph, employing a binary logistic regression method, and carrying out the optimization of the site selection of the urban facility. According to consumption behaviors and feedback evaluation of urban residents in an online and offline retail platform, correlation between online and offline convenience facility high performance and urban environment factors is evaluated, positive and negative urban environment factors influencing high-performance convenience facility site selection are obtained, and a layout site selection rule of the facility is obtained through induction. And the layout recommendation system performs layout recommendation on the online and offline convenience facilities in a city domain range to obtain a layout recommendation result, and realizes layout optimization of the online and offline convenience facilities in a city. According to the method, the site selection rule of the high-performance facility can be scientifically extracted, and powerful support is provided for site selection of a new facility.

This invention discloses a method, medium, and device for analyzing the influencing factors of residents' green travel behavior. Based on the theory of planned behavior and interpersonal relations theory, the method constructs a comprehensive theoretical model of the influencing factors of urban residents' green travel behavior from a static perspective. Secondly, based on a survey of 817 residents in the Yangtze River Delta region, structural equation modeling is used to empirically test the driving mechanisms of different categories of green travel behaviors among urban residents. Furthermore, a social interaction perspective is introduced, and a simulation model is constructed based on scale-free networks and opinion propagation dynamics to simulate and analyze the group response characteristics and dynamic trends of residents participating in various green travel behavior decisions under different scenario parameters. Finally, targeted policy recommendations are proposed to more effectively promote urban residents' practice of green travel.

The device shown [Figure 1] transforms any type of waste bin (new or existing) by adding a magnetic anchoring system, thus preventing the bin from tipping over and consequently from scattering waste into the environment. This system allows bins to be anchored on public property. It guarantees that the bin remains upright, resisting inclement weather (wind and storms) as well as attempts to tip it over, for example, by animals. The system connects and disconnects solely through human action and manipulation. Once collection is complete, the bin is returned to its private location, leaving only the metal base plate in its casing on public property. This discreet and customizable base plate poses no risk to people with reduced mobility, pedestrians, or any other users of public spaces.This magnetic anchoring device for garbage bins, according to the invention, is intended to improve the comfort of city residents, garbage collectors, and sanitation and hygiene workers. It also represents an additional safeguard in environmental protection by preventing pollution from the dispersal of waste. (DRAWING)

The invention provides an urban lifeline pipe network burst prevention system and method based on an Internet of Things large model, and the method is executed based on an emergency supervision management platform, and comprises the steps: obtaining fluid pressure data; based on the fluid pressure data, the pipe explosion probability of the pipe network node is determined; and a target valve and the valve opening degree thereof are determined based on the pipe explosion probability, and the target valve is controlled to reach the valve opening degree. The system comprises an emergency supervision management platform. According to the method, the target valve needing to be controlled can be rapidly and accurately positioned, meanwhile, the opening degree of the target valve is accurately controlled, and the influence on water consumption of urban residents is reduced while the water pipe corresponding to the pipe network node is prevented from being burst.

The invention relates to the technical field of river dredging, and provides an urban river sludge resourceful treatment and intelligent dredging device which comprises a first data acquisition module, a second data acquisition module and a scheduling module. It is ensured that the dredging equipment can adapt to the actual working conditions of rivers and sludge, and the dredging operation efficiency is improved; on the other hand, a dynamic transportation route is generated according to the information of the second data acquisition module and the treatment plant and traffic road condition information, the problem of transportation route planning lag is solved, timeliness and high efficiency of sludge transportation are guaranteed, intelligence and high efficiency of the river dredging process are promoted, the ecological environment of the urban river is improved, and the urban river dredging system is suitable for popularization and application. And the living quality of urban residents is improved.

The present invention discloses a method for predicting electricity consumption of smart city residents based on hesitant generative adversarial networks, which belongs to the field of urban electricity consumption prediction. The steps include: constructing a generator and a classifier; constructing a training sample set; training the generator and the classifier; and using the trained generator for prediction. The present invention converts the original attribute value into a ternary attribute, and explicitly quantifies the uncertainty in the attribute data, so that the model can further explore the potential correlation between the uncertainty of the attribute itself and the predicted value while mining the correlation between the attribute and the predicted value, and update the model parameters during the training process through a loss function based on the consistency of hesitation preference, to ensure that the predicted data not only conforms to the correlation law between the attribute and the predicted value, but also has a degree of uncertainty similar to the actual data, thereby strengthening the data recognition and generalization capabilities of the model and reducing the dependence on data samples.

This application provides a method, apparatus, equipment, and readable storage medium for predicting per capita car ownership in cities, belonging to the field of data prediction technology. The method includes: obtaining per capita income of urban residents, the proportion of driver's license holders, and differences in transportation accessibility, wherein the differences in transportation accessibility represent the difference in transportation convenience between having a car and not having a car; determining the saturation level of urban private car ownership; using the per capita income of urban residents, the proportion of driver's license holders, and the differences in transportation accessibility to obtain a prediction factor, wherein the prediction factor is used to predict car ownership; and calculating the per capita car ownership in cities based on the saturation level of urban car ownership and the prediction factor. This prediction method has the advantages of low data requirements, ease of understanding, and scalability.

The utility model relates to the technical field of heating and cooling, and discloses an efficient energy-saving urban distributed heating and cooling system which comprises a supply side, a user side and a supply pipeline, and the supply side comprises a heat source system, a cold source system and a centralized control device and is used for supplying cold, heat and electricity in different modes. The heat source system comprises a high-efficiency gas turbine and a flue gas waste heat boiler, the high-efficiency gas turbine and the flue gas waste heat boiler are communicated to form a whole, the high-efficiency gas turbine and the flue gas waste heat boiler are communicated with a heating exchange device and used for providing a heat source for the whole system, and the heating exchange device is communicated with a centralized regulation and control device. By using the efficient energy-saving urban distributed heating and cooling system, the supply efficiency is improved, the energy is saved, the heating and cooling function requirements of urban residents in winter and summer are met, and meanwhile, the problem that the current city only has winter urban heating is solved.

The present invention belongs to the field of urban ecology and urban planning technology, specifically a method for assessing inequality in urban residents' exposure to green space. The method comprises: obtaining residential community data for the assessment area, POI data for urban green spaces and parks, and data on major urban parks; calculating accessibility based on the number of POIs for urban green spaces and parks within a specific buffer range, and normalizing the data; calculating accessibility based on the shortest path Di from residential areas to all major urban parks, and performing inverse data normalization; averaging the accessibility and accessibility data; plotting a Lorenz curve; and calculating the Gini coefficient, which is the Green Space Exposure Inequality Index (GEII). The method is service-oriented, user-friendly, and extensible, and it dispenses with complex evaluation indicators, making it operational. It is expected to be included in urban planning guidelines, pushing research on green space exposure inequality into practical urban planning. The method is of great value in alleviating inequality in urban residents' exposure to green space and scientifically optimizing landscape planning.

This invention relates to the field of water quality analysis technology, specifically to an online water environment monitoring system. This system includes acquiring and aggregating the directional indicators of ammonia nitrogen, total phosphorus, and pH values; identifying trend convergence zones; dividing transition segments and extracting trend features; screening cross-trend combinations; summarizing jump nodes and identifying interference points; marking directional mismatches and generating off-track combinations. In this invention, by continuously extracting changes in key indicators such as ammonia nitrogen, total phosphorus, and pH values, the direction of load changes and synergistic trends are identified. Further comparison of indicator fluctuation rhythms and jump nodes is conducted to extract pollution trend structures and directional mismatch combinations, effectively revealing potential abnormal segments and interference points. This enhances the depth of identification and temporal analysis capabilities of pollution dynamics during reclaimed water transportation. Consequently, urban residential water, after treatment to form reclaimed water, is delivered to industrial parks with stable and qualified water quality, providing more accurate and structured monitoring support for the compliance of industrial water quality.

The application discloses a city resident non-commuting activity destination selection method based on data fusion, comprising the following steps: based on mobile signaling data with activity destination labels, resident travel survey data, city POI data and city 500m*500m grid data, extracting activity attribute features and built environment features required for city resident non-commuting activity destination selection probability prediction; using multiple mathematical models to model city resident non-commuting activity destination selection probability prediction, and extracting an optimal model; putting the trained city resident non-commuting activity destination selection probability model into a non-commuting activity destination selection algorithm considering activity time constraints, and realizing non-commuting activity destination selection; the method provided by the application can not only make up for the limitation of time scale and coverage range in previous research, but also can more effectively control the future travel distribution structure of city residents, so as to provide more reliable city planning decision basis.

The invention discloses a wind and rain corridor device for preventing an outer wall from falling off and adjusting microclimate and a control method thereof.The wind and rain corridor device comprises a steel frame support fixed to the outer wall, the outer end of the steel frame support is connected with one end of a steel cable, and the other end of the steel cable is fixed to the portion, above the steel frame support, of the outer wall; a sunshade structure capable of being opened and closed is installed above the steel frame support, a protective net is installed above the sunshade structure capable of being opened and closed, and an environment sensor is further installed on the steel frame support. According to the method, the risks that the outer walls of the high-rise buildings fall off and objects fall from high altitudes are effectively prevented, the personal safety of urban residents and pedestrians is guaranteed, the microclimate quality of residential buildings can be improved, and a feasible technical path is provided for urban building safety and living environment improvement; and reference is provided for sustainable development directions such as environment friendliness, energy conservation and emission reduction of current buildings and related academic researches.

The invention relates to the technical field of traffic planning, in particular to a public traffic reachability evaluation method for setting resident trip points by utilizing ArcGIS, which comprises the following steps: firstly, establishing a resident trip fishing net model and a public traffic network model, and then combining a GIS spatial analysis tool and utilizing evaluation indexes to evaluate the resident trip points. Spatial calculation is carried out on the accessibility of urban residents to arrive at activity places by utilizing public transportation, and finally the change condition of the resident travel accessibility of the whole public transportation network is analyzed. According to the method, an ArcGIS space analysis tool is utilized, the change condition of traffic accessibility is evaluated and analyzed from the perspective of resident travel points, the defects of traditional traffic accessibility analysis are overcome, meanwhile, a faster and more convenient analysis way is provided for traffic accessibility analysis, finally traffic accessibility data are visually displayed, and the traffic accessibility analysis efficiency is improved. And the reachability data analysis efficiency is improved.

The invention relates to a technical scheme for additionally arranging fitness equipment by means of columns, beams and walls of parking lots of urban residential areas or teaching buildings of hospitals and schools and the fitness equipment. The fitness equipment comprises a hanging ladder, an iron rope bridge, a hanging ring bridge, a wall bar frame, a body swinging fitness device, a double-arm rocking / rowing scull type fitness device, a rocking windlass type fitness device, a double-linkage-rod fitness device, a traction fitness device, a hand racket target and the like. As overall optimization, part of commercialized fitness equipment can be installed in the free areas of the corners. According to the scheme, the problem that fitness sites are deficient is solved with the minimum investment, and fitness convenience is provided for urban residents, medical staff and school teachers and students.

This invention discloses a method and system for modeling urban residents' travel distribution based on deep learning. The method includes: obtaining a first OD matrix for urban residents' travel based on resident travel survey data, and obtaining a second OD matrix for urban residents' travel based on mobile phone signaling data; expanding the matrices using census data to obtain expanded first and second travel matrices; performing multi-dimensional verification on the expanded first and second travel matrices to obtain a third OD matrix; extracting the required features for modeling urban residents' travel distribution based on the third OD matrix and influencing factors of urban residents' travel; and modeling the distribution by combining traditional gravity models and deep learning-based travel distribution models using these required features, and finally establishing the model by considering a comprehensive evaluation index system. This invention improves prediction accuracy and provides a more reasonable decision-making basis for modeling urban residents' travel distribution.

The invention relates to a priori and data dual-guided urban resident activity intensity prediction method, and belongs to the technical field of spatial information. According to the method, multivariate function similarity is extracted on the basis of POI and a grid to serve as priori knowledge, and complementation with the priori knowledge is formed on the basis of similarity of historical data mining and learning data levels; the similarity of priori knowledge and historical data is used to guide a depth map neural network to learn a spatial dependency relationship, and a time convolutional network and an output layer are combined to predict the activity intensity of urban residents. The method has the advantages that (1) the prior knowledge of multivariate function similarity is deeply excavated to guide the model to focus on the relation between the grids which really exist in space dependence, and the precision of the model is remarkably improved; and (2) priori knowledge and data dual guidance is adopted, and the weights of priori knowledge and data are dynamically and adaptively adjusted through a fusion module, so that advantage complementation is realized, and the generalization performance of the method is enhanced.

We provide the system. [Solution] A device for measuring the user's biometric data, A device that receives information transmitted from a device, A server equipped with a computing device that analyzes received information and generates a motion plan, A means of displaying the generated exercise plan to the user, A means of sending user feedback to a server for analysis, Means of providing individualized exercise guidance to residents in an urban environment, A system that includes this.