217 results about "Environmental agent" patented technology

The invention provides a dynamic health monitoring system integrating artificial intelligence and wearable equipment and a method thereof, and relates to the field of health monitoring, and the method comprises the steps: collecting physiological parameters and environmental data of a user, eliminating time migration of multi-source data through a timestamp alignment technology, extracting dynamic coupling features of the physiological parameters and the environmental data, and obtaining a dynamic health monitoring result; and generating the health state characterization guided by the environment. The method comprises the following steps: synchronously acquiring user voice input information, and extracting and analyzing acoustic features to generate emotional state change features after performing Mel spectrum conversion; then, cross-modal semantic association between emotions and health states is established through a modal soft constraint mechanism, and personalized guidance suggestions are generated and displayed, so that the dynamic perception ability of health state assessment and the scene adaptability of suggestion generation are improved; therefore, the problems of environmental factor splitting, subjective and objective data isolation and insufficient dynamic nonlinear relation modeling in a traditional method are solved.

The invention relates to the technical field of agricultural data management, in particular to a grain data management method and system based on artificial intelligence, and the method comprises the following steps: based on a grain transportation container and a storage environment, extracting monitoring data of temperature and humidity monitoring equipment, a gas component detector and an illumination sensor, summarizing environment parameters, screening abnormal environment data, and storing the abnormal environment data; and obtaining an environment state record. According to the invention, through accurate analysis of temperature and humidity, gas components and illumination data, perception and alarm capabilities of sudden changes of a storage environment are enhanced, comprehensiveness of quality change monitoring is improved, mining capability of relevance of environmental factors and microbial pollution is enhanced, optimal storage conditions are matched, quality loss risks are reduced, pollution factors are accurately identified, and the method is suitable for popularization and application. Through combination of air quality data, pollution hidden danger screening and risk pre-judgment capabilities are improved, abnormal environment data are deeply analyzed, quality deterioration alarm is optimized, abnormal environment identification precision is improved, and a grain quality guarantee system is enhanced.

The invention belongs to the technical field of medicines, and discloses a near-infrared cyanine probe for detecting penicillin G acylase as well as a preparation method and application of the near-infrared cyanine probe. According to the research, a near-infrared fluorescent probe Cy-NEO-PA responding to penicillin G acylase (PGA) is developed, so that the influence of environmental factors on the formation of an acinetobacter baumannii biological membrane is observed. Research results show that glucose inhibits the generation of PGA to enhance the formation of a biological membrane, while phenylacetic acid (PAA) stimulates the generation of PGA and inhibits the formation of the biological membrane. The observation results highlight the excellent capability of Cy-NEO-PA in accurately measuring PGA kinetics, and reveal the key effect of PGA in biological membrane development. In addition, the Cy-NEO-PA has good biocompatibility, strong active oxygen generation, efficient photo-thermal conversion and bacterial targeting ability, so that the Cy-NEO-PA becomes a promising drug for resisting bacterial infection and promoting wound healing through photo-thermal / photodynamic therapy.

The invention discloses a soil pollution diffusion prediction method based on differential evolution, and relates to the technical field of soil pollution control, and the method comprises the steps of collecting soil sensing data in real time, and uploading the soil sensing data to a data center. Real-time sensing data are compared and calibrated, sensing data errors caused by environmental factors are effectively reduced, data input into a model are more accurate and reliable, meanwhile, model parameters are optimized and solved by combining differential evolution and a particle swarm optimization algorithm, the differential evolution is used for global optimization to find a proper parameter combination, and the accuracy of the model parameters is improved. Particle swarm optimization performs local fine adjustment based on a differential evolution result, and the two are alternately performed, so that the accuracy of soil pollution diffusion prediction is greatly improved, the diffusion trend of pollutants in soil can be more accurately grasped, and a more reliable basis is provided for ecological environment management and human health protection.

The invention discloses lysozyme, antibacterial peptide derived from the lysozyme and application of the lysozyme in preparation of antibacterial drugs. According to the invention, 1, 640 protein sequences recorded in a ruminant rumen caterpillars genome database are systematically predicted based on a lysozyme prediction model, and finally, the lysozyme with the amino acid sequence as shown in SEQ ID No.1 is relatively strong in antibacterial activity and stable in antibacterial activity, and is slightly influenced by environmental factors. According to the invention, an antibacterial peptide region of the lysozyme is analyzed and determined, three peptide fragments with clear antibacterial activity are identified, and the amino acid sequences of the peptide fragments are respectively shown as SEQ ID No.2, SEQ ID No.3 or SEQ ID No.4. The antibacterial peptide provided by the invention has relatively strong membrane destroying ability and broad-spectrum antibacterial activity, and compared with integral protein, the antibacterial peptide is simpler in structure and more flexible in synthesis and modification, and is easier to break through a bacterial drug-resistant mechanism.

The invention belongs to the technical field of novel pesticides, and particularly provides a bactericide suspending agent and a preparation method thereof.The effective component of the bactericide suspending agent is prothioconazole, and on the basis of the effective component of the bactericide suspending agent, microencapsulated oxidized vegetable oil accounting for 5-15% of the weight of the whole bactericide is added to serve as a synergistic auxiliary agent. The prothioconazole bactericide has the advantages that the adhesion capacity of the prothioconazole bactericide on the surfaces of crops can be obviously improved, the adverse effects caused by environmental factors such as rain wash are reduced, and the absorption of the bactericide is facilitated, so that the synergistic effect is achieved.

The invention relates to the technical field of smart breeding and big data analysis, and discloses a smart breeding monitoring method and system based on big data analysis. The method comprises the following steps: periodically acquiring original data of a farm sensing network, and constructing a multi-dimensional state image through time-space synchronization and normalization processing; inputting the image into a pre-trained behavior-environment decoupling analysis network, and stripping an independent behavior feature tensor and an independent environment background field tensor in parallel; and based on the two, calculating a coupling degree index through a cross impact evaluation matrix and generating a comprehensive anomaly scoring graph. According to the graph, a strategy generation engine dynamically synthesizes a regulation and control instruction set containing directional airflow guide, refined feeding and temperature and humidity coordinated regulation. According to the method, deep separation and correlation analysis of animal behaviors and breeding environment factors are realized, an abnormal root can be accurately traced, and early warning and systematic precise regulation and control are realized.

The invention relates to the technical field of psychological state assessment, and particularly discloses a psychological state assessment method and system based on environmental perception, and a readable storage medium, and the method comprises the following steps: collecting an environment scene and an assessed object behavior image through an RGB camera, and extracting an object category, a spatial layout and a dynamic event through a semantic segmentation model; acquiring an environment voiceprint through a microphone, and recognizing a voice category by using a voice recognition model; synchronously acquiring facial micro-expression feature points, voice rhythm features and head, neck and shoulder vibration frequencies of the evaluated object; and generating a semantic vector from the object / scene label through a semantic embedding model. According to the psychological state assessment method based on environmental perception, through three core innovations of quantitative modeling of environmental semantics, causal reasoning and a dynamic attention mechanism and personalized adaptive calibration, the neglect limitation of traditional psychological assessment on environmental factors is broken through, and the accuracy, robustness and practicability of psychological state assessment are remarkably improved.

The invention discloses a line fault risk space-time distribution prediction method under bias-heterogeneous environmental factors, and the method comprises the following steps: S1, obtaining a set of historical line fault records, carrying out the normalization processing of the historical line fault records and corresponding feature factors, and obtaining a set of the historical line fault records; constructing an input mapping space between historical line fault records and corresponding fault features to obtain an evaluation database A; s2, for a data bias-heterogeneous environment, parallel learning of discrete features and continuous features in fault features is completed, and common factors and rare factors are obtained; and S3, establishing a fuzzy conditional correlation pattern identification model FCCPI, respectively extracting a high-risk HR factor and a rare high-risk RHR factor in the common factors and the rare factors through the fuzzy support degree and the conditional fuzzy support degree, normalizing the fuzzy support degree and the conditional fuzzy support degree, integrating the fuzzy support degree and the conditional fuzzy support degree to obtain a support degree score, and quantifying the risk level through the support degree score.

The invention belongs to the technical field of data processing, and relates to a disinfectant verification method based on Jerlin codes. The invention aims to solve the problem of biological potential safety hazards that the identity and the state are separated in the anti-counterfeiting verification of the existing disinfectant, and the titer of the liquid medicine falls off the threshold value due to environmental factors cannot be identified. The method comprises the following steps: in response to a code scanning operation, analyzing a Jerlin code to obtain a factory fingerprint, and splicing cloud logistics and terminal storage data to form a full-link environment monitoring sequence; calculating an environment pressure acceleration coefficient of each time slice by using a nonlinear kinetic model, and evaluating the damage degree of the environment to chemical properties; calculating accumulated chemical loss and residual titer based on the coefficient; and comparing the residual titer with a threshold value, and if the residual titer reaches the standard, generating a dynamic hash token containing titer information for cloud verification. According to the invention, deep combination of physical efficacy and digital verification is realized, and the use safety and reliability of the disinfectant are greatly improved under the condition that an expensive sensor is not needed.

The invention relates to the technical field of medicine management, in particular to an intelligent medicine expiration date management method and system, and the method comprises the steps: collecting environment parameters of medicine storage in real time; constructing a characteristic database of drug stability, and constructing a degradation rate model of the corresponding drug based on the characteristic database; based on the environmental parameters and a degradation rate model, calculating an accumulated value of the current storage condition to the drug quality, and generating a quality risk level; and generating a medicine optimization management instruction based on the quality risk level and the remaining time of the medicine fixed effective period. By means of the method, the problem that the medicine effect fails in advance due to the fact that dynamic environment factors are neglected in a traditional method is effectively solved, accurate early warning of quality deterioration is achieved through dynamic monitoring and degradation modeling, supervision blind areas are eliminated, and the risk of medical resource waste is reduced.

The utility model belongs to the technical field of experimental research, and particularly relates to an experimental device for researching a subsurface zone pollutant migration rule, which comprises a water injection component, a column body, a filling medium and a detection component, the column body is of a cylindrical cavity structure, the upper end and the lower end of the column body are each provided with a water injection opening, and the two water injection openings are each communicated with one output end of the water injection assembly; the filling medium is arranged in the column body and is used for simulating a soil layer structure from surface water to underground water; the detection assembly comprises a processor, an environment monitoring module and a pollutant collection module; the environment monitoring module is used for monitoring different depth environment indexes in the filling medium; and the pollutant collection module is used for collecting pollutants at different depths in the filling medium at regular time and transmitting the pollutants to the processor for analysis. The device can avoid the interference of external environmental factors, and provides reliable reference data for accurately analyzing the migration rule of the subsurface zone pollutants in the vertical direction.

The invention relates to the field of rice disease and insect pest questioning and answering, in particular to a rice disease and insect pest questioning and answering method based on circular retrieval. The scheme comprises the following steps: collecting data; constructing a rice disease and insect pest knowledge base; encoding a rewritten problem into vector representation by using an embedded model; executing cosine similarity matching in the knowledge base; whether the retrieved context can answer the question of the user or not is judged, if yes, the answer to the question is output through a large language model, if not, the large language model is used as a generation model, a targeted reverse question is generated in combination with prompt words, and the user is guided to provide more rice disease information, environmental factors and symptom description in a reverse question mode; and then integrating and optimizing to obtain a new question, executing cosine similarity matching in the knowledge base through the obtained question, and realizing efficient and accurate answering through the circular retrieval. The method is suitable for rice disease and insect pest questioning and answering.

The invention discloses antistatic medical gauze and a preparation method thereof, and relates to the technical field of medical gauze. The antistatic medical gauze comprises the following raw materials in parts by mass: 60-80 parts of cotton fibers, 1-5 parts of an antistatic agent, 5-15 parts of a water-soluble polymer and 0.5-1 part of an antibacterial agent. Compared with the traditional technology that the antistatic effect is transient and is easily influenced by environmental factors, the invention realizes long-acting and stable charge neutralization capability by introducing a specific micromolecule antistatic agent (such as a compound shown in the formula 1) and combining a moisture absorption conductive mechanism, an ionization effect and surface energy regulation. The trend shows that the static dissipation is faster and the effect is lasting, the problems of potential safety hazards and dust adsorption caused by charge accumulation are effectively avoided, and the defect that the effect of an antistatic agent in the prior art is not lasting is overcome.

The invention relates to an NAPL contaminated site comprehensive evaluation method based on environmental medium driving. The NAPL contaminated site comprehensive evaluation method comprises the following steps: collecting a contaminated site soil sample and an underground water sample and measuring physicochemical property parameters of the soil sample and the underground water sample; simulating the migration process of the NAPL in the underground environment by using a microfluidic experimental device to obtain a migration form change image in the migration process of the NAPL; for a migration form change image in the NAPL migration process, a multi-scale image processing algorithm is adopted to carry out feature parameter extraction; inputting the measured physicochemical characteristic parameters into a model constructed based on multi-factor coupling so as to compare an error between a model prediction result and an experimental measurement value; and in combination with GIS analysis, the pollution condition is determined according to a model prediction result, the risk level is judged, and a repair suggestion is given. According to the method, multiple key environmental factors are comprehensively considered, accurate data are obtained through a microfluidic experiment, a reliable migration model is constructed, and the NAPL pollution condition is accurately evaluated.

The invention discloses a garden disease and pest identification method and system based on computer image processing, and belongs to the technical field of disease and pest monitoring, and the method specifically comprises the steps: collecting a visible light image, an infrared image and environment parameters of vegetation; performing space-time registration on the visible light image and the infrared image and generating a three-dimensional temperature field model; the three-dimensional space is divided into grid units, and the temperature statistical characteristics and the vertical direction temperature gradient of each unit are extracted; obtaining an expected temperature gradient direction through a preset standard three-dimensional radiation field reference model; and when the actual gradient direction is consistent with the expected gradient direction, calculating a gradient direction deviation value of each grid unit, calibrating the grid unit with the deviation exceeding a threshold value as an abnormal region, and extracting a corresponding visible light image to carry out pest recognition. According to the invention, early-stage accurate identification of diseases and insect pests is realized, systematic diseases and local insect pests are effectively distinguished, interference of environmental factors is overcome, and the reliability of insect pest monitoring is improved.

The invention discloses a sea-land interaction zone underground water pollution source tracing method based on multi-pollutant fingerprints, and the method comprises the steps: constructing a fingerprint feature library of eight key pollutants including cadmium, arsenic, nitrate nitrogen, ammonium nitrogen, phosphate, total petroleum hydrocarbon, sulfamethoxazole, pH value and the like; statistical characteristic models of four pollution sources of industrial emission, agricultural non-point sources, oil exploitation and aquaculture are established, Z-Score standardization and a similarity calculation method based on a standard normal distribution probability density function are adopted, comprehensive similarity evaluation is performed in combination with a risk weight distribution mechanism, a similarity threshold value of 0.7 is set to perform pollution source identification and sorting, and the pollution sources are identified and sorted according to the similarity threshold value. And correction is performed by considering environmental factors such as tide, season and geology of a sea-land interaction zone. The method can quickly and accurately recognize the groundwater pollution source of the sea-land interaction zone, the traceability accuracy rate reaches 80% or above, and scientific and technical support is provided for prevention and control of groundwater pollution of the sea-land interaction zone and formulation of an environmental protection policy.

The invention provides a deep learning-based dangerous rock mass collapse landslide monitoring and early warning method and system, and relates to the technical field of geological disaster monitoring and early warning, and the method comprises the steps: obtaining rock mass monitoring data; according to the rock mass monitoring data, carrying out dangerous rock mass collapse landslide risk preliminary identification; when it is preliminarily recognized that the dangerous rock body does not have the collapse landslide risk, rock body monitoring data are obtained again; when the collapse landslide risk of the dangerous rock body is preliminarily identified, acquiring environment monitoring data; according to the rock mass monitoring data and the environment monitoring data, through a deep learning algorithm, carrying out dangerous rock mass collapse landslide risk fine identification; when it is finely recognized that the dangerous rock body does not have the collapse landslide risk, rock body monitoring data are obtained again; and when the collapse landslide risk of the dangerous rock body is finely identified, an early warning signal is sent out. According to the invention, environmental factors are considered, and timely and accurate early warning information can be provided in the face of complex and changeable natural environments.

The invention discloses a cibotium barometz sporophyte transformation method and system based on multi-factor coupling regulation, and relates to the technical field of biology. The method comprises the following steps: synchronously acquiring environment data and sporophyte image data; preprocessing the environment data, performing feature extraction on the image data, and splicing the processed data into a comprehensive feature vector; quantifying the weight, correlation degree and interaction level among the environmental factors through an entropy method, grey correlation analysis and a coupling coordination degree model; constructing an improved CNN-LSTM neural network, extracting features through a double-branch structure, fusing a coupling analysis result to carry out cross-modal fusion, and training to obtain a prediction model; when the predicted conversion rate is lower than a threshold value, environment parameters are automatically adjusted until conversion is completed; according to the method, the problems of environmental factor data isolation and regulation lag in the prior art are solved, accurate prediction and intelligent regulation of the sporophyte transformation process are realized, and the transformation success rate and the production efficiency are remarkably improved.

The invention relates to the technical field of animal behavioral experiments, and discloses an animal behavioral experiment multi-scene simulation system. According to the invention, through cooperative control of multiple environment modules and seamless switching of a dynamic scene, continuous switching of natural scenes such as illumination, sound, smell, terrain and the like is accurately simulated; on the basis of real-time biological signal detection and intelligent feedback, environment adjustment or scene switching is automatically triggered according to animal behaviors / physiological states, and closed-loop self-adaptive adjustment is formed; in combination with an intelligent decision and an AI scene generation engine, self-definition and iterative optimization of a complex script are supported; the parameter coupling controller simulates the interaction effect between environmental factors, the fault-tolerant mechanism and the effect evaluator guarantee the data reliability, the closed-loop verification loop efficiently establishes a causal model of environmental parameters and behavior response, and a high-authenticity, self-adaptive and reproducible experimental platform is provided for animal behavior research.

The invention provides a new pollutant classification prediction method and a related device, and relates to the technical field of new pollutant classification. Comprising the following steps: collecting chemical information (molecular structure, molecular fingerprint and physicochemical property) of a target pollutant and carrying out standardization treatment; preliminary classification is calculated based on Tanimoto similarity; simulating a migration path and a conversion behavior of the pollutants in the environment by using a graph neural network; multi-mechanism comprehensive evaluation is carried out by comprehensively considering durability, mobility and biological accumulation; introducing an environmental factor correction model, and correcting scores according to parameters such as temperature, pH value and dissolved oxygen concentration; integrating the molecular structure, the migration path, the mechanism characteristics and the environment correction result, and calculating a final classification prediction value; and dividing risk levels (high, medium and low risks) according to predicted values. Pollutant risks are comprehensively assessed through a machine learning technology, the assessment precision and reliability are improved, and a scientific basis is provided for pollution prevention and control.

The invention provides a nano lipid carrier system with photo-thermal stability as well as a preparation method and application thereof, and relates to the technical field of nano preparations. The lipid carrier comprises the following components: an active substance, hydrogenated lecithin, simmondsia chinensis seed oil, SpectrastHCP, an emulsifier and a chelating agent, wherein the active substance is resveratrol. The lipid carrier has better stability, is stable under the conditions of dilution, centrifugation and the like, and can be stored for a long time in a severe environment. Indissolvable substances such as resveratrol are wrapped by the lipid carrier, so that the water solubility of the substances can be remarkably improved, and the problem of difficult dissolution is solved. In addition, the wrapping of the lipid carrier can effectively isolate the influence of oxygen, illumination and other environmental factors, the stability of the active matter can be improved, and meanwhile, the discoloration problem is effectively improved. When the nano-scale lipid carrier is applied to a preparation, the nano-scale lipid carrier can more easily penetrate through the skin barrier and deeply penetrate into the deep layer of the skin, and the effect of transferring active matters is more facilitated.

The invention relates to the technical field of herbicide performance evaluation, in particular to a block chain-based herbicide performance evaluation method and system, and the method comprises the following steps: collecting the herbicide application amount, plant growth data, soil conditions and climate information in real time based on farmland environment monitoring information, summarizing and analyzing the data, and obtaining a block chain-based herbicide performance evaluation result; and comparing the data with the trend, identifying the influence of environmental factors, and generating environmental monitoring data. According to the method, encryption storage and timestamp marking are performed on the monitoring data of the agricultural herbicide through a block chain technology, so that the security and integrity of the data are improved, the data management is more transparent, data tampering is prevented, the credibility is enhanced, and by real-time analysis of the environment and the herbicide use effect, the monitoring efficiency of the agricultural herbicide is improved. The interaction between the environment variable and the pesticide effect is accurately evaluated, the scientificity and effectiveness of herbicide application are improved, the data processing flow is optimized, the real-time performance and accuracy of decision making are ensured, and accurate management of agricultural production is effectively supported.

The invention discloses a composite microcapsule of bacillus subtilis and trichoderma asperellum, which is prepared by the following steps: embedding bacillus subtilis Pn1 and trichoderma asperellum Ta1 by adopting sodium alginate, and carrying out microencapsulation treatment, so that the controllable release of the bacillus subtilis Pn1 and the trichoderma asperellum Ta1 is realized; therefore, the stability of the composite biocontrol bacterium under adverse environmental factors is improved, meanwhile, the inhibition effect on root rot bacteria is enhanced, and the sodium alginate embedded bacillus subtilis Pn1 and trichoderma asperellum Ta1 have important application value in prevention and treatment of panax notoginseng biological root rot.

The invention discloses an XGBoost chlorophyll a concentration aerial remote sensing inversion method based on characteristic wave band selection, and relates to the technical field of environmental monitoring. By constructing an integrated input characteristic vector, an optimal characteristic wave band most relevant to the chlorophyll a concentration, an enhanced chlorophyll a index and specially designed correction characteristics are fused; and more targeted information is provided for the model. Moreover, correction features obtained through calculation of spectral difference values of adjacent shadow regions and non-shadow regions are introduced, and training data containing samples of the two regions are utilized to train an XGBoost model, so that the XGBoost model can autonomously learn and quantify a composite interference effect brought by illumination and suspended matter concentration change. Therefore, according to the technology, inversion noise caused by complex environmental factors can be effectively inhibited, high-precision and full-coverage inversion of the chlorophyll a concentration under different illumination and turbidity conditions is realized, and the robustness and the practical application value of the method are remarkably improved.

The invention discloses a bacteriophage gel microsphere as well as a preparation method and application thereof. The preparation method is simple and easy to implement and convenient to operate and popularize. Meanwhile, the prepared bacteriophage gel microspheres are high in loading capacity and can effectively load bacteriophages, the high porosity and the porous structure can provide a large number of binding sites for the bacteriophages, the contact opportunity of the bacteriophages and bacteria is increased, and the antibacterial efficiency is improved. In addition, the hydrogel property of the bacteriophage gel microspheres can protect the bacteriophage from being influenced by adverse environmental factors such as dryness and high temperature, and the stability of the bacteriophage in practical application is improved. In addition, compared with bacteriophage hydrogel microspheres prepared in the prior art, the bacteriophage gel microspheres prepared in the invention have smaller particle size, so that multi-way administration modes such as treatment of pulmonary infection by atomization administration and the like can be carried out.

Select substituted lysine and branched amino acid salts, compositions containing the same and the use of the foregoing in treating the adverse physiological effects of various diseases, especially skin diseases; in mitigating the effects of aging and environmental factors on skin; and in improving and rejuvenating skin.

METHODS FOR GEOLOCATION-BASED SKIN SCIENCE-BASED ENVIRONMENTAL EXPOSURE METRICS Methods for communicating the risk of skin conditions due to exposure to sunlight and environmental conditions to individuals. These methods leverage geolocation and environmental data to provide guidance and enable consumers to make informed decisions regarding outdoor activities, healthcare, and skincare. A photopollution metric is a function of the ultraviolet index (UVI) and the level of a pollutant such as particulate matter (PM) and allows for the communication of an individual's risk of exposome-induced skin conditions based on environmental exposure. Figure for abstract: none

The present application relates to a kind of ship hull fouling detection method and system that can accurately remove environmental interference, the method includes the storage and pre-processing of multi-source data, the reference effective power under the prediction of unblocked state, the effective power required by the actual output and the effective power required by the environmental additional resistance, the effective power required by the consumption, the quantification and identification of fouling state and the output and visualization of result.The method can realize the high-precision quantitative evaluation of the degree of ship fouling, and accurately removes the interference of wind, wave, seawater temperature, salinity and other environmental factors.The above multi-source data can be collected synchronously in millisecond level to ensure the consistency of data space-time, in addition, the method is matched by resistance decomposition and fouling database, the fouling coverage area, thickness and type are accurately calculated, and the accuracy and reliability of fouling detection are significantly improved.

The invention belongs to the technical field of cultural relic protection and building information models, and discloses an ancient city wall daily management and disease management and control system and method based on BIM scene construction. An existing disease management and control system has the problems that the urban wall occurrence environment and the repair history are difficult to comprehensively consider, and multi-disease collaborative analysis is lacked. According to the method, non-structural nodes are introduced, environmental factors such as a drainage system, vegetation coverage, underground facilities and an internal space are incorporated into a city wall management system, and collaborative expression of a city wall structure and an occurrence environment is realized on the basis of structural partitioning. According to the system, urban wall block numbers serve as a unified index, monitoring data, disease information and repair records are fused, spatial visualization and information linkage are achieved based on a BIM scene, meanwhile, a threshold value management mechanism is set, when state parameters of non-structural nodes reach a threshold value, a corresponding maintenance protection scheme is triggered, and the maintenance and protection efficiency is improved. And urban wall information management, disease dynamic monitoring and scientific repair decision making are realized.