968 results about "Indoor air quality" patented technology

Techniques for operating an environmental sensing system are described. In an example, a cloud-based server system receives a first indication that a first type of air pollutant is present within a first structure from a first plurality of indoor air quality (IAQ) sensing devices positioned within the first structure. A second structure within a predefined distance to the first structure is then identified by the server system. The server system then determines that the first type of air pollutant is not present within the second structure. The server system then causes a second plurality of IAQ sensing devices positioned within the second structure to change an operating mode from a normal sensitivity mode to a high-sensitivity mode.

An IAQ sensor module includes: a sensor configured to measure an amount of an item in air, the item being one of particulate matter, volatile organic compounds, and carbon dioxide; a minimum module configured to selectively store the amount of the item as a minimum value of the amount when a mitigation device has been on for at least a predetermined period, the mitigation device being configured to decrease the amount of the item in the air when on; a storing module configured to selectively store the minimum value as an initial minimum value; an offset module configured to determine a drift offset for the sensor based on a difference between the minimum value and the initial minimum value; and an adjustment module configured to determine an adjusted amount of the item in the air at the IAQ sensor module based on the amount and the drift offset.

The invention relates to the technical field of energy consumption management, and particularly discloses an AI-based clean room dynamic energy consumption management system and method. According to the method, a deep learning algorithm is introduced to carry out deep interaction analysis on clean room indoor air quality parameter time sequence data and environment change driving event data such as the number of indoor personnel, the external environment temperature, the room door opening and closing state and the equipment power, so that intelligent reasoning of the dynamic evolution process of the clean room indoor air quality is realized; according to the method, the air quality parameter prediction result is compared with the preset air quality standard range so as to predict the air quality change in the future short time under the current driving event, and then the short-time air quality parameter prediction result is compared with the preset air quality standard range so as to carry out feedforward adjustment on the HVAC system operation parameters of the clean room according to the difference between the short-time air quality parameter prediction result and the preset air quality standard range. According to the method, environmental changes can be actively predicted, smooth pre-adjustment is conducted in advance, the air quality in the clean room is kept within the preset standard range, meanwhile, unnecessary energy waste is remarkably reduced, and the environmental stability is improved.

The invention discloses an indoor air quality monitoring method and system based on multi-dimensional analysis, and belongs to the technical field of air quality monitoring. The indoor air quality monitoring method based on multi-dimensional analysis comprises the steps that various data of a chemical sensor, an optical sensor and an acoustic sensor are collected; preprocessing the data, including unifying sampling frequency and normalizing different data formats; performing multi-dimensional feature extraction to obtain a multi-modal feature; carrying out feature fusion by adopting a machine learning algorithm; the air quality state is evaluated based on the fusion features; through multi-source data fusion analysis, the problems of one-sided monitoring result and insufficient reliability of a single sensor are solved, the monitoring accuracy and reliability are improved, and the method can be widely applied to scenes such as smart homes and office buildings.

The invention relates to an air purification method and system fused with AI intelligent big data analysis, and solves the problem that the purification effect is greatly reduced due to the fact that an air purifier cannot adjust operation parameters in time according to upcoming air quality changes in the operation process. The method comprises the following steps: inputting real-time gas related data and gas related data in a historical past time range into a pre-trained air quality prediction model, and outputting an air quality prediction result in a future preset time range; and the mode set by the user about the air purifier and the air quality prediction result in the future preset time range are input into the air purifier operation parameter optimization model, the optimized air purifier operation parameters are output, and the air purifier is indicated to perform corresponding operation according to the optimized air purifier operation parameters. The intelligent air purifier has the following effects that precise and intelligent air purification is achieved, the indoor air quality is effectively improved, and various requirements are met.

The invention relates to the technical field of indoor air quality monitoring, and discloses an indoor air quality joint detection system fused with a space-time diagram neural network. The system comprises a multi-source sensor data acquisition module for acquiring multi-source air quality data flow by configuring various sensors; the space-time diagram construction module constructs space-time diagram data according to the spatial position and the time sequence of the sensor; the fusion processing module adopts a space-time diagram neural network to perform feature fusion on the space-time diagram data to generate an air quality fusion feature set; the prediction strategy module determines a prediction strategy based on the remaining duration of the current time and the end time of the prediction period, and performs air quality prediction in combination with the fusion feature set; the dynamic adjustment module analyzes the real-time change of the data, constructs the pollution change degree and tendency degree, and adjusts the detection control parameters according to the pollution change degree and tendency degree; and the joint detection output module synthesizes the prediction result and the adjustment parameters to generate an indoor air quality joint detection report. The system provides powerful support for indoor air quality evaluation.

This preferred embodiment pertains to a system designed to manage and optimize indoor air quality within a certain space. It employs a processor, multiple sensors, air dampers, and highly sophisticated machine learning code to control air flow, consider energy consumption, and analyze air quality data to maintain optimal conditions for both health and energy efficiency.

The invention discloses a ventilation and air exchange device for a green building. The ventilation and air exchange device comprises a ventilation and air exchange box, a mounting plate, a ventilation and air exchange opening, a rotary air disc and fan blades. Mounting plates are fixed to the two ends of the two sides of the ventilation box, fixing pins penetrate through the interiors of the mounting plates, one ends of the fixing pins extend into the green building wall, and ventilation ports are formed in the two ends of the outer side of the ventilation box. According to the ventilation device for the green building, a fan motor is used for driving a linkage shaft to rotate, and a transmission assembly is matched to enable a fan shaft to rotate synchronously, so that two rotating wind discs and a plurality of fan blades are driven to rotate, outdoor fresh air is extracted and fed into the green building, and the ventilation effect is improved. According to the indoor air purification device, vitiated air, harmful gas and microorganisms in a building can be effectively diluted and discharged, so that the indoor air quality is improved, a healthier and more comfortable living environment is provided for people, indoor oxygen can be effectively supplemented, and the freshness and vitality of indoor air are kept.

The invention discloses an indoor air quality inspection robot, which belongs to the field of indoor air quality inspection, and comprises the following steps: collecting air quality data in real time by adopting a sensor network according to preliminary monitoring priority distribution, extracting abnormal fluctuation characteristics from air quality change of each region, and determining a target region range needing key inspection; a path planning algorithm is called to generate a shortest feasible path from a current position to a target area through a local path adjustment scheme in combination with a global path optimization target, and a real-time updating result of a dynamic inspection path is obtained; and transmitting task allocation data of each inspection robot through a scheduling instruction of multi-device collaborative operation, and extracting target area and path planning information of each device from the task allocation data to obtain a coordination optimization scheme of overall inspection coverage.

A system can include one or more memory devices that can store instructions thereon that, when executed by one or more processors, cause the one or more processors to retrieve first information to indicate one or more aspects of a building, generate a plurality of constraints for a model, provide the plurality of constraints to the model to cause the model to simulate a performance of a plurality of sensors in collecting first indoor air quality data for the building, identify one or more first sensors to position at one or more first locations of the building and one or more second sensors to position at one or more second locations of the building, and generate a recommendation to indicate a placement of the one or more first sensors and a placement of the one or more second sensors.

The heat recovery fresh air conditioning unit comprises a total heat recovery fresh air conditioning unit body and a control cabinet, the total heat recovery fresh air conditioning unit body is formed by splicing an upper exhaust box body and a lower air supply box body, and an exhaust side bypass electric air valve and a heat recovery device are sequentially arranged in the upper exhaust box body in the flowing direction; a first pressure difference sensor assembly and an exhaust enthalpy value sensor are distributed in the upper exhaust box, a constant air volume device, a heat recovery device, an air supply side bypass electric air valve and an air feeder are arranged in the lower air supply box body in the flowing direction, and a second pressure difference sensor assembly, a fresh air enthalpy value sensor and a fresh air enthalpy value sensor after heat recovery are distributed in the lower box body. And the control cabinet realizes the operation states of the heat recovery device and the bypass electric air valve through judgment according to the pressure difference measured by the pressure difference sensor assembly and the enthalpy value measured by the enthalpy value sensor in combination with the frequency value and the electricity consumption of the fan. Compared with a traditional control method, the method is easier to implement, the energy-saving effect is better, and the indoor air quality is higher.

The invention discloses an automatic indoor air quality monitoring method, and belongs to the technical field of indoor air quality detection. According to the method, a first data set and a second data set are obtained by monitoring cells, air inlets and air outlets of a communication area and an indoor area, an air state model of the communication area and each indoor area is constructed, and a state transition probability and a state input probability are predicted and substituted into the air state model; and a state vector of the next state transfer step length is generated, so that the data processing amount of multi-region air quality monitoring is reduced, and the effect of prediction in advance is achieved. Furthermore, multiple components are monitored through an air state model, a negative parameter set is generated from the aspects of germ infection, lung harm, explosion danger and the like, the air quality negative index is evaluated, a positive parameter set is generated from the aspects of proper temperature and humidity, proper O2 concentration, proper CO2 concentration and the like, the air quality positive index is evaluated, and comprehensive monitoring of the air quality is achieved.

The invention provides a data acquisition and analysis method of an intelligent sofa, which comprises the following steps: arranging an electrostatic sensor array on the intelligent sofa, and acquiring electrostatic signal intensity and polarity distribution, human body charge and environmental humidity data of different areas on the surface of the sofa in real time to obtain electrostatic distribution data; under different air quality conditions including pollutant concentration and particulate matter content, according to the electrostatic characteristic parameters, a mapping relation model of the electrostatic characteristic parameters and the air quality is trained through a support vector machine algorithm; inputting sofa static signal intensity collected in real time into the trained mapping relation model of static characteristics and air quality to obtain changes of the static characteristics, and evaluating indoor air quality in real time; if the evaluation result shows that the air quality is smaller than the air quality threshold value, an air purification device of the intelligent sofa is triggered, an air purifier is started, and the ventilation amount of a fresh air system is increased so as to improve the indoor air environment.

The invention relates to the technical field of environment monitoring, in particular to a multifunctional air quality monitoring and early warning system, which comprises a monitoring and adjusting module, a monitoring and early warning module, a monitoring and early warning module, an early warning module and an early warning module, and is characterized in that the monitoring and adjusting module monitors pollutants and temperature and humidity information in air through various sensors and automatically adjusts sensor detection ranges according to air quality conditions; the intelligent early warning module is used for establishing a prediction model, pre-judging the deterioration trend of the indoor air quality in advance through the prediction model, and triggering trend early warning when monitoring that the deterioration risk is high; and the equipment linkage module is used for establishing an equipment linkage rule base and automatically matching an optimal equipment operation strategy according to the air quality data. Various high-precision sensors are integrated, multi-dimensional data of particulate matter, harmful gas, oxygen content and temperature and humidity in air can be comprehensively monitored, the indoor air quality condition is accurately reflected, an air purifier and fresh air system equipment are automatically allocated according to a data analysis result, and intelligent environment adjustment is achieved.

The invention relates to the technical field of fresh air blowers, and discloses a whole house type frequency conversion fresh air dehumidification system which comprises an intelligent control module, an environment sensing module, an intelligent control module, an intelligent control module, an intelligent control module, an intelligent control module, an intelligent control module and an intelligent control module, the indoor air quality data collection module collects indoor air quality data in real time and transmits the indoor air quality data to the intelligent control module, the air processing module comprises a fresh air introduction unit, a return air circulation unit and a mixed air processing unit, and the mixed air processing unit is configured to mix outdoor fresh air and indoor return air according to a preset proportion; according to the whole house type variable frequency fresh air dehumidification system, the variable frequency compression unit and the variable frequency fan unit are adopted, the humidity control precision of + / -3% can be achieved within the daily dehumidification amount range of 45-145 L, meanwhile, energy consumption is reduced by 15-35%, noise is lower than 36 dB (A), the PM2.5 purification efficiency of double filter screens reaches 99.98%, the indoor air quality is remarkably improved, and the maintenance process is simplified.

The invention belongs to the technical field of intelligent control, and particularly relates to an air purification system based on intelligent perception and a self-adaptive regulation and control method thereof. Comprising a multi-dimensional environment perception unit, an environment data fusion and modeling unit, a self-adaptive regulation and optimization decision unit, a modular air purification execution unit and a man-machine interaction and user preference setting unit. According to the method, multi-element parameters are collected, fusion modeling is carried out, a pollution source is identified and predicted, a multi-target optimization algorithm is applied to generate an optimal purification strategy, and then a purification execution unit is controlled. The indoor air quality can be finely and dynamically managed, the purification efficiency is remarkably improved, energy consumption, operation noise and the service life of a filter material are intelligently balanced, and a personalized healthy breathing environment is provided.

The present application relates to air conditioning technology field, specifically relates to a kind of partition regulation formula refrigeration constant temperature and humidity air conditioning unit with air supply system, comprising: unit machine case;Constant temperature air supply structure for temperature regulation for air supply system air supply is equipped in the inside of unit machine case, and the air supply end of constant temperature air supply structure is connected with air duct for wind force transmission;The air duct is installed with constant humidity partition regulation structure for indoor partition regulation air supply in air outlet end.This application, in hot air heating mode, system can effectively deliver hot air to each partition by closing No. 1 and No. 3 electromagnetic valve, realize subarea heating, improve energy utilization efficiency, in cold air refrigeration mode, system is adjusted closed flap and starts compressor, so that cold air is delivered to each partition after refrigeration cycle, also realize subarea refrigeration, exhaust air and dust mode can extract indoor peculiar smell and dust, improve indoor air quality.

Systems and methods for executing an IAQ analysis of a building. One system includes a controller including memory and one or more processors configured to obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species, obtain BAS data, identify one or more unknown parameters from the IAQ data and BAS data of two or more of the plurality of environment species, estimate the one or more unknown parameters based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the plurality of environment species subject to the two or more of the plurality of environment species evolving according to a single-species concentration model, and provide the estimated one or more unknown parameters to one or more predictive models.

The invention belongs to the technical field of building ventilation, and particularly discloses an intelligent building ventilation energy-saving system based on AI dynamic adjustment, and the system is characterized in that the system comprises a sensing layer which is used for collecting indoor and outdoor environment parameters in real time; the data transmission layer transmits various data acquired by the sensing layer to a central control system in real time through an Internet of Things communication technology, and is provided with a data caching mechanism; the central control system comprises a data processing module and is used for preprocessing the received data; the AI analysis module is used for establishing an indoor air quality prediction model, a personnel activity mode prediction model and a ventilation system energy consumption model by applying a machine learning algorithm; the control decision module generates an optimal ventilation control strategy; and the execution layer comprises a fresh air fan and an exhaust fan which adopt a frequency conversion technology, and an air supply outlet and an exhaust outlet which are provided with electric air valves, and further comprises a function of receiving a control instruction of the central control system and controlling ventilation equipment in real time.

The invention relates to an indoor air quality adjusting method, device and equipment based on user preferences. The method comprises the steps of obtaining current state data of a user and current air data of an environment where the user is located; the current state data are input into a preset air quality preference model, required air data corresponding to the user are obtained, whether the current air data reach the required air data or not is judged, and the preset air quality preference model is obtained by learning through a random forest algorithm and a deep reinforcement learning algorithm based on multiple pieces of historical data; and if any parameter in the current air data does not reach the required air data, target control equipment and control parameters thereof are determined according to the parameters which do not reach the required air data, and the target equipment is controlled according to the control parameters. Therefore, user preference air quality decision control is realized through integrated hardware and various algorithms, real intelligent and personalized management is realized, and multiple requirements of the user on comfort, health and energy conservation are met.

A system for detecting low IAQ and enabling ventilation in a multi-zone environment is disclosed. The system comprises dampers configured in supply air channels associated with zones of the environment, and an IAQ sensor configured in a common return duct associated with the environment. When the IAQ values of combined return air are detected to vary, a controller successively operates one of the dampers in an open state while operating remaining zone dampers in a closed state, so that supply air flows into the zone having zone damper in the open state. The controller further successively monitors IAQ values of the return air received from each of the zones and accordingly detects a low IAQ condition in the zones when a difference is detected between the IAQ values of the return air from the respective zone, and the IAQ values of the combined return air received collectively from the zones.

A dark toilet exhaust passage concrete one-time forming structure comprises a large corrugated pipe and multiple sets of outer aluminum alloy modules, a cavity is formed among the multiple sets of outer aluminum alloy modules, the large corrugated pipe is arranged in the middle of the interior of the cavity, and the large corrugated pipe is fixedly connected with the outer aluminum alloy modules through fixing assemblies. The utility model has the beneficial effects that the concrete material is adopted for pouring, so that the concrete exhaust passage has better strength, durability and plasticity, a material basis is provided for manufacturing a one-step formed full-concrete exhaust passage, and the exhaust passage which is firm in structure, smooth in surface and good in sealing property can be manufactured; compared with the traditional material, the concrete material is more environment-friendly, not only has excellent ventilation performance, but also can reduce the building energy consumption and improve the indoor air quality, and adopts the form of the prefabricated member, so that the field installation is simple, convenient and rapid, the construction period is greatly shortened, and meanwhile, the material cost is relatively low, so that the building cost can be effectively controlled.

A method for calibrating indoor air quality (IAQ) sensors associated with an area of interest (AOI) is disclosed. The method comprises the steps of creating a predetermined calibration environment for one or more IAQ sensors associated with the AOI by enabling a building management system (BMS) associated with the AOI to perform one or more of adjusting inflow of outside air into the AOI to a first predetermined maximum level, adjusting ventilation rate of the AOI to a second predetermined maximum level, and increasing a degree of air filtration in the AOI to a third predetermined maximum level; monitoring IAQ values detected by the one or more IAQ sensors at the AOI in the predetermined calibration environment, and calibrating the one or more IAQ sensors based on an average value of the monitored IAQ values being detected by each of the IAQ sensors.

The utility model relates to the technical field of air quality monitoring, and discloses an indoor air quality multi-channel rapid monitor, comprising: a monitoring module comprising an instrument part and a detection part, the detection part comprising a mounting box arranged at the bottom of the instrument part, a plurality of air chambers uniformly arranged at the bottom of the mounting box along the left and right, the bottom of each air chamber being open, different types of sensors are respectively arranged in the sensors; the adjusting diffusion module comprises a ventilation box, the bottom of the adjusting diffusion module is provided with a plurality of air inlet channels, the top of the adjusting diffusion module is provided with an air replacement module, all the air chambers are arranged in the ventilation box, and air in the ventilation box is subjected to standing and free diffusion in the ventilation box after being replaced by the air replacement module and is detected through a sensor; the blowback ventilation module is arranged on one side of the ventilation box and used for carrying out blowback and replacement on gas in the ventilation box, and compared with the prior art, the detection device has the advantages that detection is carried out through gas replacement and gas diffusion, and the nitrogen blowback cleaning function is achieved.

The utility model relates to the technical field of air samplers, and discloses an air sampler for indoor environment detection, which comprises a fixed table, a hydraulic rod is fixedly connected to the side wall of the fixed table, a first sliding table is fixedly connected to the output end of the hydraulic rod, a sliding rail is fixedly connected to the side wall of the fixed table, the first sliding table is slidably connected to the side wall of the sliding rail, and a second sliding table is fixedly connected to the side wall of the sliding rail. An inclined plate is fixedly connected to the side wall of the fixed table, a supporting table is fixedly connected to one side wall of the sliding table, a connecting column is rotatably connected to the interior of the supporting table, a connecting plate is fixedly connected to the bottom of the connecting column, a pulley is rotatably connected to the interior of the connecting plate, and a sampling head is fixedly connected to the top of the connecting column. According to the utility model, through the cooperation of the sliding rail, the supporting table, the inclined plate and other structures, the movement and rotation of the sampling head are realized, so that the sampling range of the sampling head is expanded, the sampling structure is diversified, and the indoor air quality detection and evaluation are more accurate.

The invention relates to the technical field of workshops, and discloses an assembly type heavy steel frame workshop structure and a construction method thereof.The assembly type heavy steel frame workshop structure comprises a roof truss installed on a foundation; four roof beams which are symmetrically distributed in pairs are installed at the top end of the roof truss through high-strength bolts, a connecting beam is installed between every two symmetrically-arranged roof beams through high-strength bolts, and supporting beams are installed at the bottom ends of the two connecting beams and the top end of the roof truss through high-strength bolts; the inner walls of every two roof beams located on the same side are connected with a main roof plate through high-strength bolts, by arranging a driving mechanism and a movable mechanism, the top of the plant can be rapidly opened, in summer, indoor ventilation and heat dissipation can be achieved through natural wind, the indoor air quality can be improved, and the temperature and humidity can be reduced; natural light can be utilized to the maximum extent for illumination, and the lighting efficiency is improved.

Readings may be received from a chemical sensor disposed proximate to a battery within a housing of a smart-home device. The readings from the chemical sensor may be processed to determine whether a chemical associated with an internal environment of the battery is present inside the smart-home device. A determination may then be made as to whether the battery is damaged based on whether the chemical is present inside the smart-home device. Alternatively, the device may determine that the chemical originates from outside of the housing of the device. A sequence of mitigation actions may then be executed to remedy the faulty battery or improve the indoor air quality.

The application discloses an installation prompting method, which comprises the following steps: acquiring first module information and second module information; the first module information is information of a first functional module to be installed corresponding to a preset area of the air conditioner; the second module information is information of a second functional module currently installed in the preset area of the air conditioner; determining a recommended installation position according to the first module information and the second module information; the recommended installation position comprises positions of the first functional module and the second functional module respectively recommended for installation in the preset area; and outputting installation prompting information according to the recommended installation position. The application also discloses an air conditioner and a computer readable storage medium. The application aims to improve the accuracy of the installation position of the functional module on the air conditioner, so as to improve the effect of the air conditioner on improving indoor air quality.

The utility model provides a fan coil with an air filter structure, which comprises a fan coil component, an air inlet filter component and an air outlet filter component, a heat exchange box for cold and heat exchange is arranged in the fan coil component, the air outlet filter component for filtering air before air outlet is mounted on the right side of the heat exchange box, and the air outlet filter component is mounted on the right side of the heat exchange box. Compared with the prior art, the fan coil assembly, the air inlet filter assembly, the air outlet filter assembly and the filter element plate are additionally arranged, the air inlet filter assembly is installed at the air inlet of the volute, the filter element plate is installed in the installation groove, and the air outlet filter assembly is installed on the right side of the heat exchange box. Inlet air is firstly filtered through the filter element plate, discharged through the air outlet filter assembly after heat exchange is completed, and secondarily filtered through the activated carbon filter plate and the outlet filter plate, the indoor air quality can be improved, and the position of the air inlet can be changed by additionally arranging the fan coil assembly and the air inlet filter assembly.

The invention discloses a method for identifying VOCs (Volatile Organic Compounds) in a mixed environment based on a machine learning algorithm, which comprises the following steps of: firstly, explaining the principles and mechanisms of data preprocessing and deep learning (mainly CNN (Convolutional Neural Network)); then, a VOCs identification and prediction method based on a mixed background library is provided, and a series of experiments are designed to verify the effectiveness of the method. Finally, through analysis and discussion of experimental results, the specific single-phase VOCs gas is successfully identified from the mixed environment. The research result of the invention is helpful for improving the accurate identification and prediction capability of VOCs in the fields of environment monitoring, indoor air quality detection, personal health protection and the like, and provides theoretical and technical support for the detection of mixed gases in practical application.