Construction site dust real-time monitoring and automatic linkage treatment system

Abstract

The invention discloses a real-time monitoring and automatic linkage treatment system for construction site dust. The real-time monitoring and automatic linkage treatment system comprises a multi-parameter monitoring module, an edge computing controller, a linkage treatment execution unit and a data communication and cloud platform. The multi-parameter monitoring module is integrated with a lifting adjusting mechanism and an intelligent dust cleaning system, and collects the dust concentration and environmental parameters of a construction area in real time; the edge computing controller is internally provided with a self-adaptive dust source tracking algorithm to realize data processing and intelligent decision making; the linkage treatment execution unit comprises an intelligent fog gun, a dustproof sky screen and a spraying system, and automatically starts treatment measures according to the control instruction; the data communication and the cloud platform realize remote monitoring and closed-loop management through multi-protocol compatibility and AI visual identification. The problems of inaccurate monitoring, response lagging, extensive treatment and the like in traditional flying dust monitoring treatment are solved, and accurate monitoring and efficient treatment of construction site dust are achieved.

Description

Technical Field

[0001] This invention relates to the field of environmental management technology in construction sites, and in particular to a real-time monitoring and automatic linkage management system for dust at construction sites. Background Technology

[0002] Dust pollution generated during construction has become a significant factor affecting urban air quality. Dust refers to airborne particulate matter of a certain size range formed when loose particulate matter from the ground enters the ambient air under natural or human influence. It is mainly divided into soil dust, construction dust, road dust, and stockpile dust.

[0003] Currently, common dust monitoring technologies both domestically and internationally mainly include the filtration weighing method, beta-ray method, light scattering method, charge induction method, and micro-oscillation balance method. Each of these technologies has its own advantages and disadvantages in practical applications: the beta-ray method involves large equipment size and high cost; while the light scattering method is small and low-cost, its monitoring accuracy is easily affected by environmental factors. Furthermore, traditional dust monitoring relies heavily on manual inspections and paper records, resulting in data lag, difficulty in obtaining evidence, and inefficient response.

[0004] In terms of dust control, existing technologies mainly include single control measures such as water spraying, dust suppression cannons, and dust netting. These measures often rely on manual experience and lack real-time linkage with monitoring data, resulting in low accuracy, poor timeliness, and serious waste of water resources. For example, traditional dust cannon equipment often needs to be manually activated, cannot automatically adjust according to changes in dust concentration, and has a limited coverage area under wind interference.

[0005] In recent years, with the development of IoT and AI technologies, some intelligent dust monitoring systems have emerged. However, these systems still have many limitations: monitoring equipment is susceptible to harsh construction site environments, displays are prone to dust accumulation, detection height is fixed and limited, detection modules lack protection, and maintenance is inconvenient; inter-system protocols are incompatible, making it difficult to achieve multi-device collaboration; and the governance response mechanism is simplistic, lacking multi-measure linkage control.

[0006] Therefore, developing a construction site dust monitoring and control system that can achieve real-time and accurate monitoring, multi-device collaborative linkage, and adaptability to environmental changes has become an urgent need for the industry. Summary of the Invention

[0007] The purpose of this invention is to provide a real-time monitoring and automatic linkage control system for dust at construction sites, which solves the problems of disconnect between monitoring and control, delayed response, and low control accuracy in the existing technology, and realizes real-time and accurate monitoring and automatic linkage control of dust pollution.

[0008] To solve the above problems, the present invention adopts the following technical solution: This invention provides a real-time monitoring and automatic linkage control system for dust at construction sites, including a multi-parameter monitoring module, an edge computing controller, a linkage control execution unit, and a data communication and cloud platform.

[0009] The multi-parameter monitoring module is used to collect real-time dust concentration data and environmental parameters in the construction area, including a PM2.5 / PM10 sensor based on light scattering, a noise sensor, a temperature and humidity sensor, and an anemometer. The module employs a lifting and adjusting mechanism; the support frame consists of a support cylinder and a connecting cylinder, and the height is adjusted via a threaded connecting rod. A gear-driven lifting power component is located at the bottom, allowing for flexible adaptation of the detection height from the ground to high altitudes. Simultaneously, the module integrates an intelligent dust removal system, including a display screen housed in the mounting box, a liftable baffle, a dust removal plate that fits the display screen, and a power component that drives the baffle's lifting and lowering. A magnetic structure enables quick assembly and disassembly of the dust removal plate, effectively solving the problem of dust accumulation on the display screen caused by construction site dust.

[0010] The edge computing controller employs an ARM embedded system with a built-in adaptive dust source tracking algorithm. It integrates laser scattering particle detection technology based on Mie scattering theory and magnetic attitude angle measurement technology to achieve real-time localization of dust sources and prediction of diffusion paths. The controller also employs a data cleaning and completion mechanism, using a sliding window algorithm to remove abnormal sensor data and an LSTM neural network to predict missing data, ensuring the continuity of the monitoring curve.

[0011] The coordinated dust control execution unit includes an intelligent fog cannon device, a dust suppression canopy system, and a spray dust suppression system. The dust suppression canopy system consists of multiple motorized canopy units that can automatically open and close according to vertical transportation needs, achieving full coverage of the pit operation space and transforming "open-air operations" into "indoor operations." The execution unit automatically activates corresponding dust control measures based on control commands to achieve precise dust suppression.

[0012] The data communication and cloud platform transmit data to the cloud via a CAN-BUS wireless gateway and 4G / 5G networks, supporting remote monitoring and data analysis. The system supports multiple protocols, including Modbus TCP / RTU, OPC UA, DL / T 645, and ONVIF, enabling seamless access for devices of different brands and types. The cloud platform integrates AI visual recognition capabilities, automatically identifying violations such as uncovered bare soil and malfunctioning fog cannons through high-altitude cameras and deep learning technology, and generating structured early warning information.

[0013] In addition, the system also includes a diffusion supervision unit, which is used to analyze the amount of air dust around the spraying equipment, judge the dust reduction effect according to the analysis result, and generate an abnormal reminder when the effect is insufficient. The system adopts a closed-loop management mechanism to achieve full-chain governance of real-time monitoring, instant push, time-limited disposal, and closed-loop feedback, and pushes warning information to the construction site supervisor through a mobile terminal. The present invention adopts a multi-source monitoring data fusion and intelligent decision-making mechanism. The system collects multi-source information such as dust concentration and meteorological data through a multi-parameter monitoring module, uses an edge computing controller for data fusion analysis, and combines an adaptive dust source tracking algorithm to achieve accurate prediction of dust diffusion laws and intelligent decision-making on governance measures. It breaks through the limitations of traditional single-parameter monitoring, improves the monitoring accuracy and reliability through multi-source data fusion; adopts an edge computing and cloud collaboration architecture to achieve local real-time processing and in-depth cloud analysis of data.

[0014] The present invention uses dust source tracking and adaptive governance technology. Based on the laser scattering particle detection technology of Mie scattering theory combined with magnetic induction attitude angle measurement, it real-time locates the dust source position and predicts the diffusion path; dynamically adjusts the parameters of the governance equipment through a control algorithm to achieve precise tracking and governance of the dust source. It solves the problem of limited coverage of traditional fixed governance equipment, realizes an adaptive dust reduction mode of "the dust source moves and the governance follows", and significantly improves the governance efficiency.

[0015] The present invention adopts multi-device protocol compatibility and linkage control. Through multi-protocol transparent transmission and protocol conversion technology, it breaks the "language barrier" between different brands and types of devices, and realizes seamless docking and collaborative work between monitoring devices and governance devices. It constructs a unified device access standard, solves the system integration problem caused by a large number of equipment brands and inconsistent protocols at the construction site, and realizes true full-system linkage.

[0016] The present invention sets intelligent ash cleaning and environment adaptation technology. It adopts a mechanical automatic ash cleaning structure, and through the coordinated movement of a lifting baffle and an ash cleaning plate, regularly removes the dust on the display screen surface; combined with the design of a cooling fan and a dust-proof net, it ensures the long-term stable operation of the equipment in a harsh construction site environment, solves the industry problems of easy dust accumulation and easy failure of outdoor monitoring equipment, and greatly reduces the equipment maintenance frequency and cost.

[0017] The beneficial effects brought by the present invention include: 1. Significantly improved monitoring accuracy: Through the multi-parameter monitoring module and the intelligent ash cleaning system, it solves the problem of insufficient accuracy of traditional monitoring equipment in the complex construction site environment, and ensures the accuracy and reliability of monitoring data. Adopting a lifting adjustment mechanism, it realizes accurate detection of air parameters at different heights, meeting the monitoring requirements of different areas of the construction site.

[0018] 2. Significantly improved governance efficiency and accuracy: Through adaptive dust source tracking algorithms and linked governance execution units, the system shifts from "area governance" to "point source governance," improving governance accuracy by over 40%. The adoption of a dust-proof canopy system reduces dust from the foundation pit by nearly 80%.

[0019] 3. Optimized water resource utilization efficiency: Intelligent control of the spraying equipment is achieved based on dust content, enabling the equipment to automatically adapt to changes in water pressure and volume due to varying dust levels. This ensures effective dust suppression while preventing excessive water waste. In practical applications, water savings exceed 30%.

[0020] 4. Faster system response speed: Through edge computing technology, local real-time data processing and rapid generation of control commands are achieved, with a response time of less than 1 second, overcoming the drawback of traditional manual response being delayed by several hours.

[0021] 5. Significantly improved management efficiency: Through a closed-loop management mechanism and AI visual recognition, the entire chain of governance, including "real-time monitoring, instant push notifications, time-limited handling, and closed-loop feedback," is achieved, greatly reducing the cost of manual supervision and decreasing the weekly problem rate by more than 90%. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the overall structure of the system of the present invention; Figure 2 This is a schematic diagram of the structure of the multi-parameter monitoring module of the present invention. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 , Figure 2 A real-time monitoring and automatic linkage control system for dust at construction sites, comprising: The multi-parameter monitoring module is used to collect real-time dust concentration data and environmental parameters in the construction area. It includes a PM2.5 / PM10 sensor based on light scattering, a noise sensor, a temperature and humidity sensor, and an anemometer. The module also features a lifting and adjusting mechanism. The support frame consists of a support cylinder and a connecting cylinder, with height adjustable via a threaded connecting rod. A gear-driven lifting power component at the bottom allows for flexible adaptation of the detection height from the ground to high altitudes. The multi-parameter monitoring module integrates an intelligent dust removal system, comprising a display screen, a liftable baffle, a dust removal plate that fits the display screen, and a power component that drives the baffle's lifting and lowering. A magnetic structure allows for quick assembly and disassembly of the dust removal plate.

[0025] The edge computing controller, employing an ARM embedded system, incorporates an adaptive dust source tracking algorithm to process monitoring data and generate control commands. This algorithm integrates laser scattering particle detection technology based on Mie scattering theory and magnetic attitude angle measurement technology to achieve real-time location of dust sources and prediction of their diffusion paths. The edge computing controller utilizes a data cleaning and completion mechanism, employing a sliding window algorithm to remove abnormal sensor data and an LSTM neural network to predict missing data, ensuring the continuity of the monitoring curves.

[0026] The coordinated governance execution unit includes an intelligent fog cannon device, a dustproof canopy system, and a spray dust suppression system, which automatically activate corresponding governance measures according to control commands. The coordinated governance execution unit includes a dustproof canopy system, which consists of multiple electric canopy units that can automatically open and close according to vertical transportation needs, achieving full coverage of the pit operation space.

[0027] The data communication and cloud platform transmits data to the cloud via a CAN-BUS wireless gateway and 4G / 5G network, supporting remote monitoring and data analysis.

[0028] The system supports multiple protocols, including Modbus TCP / RTU, OPC UA, DL / T 645, and ONVIF, enabling seamless integration with devices of different brands and types. The system also includes a diffusion monitoring unit, used to analyze the amount of dust in the air surrounding the spraying equipment, determine the dust suppression effect based on the analysis results, and generate an alert if the effect is insufficient.

[0029] The cloud platform integrates AI visual recognition capabilities, using high-altitude cameras and deep learning technology to automatically identify violations such as uncovered bare soil and fog cannons not being turned on, and generates structured early warning information.

[0030] The system adopts a closed-loop management mechanism to achieve full-chain governance, including real-time monitoring, instant push notifications, time-limited handling, and closed-loop feedback, and pushes early warning information to the site manager via mobile terminal.

[0031] Example 1: This invention is applied to a typical construction site scenario. In this example, the system is applied to a residential project construction site with an area of ​​20,000 square meters. System deployment includes: Multi-parameter monitoring module: Five monitoring points are set up around the perimeter and center of the construction site. Each monitoring point is equipped with a PM2.5 / PM10 sensor, a noise sensor, a temperature and humidity sensor, and an anemometer. The height of the monitoring module support frame can be adjusted within the range of 2-8 meters to adapt to the monitoring needs of different construction stages. The display screen has a built-in intelligent dust removal system that automatically cleans itself every 6 hours to ensure clear data visibility.

[0032] Edge computing controller: Employs an ARM Cortex-A53 processor and incorporates an adaptive dust source tracking algorithm to calculate dust diffusion paths in real time. The controller uses a sliding window algorithm to filter out transient dust anomalies caused by passing vehicles, ensuring the validity of the monitoring data.

[0033] Joint governance implementation unit: Eight intelligent fog cannons with a range of 30 meters are deployed around the construction site; a dust suppression canopy system is deployed in the foundation pit area, covering an area of ​​3,935 square meters; and a spray dust suppression system is activated during the main construction phase.

[0034] Data Communication and Cloud Platform: Data is transmitted via 4G network, supporting Modbus and OPC UA protocols, and integrated with the existing video surveillance system on the construction site. The cloud platform integrates an AI recognition model, which can automatically identify violations such as uncovered bare soil and unwashed vehicles.

[0035] After the implementation of this embodiment, the number of complaints about construction site dust decreased by 80%, the cost of manual inspection was reduced by 120,000 yuan per year, and the number of times PM10 concentration exceeded the standard was reduced by 75%.

[0036] Example 2: This invention is applied to a linear road construction scenario. In this example, the system is used in a 5-kilometer-long urban road reconstruction project. System deployment features include: Multi-parameter monitoring module: It adopts a combination of vehicle-mounted mobile monitoring stations and fixed monitoring points. The vehicle-mounted monitoring station moves with the construction progress, while the fixed monitoring points are deployed in sensitive areas (such as residential areas and areas around schools).

[0037] Edge computing controller: It has been specially enhanced to optimize features for linear construction, and uses the ARIMA model to predict the change in dust concentration in the next hour, issuing an early warning 30 minutes in advance. When the wind speed is >5m / s and PM10 is >150μg / m³, it is automatically identified as "risk of dust diffusion in strong winds", improving the accuracy of early warning.

[0038] Joint governance execution unit: Deployed mobile fog cannons, which are linked to dust concentration via GPS positioning to achieve "follow-up dust suppression". When PM10 > 200 μg / m³, the system will link with traffic lights to extend the green light time, reducing vehicle idling emissions.

[0039] Data application mechanism: Real-time push of governance data to WeChat groups in surrounding communities to alleviate residents' panic; generation of "Dust Monitoring Daily Report", which includes concentration curves, events exceeding standards, and governance measures, as a basis for environmental protection acceptance.

[0040] After the implementation of this embodiment, the impact of road construction dust on the surrounding environment was reduced by 60%, the number of resident complaints decreased by 70%, and traffic congestion improved by 40%.

[0041] Example 3: This invention is applied to a high-density urban foundation pit construction scenario. In this example, the system is applied to a deep foundation pit project located in a high-density urban area, with multiple sensitive buildings such as residential communities, schools, and hospitals within a 200-meter radius. System deployment features include: Multi-parameter monitoring module: Utilizing a highly flexible lifting design, the monitoring point can reach a height of up to 15 meters to obtain more representative monitoring data. The monitoring module is equipped with a storage protection system, allowing the data acquisition module to be retracted into the storage box during non-use periods to prevent damage from collisions.

[0042] Edge computing controller: It adopts a multi-parameter linkage analysis strategy. When PM10 exceedance, wind speed increase and downwind direction of sensitive areas are detected at the same time, it automatically raises the warning level and starts the enhanced governance mode.

[0043] The coordinated management and control strategy primarily utilizes a dust suppression canopy system, supplemented by intelligent fog cannons. The dust suppression canopy consists of five electrically operated units that automatically open and close according to vertical transportation needs, achieving full coverage of the foundation pit. Simultaneously, a high-pressure spray system is deployed around the foundation pit to form a "water curtain barrier."

[0044] AI-powered vision-enhanced supervision: By connecting to the "Ecological Sky Eye" system in the jurisdiction, a "city sky eye matrix" is constructed through more than 1,300 high-definition high-altitude cameras, realizing a "digital neighborhood relationship map" of the construction site and environmentally sensitive buildings within a 2-kilometer radius, and accurately observing the impact of construction dust on the surrounding area.

[0045] After the implementation of this embodiment, dust from foundation pit construction was reduced by nearly 80%, PM10 concentrations at surrounding sensitive points were controlled within national standards, and the number of resident complaints dropped from an average of 15 per month to 0.

[0046] To verify the effectiveness of this system, a comparative experiment was conducted between the system of this invention and traditional manual monitoring and control methods under the same construction conditions: Comparison of monitoring data accuracy: During the 30-day experimental period, the linear correlation coefficient between the monitoring data of the present invention system and the standard methods of the environmental protection department reached 0.98, while that of the traditional light scattering method monitoring equipment was only 0.85.

[0047] Comparison of response time: The average response time of the system of this invention from detecting the exceedance to initiating the treatment measures is 8 seconds, while the traditional manual method takes an average of 45 minutes.

[0048] Dust suppression efficiency comparison: Under the same spray water volume conditions, the dust suppression efficiency of the system of the present invention reaches 92%, while that of the traditional fixed spray system is only 65%.

[0049] Water resource utilization comparison: By precisely controlling the spray volume and range, the water consumption per unit area for dust suppression is reduced by 35%.

[0050] The above comparison results show that the system of the present invention is significantly superior to traditional methods in terms of monitoring accuracy, response speed, governance effect and resource utilization efficiency.

[0051] The above description is merely a preferred embodiment of the present invention; however, the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and its improved concepts, should be covered within the scope of protection of the present invention.

Claims

1. A construction site dust real-time monitoring and automatic linkage treatment system, characterized in that, The system comprises: a multi-parameter monitoring module for real-time collection of dust concentration data and environmental parameters in the construction area, including a PM2.5 / PM10 sensor based on light scattering method, a noise sensor, a temperature and humidity sensor, and a wind speed and direction instrument; an edge computing controller using an ARM embedded system, with an adaptive dust source tracking algorithm built-in, for processing monitoring data and generating control instructions; a linked management execution unit, including an intelligent fog gun device, a dust prevention curtain system, and a spray dust suppression system, which automatically starts the corresponding management measures according to the control instructions; data communication and cloud platform, through CAN-BUS wireless gateway and 4G / 5G network to transmit data to the cloud, supporting remote monitoring and data analysis.

2. The system of claim 1, wherein, The multi-parameter monitoring module further comprises a lifting adjustment mechanism, and the support frame is composed of a support cylinder and a connecting cylinder. The height is adjusted by a threaded connecting rod. The bottom is provided with a gear transmission lifting power member to realize flexible adaptation of the detection height from the ground to the high altitude.

3. The system of claim 1, wherein, The multi-parameter monitoring module integrates an intelligent dust removal system, including a display screen, a liftable baffle, a dust removal plate attached to the display screen, and a power assembly driving the baffle to lift, which realizes quick disassembly and assembly of the dust removal plate through magnetic attraction structure.

4. The system of claim 1, wherein, The edge computing controller has an adaptive dust source tracking algorithm built-in, which combines laser scattering particulate matter detection technology under Mie scattering theory and magnetic attitude angle measurement technology to realize real-time positioning and diffusion path prediction of dust sources.

5. The system of claim 1, wherein, The edge computing controller uses data cleaning and completion mechanism, which eliminates abnormal sensor data through sliding window algorithm, and predicts missing data using LSTM neural network to ensure the continuity of the monitoring curve.

6. The system of claim 1, wherein, The linked management execution unit includes a dust prevention curtain system, which is composed of multiple electric curtain units and can automatically open and close according to the needs of vertical transportation to realize full coverage of the foundation pit operation space.

7. The system of claim 1, wherein, The system supports multi-protocol compatibility, including Modbus TCP / RTU, OPC UA, DL / T 645, and ONVIF protocols, to realize seamless access of different brands and types of devices.

8. The system of claim 1, wherein, The system further comprises a diffusion supervision unit for analyzing the amount of dust in the air around the spray equipment, judging the dust suppression effect according to the analysis results, and generating an abnormal reminder when the effect is insufficient.

9. The system of claim 1, wherein, The cloud platform integrates AI visual recognition function, which automatically identifies illegal behaviors such as bare soil uncovered and fog gun not started through high-altitude camera and deep learning technology, and generates structured warning information.

10. The system of claim 1, wherein, The system adopts a closed-loop management mechanism to realize real-time monitoring, immediate pushing, time-limited disposal, and closed-loop feedback of the whole chain management, and pushes the warning information to the site responsible person through the mobile terminal.

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