98 results about "Environmental agent" patented technology

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 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 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 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 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 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.

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.

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.

The invention discloses a strawberry gray mold early warning system and method based on multi-physiological index collaboration, belongs to the technical field of strawberry gray mold early warning, and solves the problems that in the prior art, due to dependence on a single data source, a model is easily interfered by environmental factors, early abnormal performance of gray mold in multiple physiological levels cannot be comprehensively captured, and the early warning effect is poor. Therefore, the recognition accuracy of the strawberry gray mold asymptomatic latency period is reduced. The data acquisition layer is used for acquiring fluorescence indexes, spectral indexes and photosynthetic indexes of strawberry plants; the feature processing layer is used for respectively calculating feature indexes corresponding to the fluorescence index, the spectrum index and the photosynthetic index acquired by the data acquisition layer; the alarm judgment layer is used for judging alarm levels corresponding to the feature indexes output by the feature processing layer; and the decision fusion layer is used for performing fusion decision according to the alarm level output by the alarm judgment layer to obtain an early warning state. The strawberry gray mold early warning method is used for realizing accurate and effective strawberry gray mold early warning.

The application provides a metal nanomaterial toxicity prediction method and device, the method comprises the following steps: collecting related data affecting the toxicity of the metal nanomaterial, wherein the related data comprises the physical and chemical properties of the metal nanomaterial, the interaction mode between the metal nanomaterial and organisms, the influence data of external environmental factors on the metal nanomaterial, and the selective reaction data of the metal nanomaterial between different organisms; screening target indexes from the related data and calculating the weights of the target indexes; inputting the target indexes and the weights corresponding to each target index into a pre-trained toxicity prediction model to obtain a metal nanomaterial toxicity prediction result. It can be seen that the application considers multiple dimensions and calculates the weights of the indexes, the indexes considered are more comprehensive, and the index weights can better reflect the influence degree of each index on the toxicity of the metal nanomaterial, thereby improving the accuracy of the model toxicity prediction.

This invention discloses a method for evaluating the interfacial reinforcement effect of a road interfacial reinforcing agent, comprising the following steps: S1, specimen preparation: asphalt, aggregate, and the interfacial reinforcing agent to be evaluated are compounded to prepare a standard specimen; S2, environmental and load simulation: the standard specimen is treated to simulate actual road environmental conditions to simulate cumulative damage; S3, mechanical property testing: mechanical tests are performed on the standard specimen after simulation treatment to obtain its interfacial mechanical property parameters; S4, comprehensive evaluation: based on the interfacial mechanical property parameters, an interfacial performance index is calculated to evaluate the reinforcing effect of the interfacial reinforcing agent. This invention simulates the complex environment during actual road use and conducts various environmental factor tests on the interfacial layer after treatment with the interfacial reinforcing agent to more realistically and accurately reflect the reinforcing effect of the interfacial reinforcing agent.

The present invention relates to a spinal needle that clearly identifies the presence of cerebrospinal fluid (CFS) to dispense a drug or anaesthetic in the correct direction and site of the meninges. The response of the sensor to the presence of CFS does not depend on environmental factors and is performed quickly to prevent excessive loss of CFS in the patient. The spinal needle comprises a hub having a proximal end and a distal end, said hub comprising a transparent tank arranged at the proximal end of the hub that is configured to receive CFS, an expandable CFS sensor arranged inside the transparent tank and a connection port arranged at the distal end of the hub configured to couple to a device for medical fluids, and a cannula comprising a tip fluidically connected to the proximal end of the hub.

The invention discloses a chronic obstructive pulmonary disease acute exacerbation risk early warning method and system based on home monitoring data and environmental factors, and belongs to the technical field of medical health monitoring and risk early warning. The method comprises the following steps: acquiring multi-dimensional data (symptom score, FEV1 trend, night blood oxygen saturation, medication compliance and weather data) of a user; pre-processing the multi-dimensional data and inputting the pre-processed multi-dimensional data into the trained machine learning prediction model; the model outputs an acute exacerbation risk probability value in the future 7 days; when the risk probability exceeds a preset threshold value, graded early warning information and personalized intervention suggestions are sent. The system comprises a data acquisition module, a data preprocessing module, a model prediction module, an early warning pushing module and a terminal interaction module. Multi-source data are integrated, through targeted feature extraction and model training, early-stage accurate early warning of chronic obstructive pulmonary acute exacerbation is achieved, meanwhile, personalized intervention suggestions are provided, early warning-intervention-feedback closed-loop management is supported, operation is convenient, cost is controllable, the acute exacerbation occurrence rate and the hospitalization rate of patients can be effectively reduced, and the patient experience is improved. The method is suitable for popularization and application in family and basic medical scenes.

This invention discloses a composition that can effectively soothe and repair sensitive skin, its preparation method, and its application, relating to the field of skincare products. The composition of this invention, by weight, comprises 5-18 parts β-glucan, 1-10 parts mannan, 8-15 parts yeast polypeptides, 1-10 parts sodium hyaluronate, 2-5 parts magnesium ascorbate phosphate, and 8-15 parts Scutellaria baicalensis root extract. This composition is mild and non-irritating, can quickly and effectively relieve skin sensitivity reactions, protect the skin barrier, and has good storage stability, not easily affected by environmental factors such as temperature and oxygen.

This invention relates to the fields of smart aquaculture and big data analysis technology, and discloses a smart aquaculture monitoring method and system based on big data analysis. The method includes periodically acquiring raw data from the farm's sensor network, and constructing a multi-dimensional state image through spatiotemporal synchronization and normalization processing. This image is input into a pre-trained behavior-environment decoupling analysis network, and independent behavioral feature tensors and independent environmental background field tensors are extracted in parallel. Based on these two, a coupling degree index is calculated through a cross-influence evaluation matrix to generate a comprehensive anomaly score map. According to this map, a strategy generation engine dynamically synthesizes a set of control instructions including directional airflow guidance, refined feeding, and coordinated temperature and humidity regulation. This method achieves deep separation and correlation analysis between animal behavior and aquaculture environmental factors, accurately tracing the root cause of anomalies and realizing early warning and precise systemic control.

The invention discloses an etching liquid medicine monitoring method and device, and relates to the technical field of etching liquid medicine monitoring, and the method comprises the steps: S1, collecting the concentration, temperature, pH value and conductivity parameters of an etching liquid medicine; s2, collecting temperature, humidity and illumination parameters of an etching environment; according to the method, multiple parameters including the concentration, the temperature, the pH value and the conductivity of the etching liquid medicine are collected at the same time, the correlation model is established for analysis, the problem that traditional monitoring parameters are single is solved, the state of the etching liquid medicine is comprehensively judged, etching abnormity caused by the comprehensive effect of the multiple parameters is found in time, monitoring accuracy and reliability are improved, and the monitoring cost is reduced. The quality of an etching product is guaranteed, the problem that a traditional method is poor in environmental adaptability is solved by collecting environmental parameters in real time and automatically adjusting a monitoring strategy, adaptation of the monitoring method and environmental conditions is achieved, interference of environmental factors on a monitoring result and an etching process is reduced, monitoring stability is improved, and the monitoring efficiency is improved. And the etching process is ensured to be stably carried out under wide environmental conditions.

The invention discloses a lithium sagger surface defect detection device based on visual identification, relates to the technical field of surface defect detection, and solves the technical problems of large environmental interference and single detection dimensionality in the existing technical scheme, the lithium sagger surface defect detection device comprises a main base, an inner detection assembly and an outer detection assembly, and the upper part of the main base is provided with a working box; a material conveying roller is arranged between the upper portion in the main base box and the lower portion of the working box, a mechanical arm structure is hoisted at the top end in the working box, and by arranging a cleaning air supply system with an air filtering structure, invasion of external production dust is effectively prevented. And in cooperation with a pulse dust removal unit in the inner detection assembly, floating dust on the surface of the sagger can be removed before detection, interference of environmental factors on detection precision is reduced, and the service life of a precise optical element is prolonged. According to the device, non-blind area scanning of the inner bottom face, the inner side wall and the outer side wall of the saggar is achieved through longitudinal stretching and retracting of the mechanical arm structure and circumferential movement of the track surrounding structure.

The application provides a method for efficiently breeding Actinidia chinensis, comprising the following steps: taking leaves or stem segments of Actinidia chinensis as explants, and performing culture treatment including induction culture on the explants to obtain Actinidia seedlings; wherein an induction culture medium used in the induction culture comprises an MS culture medium and an additive, the additive is selected from at least two of KT, 2,4-D, 6-BA, NAA, IBA and IAA; and in the culture medium, the content of the KT is 0.05-0.1 mg / L, the content of the 2,4-D is 0.5-1.0 mg / L, the content of the 6-BA is 0.1-0.5 mg / L, the content of the NAA is 0.5-1.0 mg / L, the content of the IBA is 0.01-0.05 mg / L, and the content of the IAA is 0.5-1.0 mg / L. The method provided by the application overcomes the influence of environmental factors on the breeding of Actinidia chinensis, and helps the protection of biodiversity.

The application relates to the technical field of environmental risk assessment, in particular to a water environment micro-plastic risk assessment method under multiple environmental factors, which comprises the following steps: constructing a micro-plastic pollution database and a multiple environmental factor resource database; pre-processing and feature engineering are performed on original data, core environmental driving factors are screened, and a standardized modeling data set is formed; a risk assessment model is constructed by fusing a harmful outcome path framework, a micro-plastic risk quantitative value is calculated by a weighted comprehensive index method or a machine learning algorithm; a final risk grade is determined in combination with a risk grade division standard and a toxic polymer adjustment mechanism, and an environmental management decision suggestion is output. The application solves the problems of single evaluation index, insufficient consideration of environmental factors, weak machine interpretation and insufficient prediction ability in the prior art, and realizes accurate and dynamic risk assessment of water environment micro-plastic pollution.

This invention discloses a composite soil conditioner and its preparation method, belonging to the field of soil conditioner preparation technology. The conditioner includes the following raw materials: biochar, composite microbial inoculum, L-erythritol, D-mannitol, isoamyl acetate, humic acid, straw residue, and sawdust. The biochar is treated with L-erythritol, isoamyl acetate, and D-mannitol to load microorganisms, increasing the microbial loading rate and ensuring good growth and reproduction speed and activity of the microorganisms. This solves the problem of microorganisms being easily affected by adverse environmental factors, reducing their effectiveness. The components in the conditioner work together to have a good comprehensive improvement effect on obstacle soils, showing great application prospects in soil improvement.

This invention discloses a fungal encapsulation agent for *Ischemicula elais* and its application in the control of pine wilt disease, belonging to the field of microbial control technology. This invention uses *Ischemicula elais* as the functional microorganism, combined with carrier materials, additives, and active ingredients to prepare a solid microbial encapsulation agent. The shelf life of *Ischemicula elais* spores at room temperature is extended from 2-3 days for traditional spore solutions to over 3-6 months, and up to 12 months under 4°C refrigeration, solving the problem of inconvenient low-temperature storage in mountainous areas. The microencapsulation components form a slow-release protective layer, preventing activity loss caused by environmental factors such as high temperature and drought.

This invention belongs to the field of myopia prevention and control technology, and relates to a method, device, and medium for myopia prevention and control based on genetic and environmental factors. Based on myopia data of each blood relative of the user to be intervened, the variant sites in the myopia-related single nucleotide polymorphism genotype, and the number of risk alleles, a myopia genetic risk index is calculated. Based on the user's daily outdoor activity time, total daily eye use time, daily near-vision time, and daily low-light eye use time over several consecutive days, an outdoor activity stability index, a near-vision load index, and an eye use light stability index are calculated, thus obtaining an environmental myopia risk index. The axial length, refractive error, myopia genetic risk index, and environmental myopia risk index of the user to be intervened are input into an adaptive Bayesian myopia risk prediction model, which outputs the myopia risk change trajectory under different myopia intervention intensities, including the predicted mean and uncertainty interval, thereby obtaining a myopia intervention strategy.

The utility model relates to the technical field of veterinary medicine powder detection equipment, in particular to a moisture determination transfer device for veterinary medicine powder. The moisture determination transfer device for the veterinary medicine powder comprises a cover body, a container and an extension part which are connected in sequence. The cover body is connected with the container through a first transition structure. The first transition structure is annularly arranged along the side wall of the cover body. The container comprises a cavity used for bearing veterinary medicine powder and a handle part. The extension part is connected with the handle part. The cover body is configured to be capable of being separated from the container from the first transition structure, rotating along the axis of the cover body and entering the cavity in the axial direction of the container to seal the cavity. According to the moisture determination transfer device for the veterinary drug powder, the sampling difficulty is reduced, the interference of environmental factors on a sample is reduced when the sample is transferred, and the accuracy of a determination result is improved.

The invention belongs to the technical field of gaseous pollutants, particularly relates to a method and a device for evaluating near-body-surface gaseous pollutant exposure of a human body, and aims to solve the problem that in the prior art, convenient, accurate and personalized risk evaluation of near-body-surface gaseous pollutant exposure level of an individual in a real life scene is difficult to realize. The method comprises the following steps: S1, pre-loading a certain amount of reference substance on an adsorption phase; s2, passively collecting gaseous pollutants at the interface of ambient air and human skin, and treating the pollutants; s3, the treated pollutants are detected and analyzed, and the equivalent air concentration of the gaseous pollutants is obtained; s4, evaluating the human skin exposure risk of the pollutants, through the reference substance preloading and dynamic correction technology, the core problem that a traditional passive sampling technology is greatly influenced by environmental factors is solved, and meanwhile pure and stable collection of the gaseous pollutants in the complex human body near-body-surface microenvironment can be achieved.

The invention relates to the technical field of remote sensing detection, in particular to a device and system for estimating cultivated land yield, and the system comprises a spectral data acquisition module, an image data acquisition module, a soil and physiological data acquisition module, an environmental parameter acquisition module, a pest and nutrition deficiency distinguishing module and a yield estimation and correction module. The device comprises a central controller and a power supply assembly for providing detection endurance, wherein the central controller is in signal connection with a spectral data acquisition assembly, an image data acquisition assembly, a soil and physiological data acquisition assembly and an environmental data acquisition assembly. According to the method, diseases and insect pests and nutrition deficiency are accurately distinguished through multi-source data acquisition and cross validation, the yield loss is corrected by dynamically integrating biological stress and environmental factors, and the defects of similar phenotype misjudgment and low estimation precision in the conventional technology are overcome.

The invention relates to an AI-based old-age-friendly indoor environment personalized map construction method. The method comprises the following steps: acquiring indoor temperature and humidity, air quality and illumination intensity parameters through an environment sensor deployed in an indoor key area; a camera with a privacy protection function and an infrared sensor combined device are used for monitoring indoor movement tracks and data of sleeping, getting up and walking behaviors of old people. Through deep analysis of the individual data of the old people, the system can accurately meet the unique demands of each old people for the indoor environment, improves the living comfort and life quality of the old people, achieves the automatic and intelligent regulation and control of the indoor environment, reduces the inconvenience of manual operation of equipment by the old people, improves the accuracy and timeliness of environment regulation and control, and improves the user experience. The indoor environment is associated with the health condition of the old people, the influence of environmental factors on health can be found in time, early warning and intervention are carried out, diseases can be prevented, and the health and safety of the old people can be guaranteed.

A strawberry gray mold early warning system and method based on multi-physiological index cooperation belong to the technical field of strawberry gray mold early warning, and solve the technical problem that the existing technology relies on a single data source, causing the model to be easily disturbed by environmental factors, and unable to comprehensively capture the early abnormal performance of gray mold in multiple physiological levels, thereby reducing the recognition accuracy of the asymptomatic latent period of strawberry gray mold. The data acquisition layer is used to collect fluorescence indicators, spectral indicators and photosynthetic indicators of strawberry plants; the feature processing layer is used to calculate the feature indexes corresponding to the fluorescence indicators, spectral indicators and photosynthetic indicators collected by the data acquisition layer respectively; the alarm judgment layer is used to judge the alarm levels corresponding to the feature indexes output by the feature processing layer respectively; and the decision fusion layer is used to make a fusion decision according to the alarm levels output by the alarm judgment layer to obtain a warning state. The present application is used to realize accurate and effective early warning of strawberry gray mold.

The present application relates to the technical field of big data, and more particularly to a community online intelligent analysis system based on health big data, which comprises an information collection module, an analysis module, a level determination module, a decision-making module and a dynamic adjustment module; the information collection module is responsible for collecting health indicators, lifestyle and environmental data of community members, and obtaining historical data; the analysis module predicts disease risk index, calculates green coverage rate, and analyzes the influence coefficient of environmental factors on risk index; the level determination module calculates the risk score level accordingly; the decision-making module formulates an initial prevention strategy according to the risk level; the dynamic adjustment module monitors health indicators and environmental data in real time, and adjusts the initial prevention strategy according to real-time data. Through intelligent analysis and management, the present application improves the accuracy of community health risk assessment and the effectiveness of response measures, and helps to improve the health level and disease prevention ability of community members.