112 results about "Occupancy rate" patented technology

The invention relates to the technical field of charging parking space guiding control, and particularly discloses a parking space charging reservation and intelligent guiding method, device, equipment and medium, and the method comprises the steps: obtaining vehicle battery state data and a user reservation time window through an Internet of Things terminal; synchronously acquiring charging pile state data, real-time traffic flow data and power grid load information in the parking lot; fusing the obtained multi-source heterogeneous data based on a federated learning framework, constructing a dynamic charging demand prediction model, and predicting charging pile occupancy rate distribution in a preset time period by using a space-time diagram convolutional network; through the combination of the dynamic charging demand prediction model and the space-time diagram convolutional network, the occupancy rate distribution of the charging piles is accurately predicted, the scheduling strategy of the charging piles is adjusted in real time, the problem of unreasonable resource allocation is avoided, and the waiting time of a user is shortened; the application of the quantum genetic algorithm optimizes the matching process of the charging pile through global optimal solution search, thereby ensuring the balance of the power grid load and the rationality of the charging strategy.

The invention belongs to the field of computer operating systems, and aims to provide a computing resource allocation method, system and equipment for a multi-core system and a medium. According to the method, the computing resources with the specified size are divided to serve as the reserved computing resources, the specified computing resource occupancy rate of each service in the multi-core system is calculated, and when the specified computing resource occupancy rate of any service is larger than the computing resource occupancy rate threshold value, certain computing resources are allocated to the service in the reserved computing resources. And normal operation of the business is facilitated. Based on the method and the device, each service can occupy the reserved computing resources according to the own specified computing resource occupancy rate, so that the jitter of other services caused by overhigh sudden specified computing resource occupancy rate of one service can be prevented, and the problem of mutual interference among the computing resources of the services is further avoided; and the stability of the multi-core system is improved.

The invention discloses a multi-motor scheduling method and system applied to a pipe rail logistics system, and relates to the technical field of conveyors for transportation, and the method mainly comprises the steps: constructing a forward following topological structure, and constructing a speed control cost function based on the forward following topological structure; by introducing a path complexity penalty term, constructing a heuristic estimation cost function under pipe track selection guide optimization on a target fixed track topological structure; constructing a resource occupancy conflict cost function used for evaluating the occupancy rate of the pipe rail section; constructing a dynamic priority total cost function according to the heuristic estimation cost function and the resource occupation conflict cost function in combination with the actual path time cost of the current logistics vehicle from the starting point to each node, and endowing the current logistics vehicle with a dynamic priority at each path node; and controlling each linear motor to drive the current logistics vehicle to adjust the speed by solving the speed control cost function. According to the invention, through dynamic weight coefficient adjustment and closed-loop feedback control, the method adapts to a complex logistics scene.

The invention relates to the technical field of equipment scheduling, and discloses a dynamic resource priority intelligent allocation method based on an equipment scheduling system, which comprises the following steps: S101, acquiring equipment state data and resource state data; s102, the tasks are classified, and task emergency degrees are obtained through calculation; s103, calculating a resource popularity index in combination with the idle degree of each field execution resource and the moving average occupancy rate in the sliding time window; s104, calculating to obtain a space-time potential energy value based on the shortest feasible path distance between the task and the field execution resource, the resource popularity index and the current accumulated waiting time; s105, constructing an adaptation degree matrix according to the task emergency degree, the resource popularity index and the space-time potential energy value; and S106, executing optimization operation to obtain a final allocation result of the task and the field execution resources. According to the method, intelligent matching of tasks and resources under multi-factor driving is realized, and the scheduling efficiency and the system response capability are remarkably improved.

The invention discloses an airport terminal air conditioning system double-layer optimization control method considering passenger flow space-time performance, and belongs to the field of air conditioner multi-area control. According to the method, a regional heat and humidity balance model and an air quality model which consider the passenger occupancy rate are constructed by dividing the functional regions of the terminal building. Based on a Markov chain and event passenger movement model, a transition probability matrix is utilized to describe the flow condition of passengers in each area, an occupied area and an unoccupied area are divided, and a differential control strategy is implemented for the areas with different occupied states. Compared with a traditional control strategy, a dynamic partition control mechanism is introduced, the problems of local pollutant accumulation and heat and humidity environment imbalance caused by uneven passenger flow distribution are effectively solved, the operation energy consumption of the air conditioning system is remarkably reduced, the balance of energy efficiency and comfort is achieved, and a new technical path is provided for optimization of the air conditioning system of the terminal building.

The invention discloses a hotel environment governance intelligent evaluation method integrating ESG indexes, and relates to the technical field of hotel environment monitoring, and the method comprises the following steps: collecting multi-source environment data in real time, and obtaining hotel data and guest room check-in information by deploying Internet of Things sensing equipment and docking with an existing hotel management system; based on the obtained guest room check-in state information, the number of check-in rooms is counted according to set time slices, and the real-time check-in rate of each time slice is calculated; performing standard unit conversion on the acquired environment data, and combining the obtained occupancy rate information to form a total environment load vector; matching a preset parameter according to the hotel type, and if no matching type exists, calculating to obtain an optimal parameter group of the hotel; on the basis of the parameters, the load efficiency of each time slice is calculated firstly, and then a DO-ELE coefficient is obtained through calculation and serves as an evaluation index; and according to the calculated DO-ELE coefficient, determining the ESG governance grade of the hotel by comparing with a preset grade division standard, and generating a visual evaluation report of a related data curve.

To provide a home presence rate management device and a home presence rate management method which can precisely predict the home presence rate of a resident.SOLUTION: A home presence rate management device includes a home presence rate prediction information storage unit and a home presence rate prediction information processing unit. The home presence rate prediction information storage unit has a home presence rate prediction data table for storing the prediction value of the home presence rate set for each house and each time zone. The home presence rate prediction information processing unit acquires information of the home presence rate and the home absence rate for each house and each time zone as information on delivery operations that a distributor has done in a predetermined period of time, and adds more predicted values of corresponding houses in corresponding time zones in the home presence rate prediction data table when the amount of information showing presence in the home is larger, and subtracts more predicted values when the amount of information showing absence in the home is larger, on the basis of the acquired information.SELECTED DRAWING: Figure 1

An elevator full load detection method and apparatus, an electronic device, and a medium. The method comprises: acquiring a depth image collected by a depth camera; acquiring a first number of pixels occupied by an object at an elevator car bottom in the depth image and a second number of pixels occupied by the elevator car bottom in the depth image; determining the elevator occupancy rate of an elevator on the basis of the first number and the second number; and on the basis of the elevator occupancy rate, determining whether the elevator is fully loaded. According to the elevator full load detection method, the passenger face privacy can be well protected by means of a depth image, and on the basis of the elevator occupancy rate, it is determined whether an elevator is fully loaded, so that unnecessary staying of elevators can be reduced, improving the elevator operation efficiency and the passenger riding experience, saving electric energy, and reducing mechanical abrasion of the elevators.

The invention belongs to the field of commodity purchasing, and discloses a blind-eye selective purchasing control method and system based on an intelligent matching technology, and the method comprises the steps: only displaying commodity standard library information through initialization setting to hide a supplier identity, and achieving blind-eye selective purchasing; supplier main data, commodity standard library data and real-time purchase demand data are acquired in real time; calculating a supplier performance score by using a multi-dimensional weighted scoring model to measure a comprehensive performance ability, calculating a cost performance index based on a commodity standard library and a real-time demand to evaluate a commodity comprehensive value, and dynamically generating a contract group quota allocation value in combination with a quota occupancy rate and the performance score; and finally, a matching score is calculated by integrating the performance score, the cost performance index and the quota distribution value, and suppliers are intelligently screened. By adopting the method, the contract resource allocation efficiency is improved, and the limit is prevented from exceeding the limit or being idle; the data security is enhanced, and order tampering and historical migration conflict risks are reduced; and the fairness, the reliability and the automation level of the purchasing system are integrally optimized.

The invention relates to the field of network management, Internet of Things and hotel informatization, in particular to a dynamic management system and method for an intelligent network cabinet of a hotel, and the system comprises a data collection module, a data processing analysis module, a multi-target optimization module and an execution feedback module which are connected through electric signals. The data acquisition module acquires network cabinet data, guest room occupancy rate and user preference; the data processing and analyzing module processes data, constructs a historical data set and predicts the historical data set; the multi-objective optimization module adjusts the weight according to the prediction result to obtain an objective function and an optimal strategy; the execution feedback module adjusts related strategies according to the optimal strategy, compares actual and prediction results, and decides whether to update Transformer model parameters and regenerate the strategy, through cooperative work of multiple modules, dynamic management of the hotel intelligent network cabinet is realized, the operation efficiency of the network cabinet is effectively improved, the cost is reduced, and the user experience is improved.

The invention discloses an urban residential quarter housing occupancy rate prediction method and device and a medium, and relates to the field of housing occupancy rate prediction.The method comprises the steps that an urban residential quarter housing occupancy rate estimation model is built based on urban residential quarter basic information and mobile phone signaling data, and correction is conducted through the actually-collected housing occupancy rate; according to the spatial range boundary, the terrain, the PM2.5 concentration, the POI, the urban road network, the NPP-VIIRS and the urban community house price of the to-be-predicted urban residential community in the set time period, determining characteristic index data, and aligning the spatio-temporal data to obtain processed characteristic index data; and through a mixed multi-head attention mechanism coupled with an efficient routing strategy and a long short-term memory network, constructing an urban residential quarter housing occupancy rate prediction model, inputting the processed characteristic index data, and determining a predicted value of the housing occupancy rate of the urban residential quarter to be predicted. According to the invention, accurate prediction of the housing occupancy rate of the urban residential quarter is realized.

The invention belongs to the technical field of apartment operation and maintenance, and particularly relates to an apartment operation and maintenance data management system and method based on the Internet of Things. According to the invention, through real-time monitoring of energy and equipment states, visualized large-screen display of the overall operation condition of the apartment is realized, fault discovery and response time is shortened, operation and maintenance efficiency is improved, the apportionment amount is automatically adjusted based on actual energy consumption and reference, market and seasonal changes can be reflected, and operation and maintenance efficiency is improved. Meanwhile, public energy consumption is finely allocated, automatic detection of unpublic allocation, instantaneous energy abnormality and equipment fault signals and priority work order generation are completely eradicated, the manual monitoring burden is greatly reduced, potential risks are handled in the first time, the maintenance cost and potential safety hazards are reduced, and the economic benefit is improved. Based on the comprehensive analysis of the payment weight, the historical operation and maintenance data and the current house resource state, accurate lease renewal, lease expansion or preferential strategy suggestions are provided for managers, and revenue maximization and lease rate improvement are realized.

The invention discloses a supply chain management system and method based on big data, and belongs to the field of hotel supply chain management, and the system comprises an intelligent sensing module which is used for collecting multi-source public information and equipment operation data, and integrating and outputting structured data and a guest room state thermodynamic diagram; the decision optimization module is used for inputting multi-modal structured data, supplier parameters and inventory demand data, and outputting time-phased occupancy rate prediction through fusion of the structured data; generating a purchase negotiation strategy, and outputting a purchase plan; the execution control module is used for converting the purchase plan into a BPMN standardized process containing a distributed account book certificate; identifying an anomaly based on a dynamic threshold determination algorithm; and the iterative feedback module is used for collecting the purchase execution data and the exception handling data, and analyzing and generating an optimization report. The system can solve the industrial problems of demand lag, serious waste and the like of traditional hotel purchase.

The invention discloses a heat supply pipe network monitoring method and system based on temperature balance, a medium and a product, and relates to the field of data monitoring. According to the method, the monitoring system periodically collects the real-time operation parameters of all the building units in the heat supply pipe network, the initial flow distribution coefficient of all the building units is calculated according to the water supply and return pressure difference, and the final flow distribution coefficient is obtained by combining building unit occupancy rate correction. And the monitoring system calculates the temperature balance degree of each building unit according to the return water temperature and the indoor temperature so as to determine the temperature balance index of the heat supply pipe network, further draws a pipe network temperature balance change curve, and determines the adjustment sensitive time period according to the curve slope. According to the dynamic monitoring mode based on temperature balance, heat supply abnormity can be found in time, the data collection frequency and the alarm threshold value are adjusted in a self-adaptive mode according to the sensitive time period where the building unit is located, the abnormity detection accuracy is improved, meanwhile, resource waste caused by excessive collection is avoided, and refined monitoring of the heat supply pipe network is achieved.

An HVAC control system having a cloud-based optimization engine in communication with a local building hub that interfaces with the building HVAC system and room units. The cloud-based optimization engine implements an optimal and predictive control strategy to integrate occupancy prediction, weather forecasting, and modeling of indoor infection risk, indoor air quality, and building energy consumptions. The control strategy includes a model-based predictive control and a model-free reinforcement learning approach. The control strategy considers outdoor weather (both thermal and air quality) conditions, indoor occupancy and requirements for IAQ and infectious risk reduction to decide whether outdoor air should be introduced and how much fresh air will be introduced into the space. Communications with the building hub allow the local HVAC unit to be driven according to the optimization plan. Individual room sensing units can provide local sensor data to the cloud-based optimization engine.

The application provides an assembled building electromechanical pipeline automatic wiring method and system, constructs a grid space by relying on a building information model, extracts forbidden area and pipeline port coordinates, and gives grid medium conflict weight according to pipeline type; generates a comprehensive sorting key by combining pipe diameter, pressure grade and space bottleneck quantity, performs descending order sorting on the pipeline, removes isolated grids based on connectivity, and takes bottleneck cross-sectional area reciprocal as congestion penalty; expands the direction according to the turning constraint weight, matches the threshold to limit pipeline turning, fuses Manhattan distance and joint cost to construct a heuristic function, adjusts node cache screening multiple according to cache occupancy rate, completes grid space wiring by using A-star algorithm, and adjusts and regulates the soft forbidden area according to high-priority pipeline parameters; when the subsequent pipeline has no solution, backtrack the previous suboptimal node and rewire, and if the same pipeline has no solution for multiple times, reduce the conflict weight and modify the soft forbidden area thickness, and write the wiring path meeting the constraint to the building information model.

The application relates to the technical field of flow security, in particular to a privacy data security protection method and system for a business information platform and a medium, the method comprising the following steps: acquiring an initial flow set and a historical flow set; determining reference flows of each initial flow from the historical flow set; determining classification error probabilities of each attribute included in each initial flow based on attribute value similarities between attribute values of the same attribute of each initial flow and each corresponding reference flow; dividing the initial flows included in the initial flow set into normal flows and disguised flows based on the classification error probabilities of each attribute included in each initial flow; and performing isolation treatment on the disguised flows in the case that a resource occupancy rate of the disguised flows is greater than a resource occupancy rate threshold. The method can analyze disguised flows hidden in the initial flows and difficult to be distinguished by conventional means, and improves the security of network protection.

The invention discloses a hotel guest room number ratio optimization method combining a room yield dynamic state and a building area parameter, and relates to the technical field of building layout optimization, and the method comprises the steps: 1, giving a partition, a settable net region and a priori contraction solution space through structural grids, curtain wall division, shaft buffer superposition and morphological erosion reduction, and carrying out the optimization of the room yield dynamic state and the building area parameter; the method comprises the following steps of 1, building a partition-house type robust optimization and integration MILP and shadow price guidance geometric fine tuning, 2, rewriting settable variables by using a furniture interference convolution kernel and electromechanical / wireless software elements and considering the modulus risk of a curtain wall, 3, mapping a door opening-aisle-exit, converting into path and capacity constraint, and eliminating posteriori check, 4, building partition-house type robust optimization and integration MILP and shadow price guidance geometric fine tuning, and 5, building a partition-house type robust optimization and integration MILP and shadow price guidance geometric fine tuning. And step 5, triggering re-solving through three-anchor-point write-back, AP RSSI and return air static pressure recharging, realizing an auditable closed loop, improving compliance, room yield and construction controllability, and reducing the risk of non-standard curtain walls and reworking.

The invention relates to the technical field of intelligent security check, and discloses a video analysis and prediction system applied to intelligent scheduling management of a security check channel, and the system comprises a data processing module which obtains flight information from a flight information system of an airport, fuses real-time passenger flow data collected by video monitoring, and constructs a multi-dimensional data set; the multi-curve analysis module is used for generating a full-load curve, an actual attendance curve, a historical prediction curve and a crew curve based on the multi-dimensional data set; and the intelligent scheduling recommendation module is used for calculating the number of security check channels required at the current time point according to the real-time number of people obtained by superposing the full load curve, the actual attendance curve, the historical prediction curve and the crew curve in combination with a preset security check speed. By means of the scheme, minute-level data processing, multi-dimensional prediction analysis and intelligent scheduling can be achieved, so that the security check efficiency and the resource utilization rate are improved, and efficient and safe operation of air transportation is guaranteed.

The invention discloses a bus dedicated path planning method and system for coping with multi-dimensional consideration, and relates to the technical field of path planning, and the method comprises the steps: synchronously collecting the multi-dimensional data of a target road section, and calculating a real-time traffic entropy value based on an information entropy theory; determining participants, performing auditing to generate an effective bidding list, regarding road use right distribution as a cooperative game problem, calculating marginal contribution of each game subject by adopting a Shapley value algorithm, and screening an optimal bidding combination; dividing traffic state intervals, combining the optimal bidding combination, the real-time traffic entropy and the exclusive lane occupancy rate, deciding the right to use according to an interval allocation rule, and generating a standardized allocation scheme; and converting the distribution scheme into a V2X broadcast instruction to be pushed, completing dynamic lane mark switching and passing guidance, collecting feedback data in real time to judge whether deviation occurs, and if the deviation is judged, dynamically adjusting the scheme and re-executing the scheme, thereby realizing dynamic optimal configuration of bus lane resources and system stability.

This invention provides a method, central control device, and processing system for handling loose pallets. The method includes: acquiring parameter information for each loose pallet in a temporary storage area and the corresponding occupancy rate of the temporary storage area; wherein the parameter information includes the storage duration of the loose pallet in the temporary storage area, and the number of cigarette cases placed on the loose pallet is less than the number of cigarette cases placed on a full-load pallet; if the storage duration of the target loose pallet in the temporary storage area exceeds a preset storage duration threshold, or the occupancy rate of the temporary storage area corresponding to the target loose pallet exceeds a preset occupancy rate threshold, then all loose pallets in the temporary storage area whose cigarette case specifications are the target specifications are identified as loose pallets to be reorganized, wherein the target specifications are the specifications corresponding to the cigarette cases placed on the target loose pallets; performing a loose pallet reorganization operation on the loose pallets to be reorganized to reduce the number of loose pallets to be reorganized and / or obtain at least one full-load pallet after reorganization. This invention can improve the turnover efficiency of loose pallets and reduce inventory redundancy.

The application discloses an enterprise service platform intelligent management and control method and system based on function analysis, relates to the technical field of platform intelligent management and control, and comprises the following steps: collecting the calling frequency, resource occupancy rate, response time delay, user behavior track and abnormal event data of a function module, performing standardization and time sequence verification, and constructing a multi-dimensional running data flow. A function behavior model is constructed based on a graph neural network, module running characteristics and structural dependencies are extracted, a function heat score graph is dynamically generated, and visual display of module load and abnormal hotspots is realized. A function twin copy is constructed for a key module, a management and control strategy is simulated in an isolated simulation environment, and feedback is obtained. A multi-level management and control strategy generation matrix is constructed based on the feedback, candidate strategies are generated and optimized, and the candidate strategies are dynamically deployed, continuously monitored and automatically adjusted. The system adopts a hierarchical rollback mechanism, realizes adaptive rollback of the strategy in an abnormal situation, and guarantees stable and reliable operation of the platform.

The shelf tier management system S acquires size information of a shelf tier and size information of an accommodated item that has been accommodated in the shelf tier, obtains a occupancy rate of the accommodated item in the shelf tier on the basis of at least the size information of the shelf tier and the size information of the accommodated item, and calculates a corrected occupancy rate by correcting the occupancy rate with a correction coefficient according to the accommodated item.

To improve the occupancy rate of real estate properties. [Solution] A real estate subleasing method in which a real estate company leases real estate from a real estate owner using a real estate management server and then subleases the real estate to a real estate user. The real estate management server registers information about the real estate owner, property information, and real estate user information. The property information includes the rent that the real estate company pays to the real estate owner (i.e., the lease fee), the rent that the real estate user pays to the real estate company (i.e., the sublease fee), and the sublease guarantee deposit that the real estate user pays to the real estate company. The sublease fee is the amount obtained by subtracting a sublease fee discount amount, which is determined based on the guarantee deposit income that the real estate company can expect to earn by investing the sublease guarantee deposit, from the lease fee, and is therefore cheaper than the lease fee.

The invention relates to the technical field of warehouse management, in particular to an AGV scheduling and warehouse stock decision-making system and method based on data analysis. Comprising an inventory management module used for obtaining storage data, sales data and to-be-warehoused data, the storage data comprises real-time inventory data, and the storage quantity and the storage amount of each type of goods, the sales data comprises the sales amount of each type of goods, and the to-be-warehoused data comprises to-be-warehoused goods and the to-be-warehoused quantity; the area analysis module is used for analyzing the occupancy rate of each current inventory area according to the real-time inventory data, and the inventory area with the occupancy rate lower than a preset occupancy threshold value is marked as a low-occupancy area mark; and the turnover rate analysis module is used for calculating the stock turnover rate warehousing grade of the goods in the preset period according to the storage amount and the sales amount of the goods in the preset period, and is used for determining the warehousing grade of the goods to be warehoused according to the to-be-warehoused quantity and the storage amount turnover rate of the goods to be warehoused.

The invention relates to the technical field of big data service platforms, in particular to a government affair big data public service platform method, which comprises the following steps: a service chain definition step: analyzing a government affair data service request submitted by a user, and generating a government affair data service chain comprising a plurality of service nodes; a dynamic authority anchoring step: constructing a cross-department authority certificate chain based on a block chain, verifying the data use authority of a service node operator, and embedding an authority traceability label; a data consanguinity packaging step: extracting a data ontology layer, constructing a consanguinity metadata layer and a service interface layer, and forming a standard data container; and a service chain self-optimization execution step: monitoring the resource occupancy rate of each service node in real time, carrying out edge unloading and parallel execution on the container with the resource pressure overload, and finally outputting an integrated result. According to the method, service chain structured modeling, authority dynamic verification, data full-process traceability and computing resource adaptive scheduling are realized, and the security, controllability and execution efficiency of government affair data service are improved.

The application provides a port area collection and distribution automatic driving vehicle and cargo cooperative path planning method and system, and relates to the technical field of intelligent traffic and port logistics. The method comprises setting short-time and long-time storage thresholds, dividing containers into short-time and long-time storage groups, adopting dispersed container trucks and centralized container pickup for fast queuing and port departure for the former, and transferring the latter to a rear collection and distribution center in one time; adopting a multi-agent PPO model to jointly optimize a multi-objective reward function comprising short-time container, long-time container retention penalty, full load rate reward, empty load mileage penalty, yard cost saving reward and delay penalty; combining LSTM traffic prediction to update space-time graph edge weight, and applying return load pre-matching, time window synchronization and safe distance constraint; and realizing second-level to minute-level re-planning through closed-loop online learning. The application effectively reduces yard occupancy rate and storage cost, reduces vehicle empty load ratio, improves collection and distribution efficiency and safety, and has high industrial application value.

The present invention discloses a local area network (LAN) and data security-based office equipment rental management method and system. The method includes responding to office equipment rental requests from rental terminals, obtaining equipment loss rates and network behavior security scores from historical rental behaviors; parsing the target device model and required quantity in the rental request when both meet preset conditions; monitoring the LAN online status and resource occupancy rate of the target device in real time to calculate the available inventory of the target device; when the available inventory is lower than the required quantity, matching security-associated devices of the same type as the target device in the LAN device registry to calculate the device replacement security index; generating a device replacement policy when the index is greater than a security baseline, signing the policy with a digital certificate, and issuing it to the rental terminal. The system generates a target rental plan by requesting the device replacement policy in response to the rental terminal. The present invention improves the data security and response speed of rental services, and increases the utilization rate of equipment resources and the transaction rate of rental business.

The invention provides a hospital bed turnover method and system based on hospital data, a medium and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring sickbed occupation information of a plurality of departments; based on the sickbed occupancy information, predicting a first sickbed occupancy rate of a plurality of departments after a target duration; under the condition that the occupancy rate of the first sickbed is smaller than an occupancy rate threshold value, sickbed tension and patient waiting cost of the multiple departments are determined; and generating a sickbed optimization scheme based on the sickbed tensity of the plurality of departments and the patient waiting cost, and transferring the sickbeds of the plurality of departments according to the sickbed optimization scheme.

The invention discloses a parking business marketing strategy optimization method and system, and relates to the related technical field of intelligent parking, and the method comprises the steps: obtaining a user navigation terminal point, a target parking lot occupancy rate and a user travel feature in real time; calculating a distance attenuation coefficient between the user travel and the parking lot through a dynamic matching engine, and triggering pushing when the distance attenuation coefficient reaches a threshold value; based on the real-time occupancy rate and the predicted arrival time, dynamically generating triple aging parameters including receiving, payment and failure logic; generating a dynamic preferential strategy matched with the current scene; when the user approaches the destination, a dynamic policy push with countdown is performed. The technical problems of low parking resource matching efficiency and poor marketing conversion rate due to the fact that accurate and timely marketing touch cannot be performed based on the real-time journey of the user and the dynamic state of the parking lot in the prior art are solved, and the purposes of improving the accuracy, timeliness and user experience of a parking service marketing strategy and improving the user experience are achieved. And the scheduling efficiency of the parking resources and the business conversion rate are improved.