Multi-objective synergistic regulation method for brownfield remediation aimed at creating age-friendly and health-oriented landscapes

Abstract

This invention provides a multi-objective collaborative regulation method for brownfield remediation aimed at creating age-friendly and health-oriented landscapes. It relates to the field of urban environmental governance and ecological restoration technology. The method includes: constructing a remediation objective system encompassing ecological, economic, and social dimensions; deploying a mobile modular system integrating solar energy collection, soil remediation, sensing, and communication units; collecting and transmitting soil environmental data to a central control system in real time; calculating ecological restoration and social participation indices based on a multi-objective optimization algorithm to generate a collaborative regulation strategy; and dynamically adjusting module operating parameters and spatial distribution according to the strategy. Through multi-objective collaborative decision-making and dynamic regulation of the modular system, this invention achieves brownfield ecological restoration while transforming the restored space into a therapeutic public space with safety, accessibility, and psychological comfort functions. This provides technical support for outdoor health and wellness activities for the elderly and significantly enhances the public service value and social benefits of urban brownfields.

Description

Technical Field

[0001] This invention relates to the field of urban environmental governance and ecological restoration technology, and in particular to a multi-objective synergistic regulation method for brownfield remediation aimed at the construction of age-friendly and health-oriented landscapes. Background Technology

[0002] With the accelerating aging of my country's population, the demand for age-friendly and health-supporting functions in urban public spaces is becoming increasingly urgent. Brownfields, left behind by the relocation of industrial enterprises, represent a significant portion of existing urban space that can be reused. Their rehabilitated functions should not be limited to ecological restoration but should proactively address the deeper needs of the elderly for safety, accessibility, and psychological comfort in outdoor activities. However, existing brownfield remediation technologies generally lack a systematic design for "healing public spaces," failing to organically integrate the ecological restoration process with the provision of age-friendly public services. This results in rehabilitated sites being difficult to effectively transform into high-quality environmental resources supporting health and wellness activities for the elderly.

[0003] In the fields of landscape design and public space creation, "healing landscapes" and "therapeutic environments" have been proven to have positive effects on the physical health, psychological comfort, and alleviation of social loneliness among the elderly. However, existing brownfield remediation projects often prioritize pollution control and ecological restoration, resulting in sites that lack systematic health and wellness functional designs tailored to the elderly, such as age-friendly circulation routes, distribution of rest areas, and environmental comfort control. These efforts fail to technically integrate brownfield remediation with the creation of health and wellness landscapes.

[0004] From a technical perspective, existing remediation solutions often focus on single ecological objectives, with less consideration given to the economic costs and energy consumption during the remediation process, resulting in low overall project efficiency or unsustainability. Furthermore, traditional remediation facilities are mostly fixed and one-off constructions, unable to respond to the spatial heterogeneity of brownfield contamination distribution and the dynamic evolution of the remediation process, leading to resource waste and reduced efficiency. In addition, existing models typically treat the public as passive recipients, artificially isolating the community from the remediation site, hindering the stimulation of community vitality and missing the opportunity to transform remediation spaces into platforms for public education and social interaction.

[0005] In conclusion, the field urgently needs an intelligent and collaborative solution that can integrate ecological restoration with the provision of age-friendly public services and dynamically respond to changes in the restoration process and community interactions. Summary of the Invention

[0006] To address the technical problems in existing technologies, such as the difficulty in balancing ecological and economic benefits due to a single restoration objective, low social participation leading to a disconnect between restoration results and the community, and rigid restoration systems unable to dynamically respond to changes in pollution distribution and restoration progress, this invention provides a multi-objective synergistic regulation method for brownfield restoration oriented towards the construction of age-friendly and health-oriented landscapes.

[0007] The technical solution provided by this invention is as follows: The present invention provides a multi-objective synergistic regulation method for brownfield remediation aimed at the construction of age-friendly and health-oriented landscapes, comprising: S1: Multi-objective system construction: Determine multiple optimization objectives for brownfield remediation, including ecological, economic, social and health-related objectives. Among them, ecological objectives include soil purification efficiency and vegetation coverage; economic objectives include remediation costs and energy consumption; social objectives include community participation and public education value; and health-related objectives include age-friendly safety and health-related service effectiveness. S2: Modular remediation system deployment: Deploy multiple mobile landscape remediation modules in brownfield areas. Each module includes a solar energy acquisition unit, a soil remediation unit, a sensor unit, and a communication unit. The sensor unit is used to collect soil environmental data, including soil pollution concentration, pH value, humidity, and temperature. The communication unit is used for data transmission. The modules are spatially arranged based on the initial pollution distribution map and support independent operation or network collaboration. S3: Data Acquisition and Transmission: Soil environmental data is acquired in real time through the sensor unit and transmitted to the central control system through the communication unit; S4: Multi-objective collaborative decision-making: Based on the multiple optimization objectives and real-time data, the ecological restoration index, social participation index, and health and wellness suitability index are calculated according to predefined rules. The ecological restoration index is calculated based on soil pollution concentration, restoration time, and energy consumption data to reflect the balance between soil purification effect and energy efficiency. The social participation index is calculated based on the number of community participations, restoration area coverage, and public satisfaction scores to reflect the correlation between community interaction and restoration progress. The health and wellness suitability index is calculated based on one or more of the following: rest area coverage, nighttime lighting uniformity, and ground flatness to reflect the age-friendly service level of the restoration site. Based on the above indices, a collaborative control strategy is generated, which includes adjustment of working parameters and optimization of module spatial distribution. S5: Repair Execution and Dynamic Adjustment: Based on the collaborative control strategy, control the working parameters and spatial distribution of the landscape restoration module. The working parameters include ultraviolet irradiation intensity, infrared irradiation time, and energy allocation. The spatial distribution includes the movement and reorganization of the module. Adjust the strategy in real time based on feedback data to optimize multiple objectives.

[0008] The beneficial effects of the technical solution provided by this invention include at least the following: (1) This invention constructs a comprehensive evaluation system covering ecological, economic and social goals, and combines real-time environmental data with multi-objective optimization algorithms to achieve synergistic regulation of the ecological restoration index and the social participation index. While ensuring the pollution purification effect, it significantly optimizes energy utilization efficiency and restoration costs, breaking the limitations of traditional single-objective orientation.

[0009] (2) This invention achieves precise delivery of repair resources and real-time optimization of spatial layout by using a mobile, modular repair unit that supports network collaboration and a dynamic adjustment algorithm. This overcomes the shortcomings of slow response of traditional fixed facilities and significantly improves repair efficiency and resource utilization.

[0010] (3) This invention deeply integrates brownfield restoration with the creation of health and wellness landscapes, achieving the systematic construction of age-friendly healing spaces. By incorporating the regional population structure and the activity characteristics of the elderly into a multi-objective decision-making system, and combining the dynamic control of the spatial layout of the modular system, slow-moving paths, rest nodes, and environmental comfort conditions that meet the needs of the elderly can be precisely formed, so that the restored site has both ecological safety and health and wellness service functions. At the same time, the interactive platform's visualization display and public participation mechanism effectively enhance the effectiveness of community interaction and environmental education, transforming brownfields from a single ecological governance object into an active urban space that carries age-friendly health and wellness landscapes. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating a multi-objective synergistic regulation method for brownfield remediation aimed at constructing age-friendly and health-oriented landscapes, provided in an embodiment of the present invention. Detailed Implementation

[0013] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0014] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0015] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0016] In embodiments of the present invention, sometimes the subscript is as follows: It may be mistakenly written as a non-subscript form such as W1. When the distinction is not emphasized, the meaning they express is the same.

[0017] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0018] Reference manual attached Figure 1 The diagram illustrates a flowchart of a multi-objective synergistic regulation method for brownfield remediation aimed at constructing age-friendly and health-oriented landscapes, provided by an embodiment of the present invention.

[0019] This invention provides a multi-objective synergistic regulation method for brownfield remediation aimed at constructing age-friendly and health-oriented landscapes. The processing flow may include the following steps: S1: Multi-objective system construction: Determine multiple optimization objectives for brownfield remediation, including ecological, economic, social and health-related objectives. Among them, ecological objectives include soil purification efficiency and vegetation coverage; economic objectives include remediation costs and energy consumption; social objectives include community participation and public education value; and health-related objectives include age-friendly safety and health-related service effectiveness.

[0020] In the specific implementation process, it is first necessary to clarify the multiple optimization target systems involved in urban brownfield remediation. Ecological targets are mainly reflected through soil purification efficiency and vegetation cover. Soil purification efficiency focuses on the rate of pollutant degradation and the degree of restoration of soil health, while vegetation cover reflects the level of ecosystem reconstruction. Economic targets focus on balancing remediation costs and energy consumption. Remediation costs include equipment investment, operation and maintenance, and material costs, while energy consumption involves the utilization efficiency of renewable energy sources such as solar energy. Social targets emphasize community participation and public education value. Community participation is measured by the frequency of resident interaction and the scale of activities, while public education value is reflected in the improvement of environmental awareness and the effectiveness of knowledge dissemination. Based on this, health and wellness service targets can be further extended. This involves creating age-friendly pathways, rest nodes, and environmental comfort conditions that conform to the activity characteristics of the elderly through the coordinated control of modular spatial layout and operational parameters, technically integrating brownfield remediation with the creation of health and wellness landscapes. The determination of these targets relies on historical remediation data, regional environmental standards, and social needs analysis to ensure that the target system comprehensively covers ecological, economic, and social dimensions.

[0021] S2: Modular Remediation System Deployment: Multiple mobile landscape remediation modules are deployed in brownfield areas. Each module includes a solar energy acquisition unit, a soil remediation unit, a sensor unit, and a communication unit. The sensor unit is used to collect soil environmental data, including soil pollution concentration, pH value, humidity, and temperature. The communication unit is used for data transmission. The modules are spatially arranged based on the initial pollution distribution map and support independent operation or network collaboration.

[0022] The wireless communication protocol between the modules is not limited to ZigBee. In scenarios requiring longer transmission distances or higher data throughput, the communication unit can adopt the LoRa protocol to significantly reduce power consumption and achieve long-distance data transmission exceeding 1 kilometer; or in urban scenarios requiring wide-area coverage, a 4G / 5G cellular communication module can be integrated to achieve direct data exchange with the cloud control center. Furthermore, the connectors between modules can adopt magnetic interfaces or physical snap-fit ​​designs to achieve "one-click" quick docking and mechanical locking, ensuring structural stability in the combined configuration. The underground replacement module ("black box") can be equipped with a status indicator LED; when the biochar adsorption inside is saturated or the slow-release agent is depleted, the LED automatically changes from green to red, providing maintenance personnel with an intuitive replacement prompt.

[0023] The deployment of the modular remediation system is based on spatial planning using an initial pollution distribution map, ensuring that the location of each landscape remediation module matches the degree of pollution. Each module integrates a solar energy harvesting unit, a soil remediation unit, a sensor unit, and a communication unit. The solar energy harvesting unit uses a flexible thin-film solar panel design, which can efficiently convert and store solar energy; the soil remediation unit is equipped with ultraviolet and infrared irradiation devices for soil purification and ecological optimization; the sensor unit is responsible for collecting environmental parameters such as soil pollution concentration, pH value, humidity, and temperature; and the communication unit achieves data exchange through a wireless transmission protocol. The modules can operate independently or in a network. During deployment, the spacing and orientation of the modules are adjusted according to the site shape and pollution gradient to maximize the remediation coverage and energy harvesting efficiency.

[0024] S3: Data Acquisition and Transmission: Soil environmental data is acquired in real time through the sensor unit and transmitted to the central control system through the communication unit.

[0025] The sensor unit monitors soil environmental data in real time, including key indicators such as soil pollution concentration, pH value, humidity, and temperature. A high-frequency sampling strategy is employed during data acquisition to ensure the timeliness and accuracy of the information.

[0026] To achieve this, the sensor unit needs to possess sufficient measurement accuracy. For example, the accuracy of a soil pollution concentration sensor is preferably ±0.1 mg / kg, the accuracy of a pH sensor is preferably ±0.1, the accuracy of a temperature sensor is, for example, ±0.5°C, and the accuracy of a humidity sensor is, for example, ±2%RH. Combining high-frequency sampling with sensors of this level of accuracy effectively ensures the reliability of the data upon which subsequent decisions are based.

[0027] The collected data is transmitted to the central control system via a communication unit. This unit, based on a wireless network protocol, establishes a data transmission channel with anti-interference and low-power characteristics. The central control system performs preliminary verification and storage of the received data, providing a complete and reliable data foundation for subsequent decision-making. The entire transmission process is automated, requiring no manual intervention and ensuring the continuity and stability of the data stream.

[0028] S4: Multi-objective collaborative decision-making: Based on the multiple optimization objectives and real-time data, the ecological restoration index, social participation index, and health and wellness suitability index are calculated according to predefined rules. The ecological restoration index is calculated based on soil pollution concentration, restoration time, and energy consumption data to reflect the balance between soil purification effect and energy efficiency. The social participation index is calculated based on the number of community participations, restoration area coverage, and public satisfaction scores to reflect the correlation between community interaction and restoration progress. The health and wellness suitability index is calculated based on one or more of the following: rest area coverage, nighttime lighting uniformity, and ground flatness to reflect the age-friendly service level of the restoration site. Based on the above indices, a collaborative control strategy is generated, which includes adjustment of working parameters and optimization of module spatial distribution.

[0029] The central control system calculates the ecological restoration index and the social participation index based on real-time data and predefined rules. The ecological restoration index reflects the comprehensive balance between soil purification effectiveness and energy efficiency by integrating data on soil pollution concentration, remediation time, and energy consumption. The social participation index assesses the correlation between community interaction and remediation progress based on the number of community participations, remediation area coverage, and public satisfaction scores. When generating control strategies, the system can further incorporate regional population structure characteristics (such as the distribution of the elderly population) to prioritize and optimize the spatial layout of modules to form safe and accessible rest nodes, thereby integrating age-friendly needs into the multi-objective decision-making process.

[0030] For example, the generation of the aforementioned collaborative regulation strategy is not limited to multi-objective genetic algorithms. In an alternative embodiment, a multi-objective particle swarm optimization algorithm can be used, with its inertia weight employing a linear decreasing strategy, gradually decreasing from 0.9 to 0.4. Both the individual cognitive factor and the social cognitive factor are set to 2.0. By simulating the social behavior of the particle swarm, premature convergence can be effectively avoided, and optimization efficiency in complex pollution scenarios can be improved. In another embodiment, NSGA-II (a non-dominated sorting genetic algorithm with an elitist strategy) can also be used as the optimization engine. Through fast non-dominated sorting and crowding distance calculation, it can efficiently handle the trade-off between the ecological restoration index and the social participation index, making it particularly suitable for restoration scenarios where there is a high degree of conflict between objectives.

[0031] After the index calculation is completed, the system generates a coordinated regulation strategy, which covers both the adjustment of working parameters and the optimization of module spatial distribution, ensuring that ecological, economic and social goals are synergistically optimized during the decision-making process. Strategy generation relies on a multi-objective optimization algorithm to dynamically adapt to environmental changes and restoration needs.

[0032] S5: Repair Execution and Dynamic Adjustment: Based on the collaborative control strategy, control the working parameters and spatial distribution of the landscape restoration module. The working parameters include ultraviolet irradiation intensity, infrared irradiation time, and energy allocation. The spatial distribution includes the movement and reorganization of the module. Adjust the strategy in real time based on feedback data to optimize multiple objectives.

[0033] According to the coordinated control strategy, the central control system instructs the landscape restoration modules to adjust their working parameters and spatial distribution. Working parameters include ultraviolet radiation intensity, infrared radiation duration, and energy allocation, which are adaptively adjusted based on real-time soil data. Spatial distribution involves the movement and reorganization of modules, optimizing module locations through path planning algorithms while also considering age-friendly circulation design within the site. This ensures that the restored module layout naturally forms slow-moving paths and rest nodes that conform to the activity habits of the elderly. During execution, the system continuously collects feedback data, including changes in environmental parameters and restoration progress, and updates the control strategy in real time accordingly. This dynamic adjustment mechanism ensures that the restoration process always evolves towards a multi-objective optimal solution, improving overall restoration efficiency and sustainability.

[0034] The adjustment of the ultraviolet and infrared irradiation cycle is not limited to continuous or intermittent modes. In an optimized embodiment, the system can employ adaptive pulse irradiation technology based on the real-time calculated pollutant degradation kinetic curve: that is, when the pollutant degradation rate enters a plateau phase, it automatically switches to a high-frequency short pulse mode to break through mass transfer resistance, reactivate the degradation process, thereby improving overall purification efficiency and reducing energy consumption.

[0035] In one possible implementation, the method for calculating the ecological restoration index in step S4 includes the following steps: S401: Obtain soil pollution concentration data, remediation time data, and energy consumption data; S402: Calculate the Ecological Restoration Index (ERI) according to the following formula:

[0036] Where T represents the total repair time, in days. C(t) represents the initial soil contamination concentration in mg / kg, and C(t) represents the soil contamination concentration at time t in mg / kg. Let E(t) represent the maximum permissible energy consumption in kilowatt-hours (kWh), and let E(t) represent the energy consumption at time t in kilowatt-hours (kWh). α and β are adjustment coefficients. , β=1-α.

[0037] The calculation of the ecological restoration index is achieved through an algorithm module built into the central control system. The system first acquires continuous data on soil pollution concentration changes over time from sensor units, while simultaneously recording energy consumption values ​​at various time points during the restoration process. The algorithm module processes this time-series data using an integral calculation method, normalizing the difference between the initial and real-time pollution concentrations and then weighting and fusing it with the energy consumption efficiency index. The adjustment coefficient is automatically calculated based on the proportional relationship between the initial pollutant concentration level and the system's maximum energy supply capacity.

[0038] For example, the physical meaning of coefficient α can be interpreted as the relative importance of the initial concentration of pollutants in remediation decisions; a larger value indicates that the system is more inclined to prioritize pollution remediation. Correspondingly, coefficient β characterizes the weight given to energy efficiency. As a preferred implementation, the determination criteria, in addition to basic proportional relationships, can also be calibrated through regression analysis of historical remediation data. For example, in one specific embodiment, when... When the concentration is above 100 mg / kg, α can be between 0.6 and 0.8; when When the value exceeds 50 kWh, β is adjusted accordingly to balance the optimization objective. Optionally, this dynamic determination mechanism allows the ecological restoration index to more flexibly adapt to the site requirements of different pollution levels.

[0039] The integral calculation process covers the entire time period from the start of the repair to the current moment, and the final output index value can comprehensively reflect the balance between pollution removal effect and energy utilization efficiency per unit time.

[0040] In one possible implementation, the method for calculating the social participation index in step S4 includes the following steps: S403: Obtain community participation counts, repair area coverage, and public satisfaction ratings; S404: Calculate the Social Participation Index (SPI) according to the following formula:

[0041] in, This indicates the number of times the community participated, expressed in times. This indicates the coverage rate of the repaired area, in square meters. This represents the total area, in square meters. The public satisfaction rating is obtained through a questionnaire and ranges from 0 to 10, including γ, δ, and These are weighting coefficients, and γ = 1 / 3, δ = 1 / 3, =1 / 3, or dynamically adjusted based on regional social characteristics.

[0042] The social participation index is calculated using a community participation management module integrated into the central control system. This module continuously records the number of times community members participate in restoration activities through an interactive platform, while also acquiring data on the area coverage of the restoration area. Public satisfaction scores are collected through an embedded questionnaire system using a ten-point scoring system. During the calculation, a logarithmic function is used to smooth out data discrepancies in the number of participations, and the area coverage is expressed as a percentage. Satisfaction scores are directly incorporated into the calculation system. The weighting coefficients for each sub-indicator are configured based on a regional social characteristics database to ensure that the index accurately reflects the actual contribution of community participation to the restoration process.

[0043] Optionally, the determination of the adjustment coefficients α and β can be based not only on the ratio of initial concentration to maximum energy consumption, but also on the biotoxicity data of the pollutants as correction factors. For example, for highly biotoxic pollutants such as polycyclic aromatic hydrocarbons, even if their initial concentration... If the score is not high, a higher purification priority can be assigned by increasing the α value to above 0.7. Similarly, the weighting coefficients γ, δ, and ε of the social participation index can be dynamically adjusted based on community population structure data; for example, in communities with a high proportion of elderly people and children, the public satisfaction score can be appropriately increased to reflect care for vulnerable groups. The weight ε is above 0.4.

[0044] In one possible implementation, the method for calculating the health and wellness suitability index in step S4 includes the following steps: Obtain data on rest area coverage, nighttime lighting uniformity, and ground flatness; The Health and Wellness Suitability Index (HAI) is calculated using the following formula:

[0045] Where R represents the rest area coverage rate, expressed as a percentage. λ represents the maximum rest area coverage, L represents the uniformity of nighttime lighting with a value range of 0-1, F represents the ground flatness score with a value range of 0-10, and λ, μ, and ν are weighting coefficients, and λ+μ+ν=1.

[0046] Rest stop coverage is calculated using the number and distribution area of ​​rest stops in the spatial layout of the interactive platform's statistical module. Nighttime lighting uniformity is assessed using light intensity data collected by sensor units, and ground flatness is obtained through terrain data collected by sensor units or manual inspection scoring. The weighting coefficients λ, μ, and ν can be dynamically adjusted according to the site's functional positioning and the needs of the elderly population. For example, the μ value can be appropriately increased in scenarios that emphasize nighttime use, while the ν value can be increased in scenarios that emphasize pedestrian safety.

[0047] In one possible implementation, when deploying the landscape restoration module in step S2, the modules form a self-organizing network through a wireless communication protocol, and the distance and connection method between the modules are dynamically optimized based on real-time pollution data to enhance data sharing and restoration collaboration.

[0048] The networking communication between landscape restoration modules adopts a self-organizing network architecture based on the ZigBee protocol. Each module's communication unit possesses routing and terminal device functions, enabling it to automatically identify adjacent modules and establish a mesh network topology. The network dynamically adjusts transmission paths and signal strength based on real-time pollution data. When a module detects a change in pollution concentration, the network re-optimizes the communication connections between modules. This dynamic networking mechanism ensures efficient data sharing among modules and provides a stable communication foundation for collaborative restoration. Network maintenance is entirely autonomous, requiring no external intervention.

[0049] In one possible implementation, the soil environmental data collected in step S3 also includes heavy metal content and organic pollutant concentration, and noise is removed through a data filtering algorithm to ensure data accuracy.

[0050] The soil environmental data collection process includes specific monitoring of heavy metal content and organic pollutant concentrations. The sensor unit is equipped with electrochemical sensors and a spectroscopic analysis module, enabling the quantitative detection of common heavy metals such as lead, cadmium, and chromium, as well as organic pollutants such as polycyclic aromatic hydrocarbons (PAHs). The collected raw data is processed using a Kalman filter algorithm to effectively eliminate interference from environmental noise and measurement errors. The filtered data is then standardized and calibrated to ensure the comparability of data collected by different sensors. This data processing method significantly improves the accuracy and reliability of environmental monitoring data.

[0051] In one possible implementation, when generating the collaborative regulation strategy in step S4, a multi-objective genetic algorithm is used for iterative optimization to simultaneously maximize the ecological restoration index and the social participation index.

[0052] The generation of the coordinated regulation strategy employs a multi-objective genetic algorithm as the core optimization engine. This algorithm uses the ecological restoration index and social participation index as dual objective functions, iteratively searching for the optimal solution set through operations such as selection, crossover, and mutation.

[0053] Those skilled in the art can configure the algorithm parameters according to the complexity of the actual problem. For example, the crossover rate can preferably be set in the range of 0.7 to 0.9 to maintain population diversity; the mutation rate can be set in the range of 0.01 to 0.1 to avoid premature convergence. Preferably, the selection operation adopts the tournament selection method, with a scale of, for example, 2 to 4 individuals. Optionally, these parameters can be fine-tuned based on the specific conditions of the remediation site. For example, in areas with high spatial heterogeneity of contaminated space, the mutation rate can be appropriately increased, for example, to the range of 0.05 to 0.15, to enhance the global search capability.

[0054] The algorithm population size is set to 100 individuals, each representing a set of possible regulatory strategies. During iteration, the algorithm performs non-dominated sorting of individuals based on the objective function value and calculates crowding distance to maintain population diversity. After 100 generations of evolution, the algorithm outputs a Pareto optimal solution set, from which the collaborative regulatory strategy that best meets the current repair needs is selected.

[0055] In one possible implementation, when controlling the operating parameters of the landscape restoration module in step S5, the irradiation cycle of ultraviolet and infrared rays is adaptively adjusted according to the soil type and pollution level. The irradiation cycle includes continuous mode and intermittent mode.

[0056] The landscape restoration module's operating parameters are controlled using an adaptive adjustment mechanism based on soil characteristics. The control unit automatically selects the ultraviolet and infrared irradiation cycle modes based on soil type and pollution level characteristics detected by sensors. For clay soils and areas with high pollution concentrations, the system employs a continuous irradiation mode to ensure sufficient energy input; for sandy soils and areas with low pollution concentrations, an intermittent irradiation mode is used to balance remediation effectiveness and energy consumption. The switching between different irradiation modes is dynamically determined based on real-time monitoring of pollutant degradation rates, ensuring the remediation process is always in an optimal state.

[0057] In one possible implementation, when dynamically adjusting the spatial distribution of the modules in step S5, the module movement path is calculated based on the gradient descent algorithm to minimize pollution residue and maximize coverage area.

[0058] The dynamic adjustment of the module spatial distribution employs a gradient descent algorithm for path planning. The algorithm uses the amount of residual contamination as the objective function, determining the gradient direction by calculating the partial derivative of the objective function with respect to the module position. In each iteration, the module moves a certain step size along the opposite direction of the gradient, gradually approaching the minimum point of residual contamination. The algorithm also considers the maximization of coverage area, introducing an area constraint into the objective function. This optimization method ensures that the module movement path effectively reduces residual contamination while maximizing the remediation coverage.

[0059] In one possible implementation, the method further includes step S6: visualization of restoration effects, displaying the ecological restoration index, social participation index and restoration progress in real time through an interactive platform, and generating a multi-objective assessment report.

[0060] The visualization of restoration effects is achieved through a separate interactive platform. This platform acquires real-time data on ecological restoration indices, social participation indices, and restoration progress from the central control system and displays this data dynamically in chart form. The platform uses WebGL technology to render 3D scenes, intuitively displaying changes in pollution distribution and the operational status of modules. Simultaneously, the platform automatically generates multi-objective assessment reports, including modules for restoration efficiency analysis, resource utilization assessment, and social benefit statistics. It can also be expanded to display age-friendly service indicators (such as rest area coverage, nighttime lighting uniformity, and accessibility continuity), facilitating managers' evaluation of the effectiveness of health and wellness services after site renovation. All visualized data supports multi-terminal access, allowing different stakeholders to promptly understand the restoration progress.

[0061] In one possible implementation, the solar energy harvesting unit of the landscape restoration module employs flexible thin-film solar panels and is integrated with a supercapacitor to enable rapid energy storage and release to support nighttime restoration operations.

[0062] The energy system of the landscape restoration module adopts an integrated design of flexible thin-film solar panels and supercapacitors. The flexible thin-film solar panels are made of amorphous silicon, which is lightweight and flexible, and can adapt to various installation surfaces.

[0063] As a typical configuration, each module's solar harvesting unit has a power output, for example, between 100W and 200W, and under standard sunlight conditions, the daily power generation is preferably between 0.5 and 1 kWh. The integrated supercapacitor has a capacity, for example, selectable from 1000F to 2000F, allowing this configuration to support continuous operation for 4 to 8 hours during overnight repair work. This specification range strikes a good balance between energy supply and module portability, making it suitable for most urban brownfield scenarios.

[0064] Supercapacitors, as energy storage units, possess rapid charging and discharging capabilities and long cycle life. The energy management system intelligently allocates electrical energy according to the needs of the repair operation, prioritizing the conversion of solar energy into electrical energy for storage during the day and releasing electrical energy at night to support the operation of ultraviolet and infrared irradiation devices. This design ensures that the repair operation can be carried out continuously around the clock, unaffected by sunlight conditions.

[0065] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following: (1) This invention constructs a comprehensive evaluation system covering ecological, economic and social goals, and combines real-time environmental data with multi-objective optimization algorithms to achieve synergistic regulation of the ecological restoration index and the social participation index. While ensuring the pollution purification effect, it significantly optimizes energy utilization efficiency and restoration costs, breaking the limitations of traditional single-objective orientation.

[0066] (2) This invention achieves precise delivery of repair resources and real-time optimization of spatial layout by using a mobile, modular repair unit that supports network collaboration and a dynamic adjustment algorithm. This overcomes the shortcomings of slow response of traditional fixed facilities and significantly improves repair efficiency and resource utilization.

[0067] (3) This invention deeply integrates brownfield restoration with the creation of health and wellness landscapes, achieving the systematic construction of age-friendly healing spaces. By incorporating the regional population structure and the activity characteristics of the elderly into a multi-objective decision-making system, and combining the dynamic control of the spatial layout of the modular system, slow-moving paths, rest nodes, and environmental comfort conditions that meet the needs of the elderly can be precisely formed, so that the restored site has both ecological safety and health and wellness service functions. At the same time, the interactive platform's visualization display and public participation mechanism effectively enhance the effectiveness of community interaction and environmental education, transforming brownfields from a single ecological governance object into an active urban space that carries age-friendly health and wellness landscapes.

[0068] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0069] The following points need to be explained: (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0070] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0071] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0072] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-objective synergistic regulation method for brownfield remediation aimed at constructing age-friendly and health-oriented landscapes, characterized in that, include: S1: Multi-objective system construction: Determine multiple optimization objectives for brownfield remediation, including ecological, economic, social and health-related objectives. Among them, ecological objectives include soil purification efficiency and vegetation coverage; economic objectives include remediation costs and energy consumption; social objectives include community participation and public education value; and health-related objectives include age-friendly safety and health-related service effectiveness. S2: Modular remediation system deployment: Deploy multiple mobile landscape remediation modules in brownfield areas. Each module includes a solar energy acquisition unit, a soil remediation unit, a sensor unit, and a communication unit. The sensor unit is used to collect soil environmental data, including soil pollution concentration, pH value, humidity, and temperature. The communication unit is used for data transmission. The modules are spatially arranged based on the initial pollution distribution map and support independent operation or network collaboration. S3: Data Acquisition and Transmission: Soil environmental data is acquired in real time through the sensor unit and transmitted to the central control system through the communication unit; S4: Multi-objective collaborative decision-making: Based on the multiple optimization objectives and real-time data, the ecological restoration index, social participation index, and health and wellness suitability index are calculated according to predefined rules. The ecological restoration index is calculated based on soil pollution concentration, restoration time, and energy consumption data to reflect the balance between soil purification effect and energy efficiency. The social participation index is calculated based on the number of community participations, restoration area coverage, and public satisfaction scores to reflect the correlation between community interaction and restoration progress. The health and wellness suitability index is calculated based on one or more of the following: rest area coverage, nighttime lighting uniformity, and ground flatness to reflect the age-friendly service level of the restoration site. Based on the above indices, a collaborative control strategy is generated, which includes adjustment of working parameters and optimization of module spatial distribution. S5: Repair Execution and Dynamic Adjustment: Based on the collaborative control strategy, control the working parameters and spatial distribution of the landscape restoration module. The working parameters include ultraviolet irradiation intensity, infrared irradiation time, and energy allocation. The spatial distribution includes the movement and reorganization of the module. Adjust the strategy in real time based on feedback data to optimize multiple objectives.

2. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, The method for calculating the ecological restoration index in step S4 includes the following steps: S401: Obtain soil pollution concentration data, remediation time data, and energy consumption data; S402: Calculate the Ecological Restoration Index (ERI) according to the following formula: ； Where T represents the total repair time, in days. C(t) represents the initial soil contamination concentration in mg / kg, and C(t) represents the soil contamination concentration at time t in mg / kg. Let E(t) represent the maximum permissible energy consumption in kilowatt-hours (kWh), and let E(t) represent the energy consumption at time t in kilowatt-hours (kWh). α and β are adjustment coefficients. , β=1-α.

3. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, The method for calculating the social participation index in step S4 includes the following steps: S403: Obtain community participation counts, repair area coverage, and public satisfaction ratings; S404: Calculate the Social Participation Index (SPI) according to the following formula: ； in, This indicates the number of times the community participated, expressed in times. This indicates the coverage area of ​​the repaired area, in square meters. This represents the total area, in square meters. The public satisfaction rating is obtained through a questionnaire and ranges from 0 to 10, including γ, δ, and These are weighting coefficients, and γ = 1 / 3, δ = 1 / 3, =1 / 3, or dynamically adjusted based on regional social characteristics.

4. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, When deploying the landscape restoration module in step S2, the modules form a self-organizing network through a wireless communication protocol, and the distance and connection method between the modules are dynamically optimized based on real-time pollution data to enhance data sharing and restoration collaboration.

5. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, The soil environmental data collected in step S3 also includes heavy metal content and organic pollutant concentration, and noise is removed through a data filtering algorithm to ensure data accuracy.

6. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, In step S4, when generating the collaborative regulation strategy, a multi-objective genetic algorithm is used for iterative optimization to simultaneously maximize the ecological restoration index and the social participation index.

7. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, In step S5, when controlling the working parameters of the landscape restoration module, the irradiation cycle of ultraviolet and infrared rays is adaptively adjusted according to the soil type and pollution level. The irradiation cycle includes continuous mode and intermittent mode.

8. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, In step S5, when dynamically adjusting the spatial distribution of the modules, the module movement path is calculated based on the gradient descent algorithm to minimize pollution residue and maximize coverage area.

9. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, The method also includes step S6: visualization of restoration effects, which displays the ecological restoration index, social participation index and restoration progress in real time through an interactive platform, and generates a multi-objective assessment report.

10. The multi-objective synergistic regulation method for brownfield remediation oriented towards the construction of age-friendly and health-oriented landscapes according to claim 1, characterized in that, The solar energy collection unit of the landscape restoration module uses flexible thin-film solar panels and is integrated with supercapacitors to achieve rapid energy storage and release, supporting nighttime restoration operations.

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