168 results about "Building automation" patented technology

The invention discloses a green building intelligent lighting and energy collaborative optimization system based on multi-source data fusion. According to the system, firstly, multi-source information such as indoor and outdoor illumination, weather, personnel occupation and electricity price is subjected to weighted fusion through dynamic confidence, and an accurate real-time environment state is constructed; then, model predictive control is combined with a multi-objective optimization strategy, and a sunshade device, intelligent lighting and a heating ventilation air conditioner are cooperatively adjusted, so that the comprehensive energy consumption or operation cost is minimized on the premise that the indoor illumination and temperature comfort requirements are met; besides, the self-adaptive module continuously learns and adjusts the thermal characteristics and the use mode of the building through online model parameter correction and occupancy probability prediction, and it is ensured that the energy-saving effect is stable for a long time; the system drives each execution device through a standard building self-control interface, is easy to integrate in a newly built or reformed project, and can significantly improve the energy utilization efficiency and the indoor environment quality.

The invention relates to the field of building automation, discloses a control method and system for a low-carbon energy-saving building system, and aims to solve the problems of insufficient multi-source data integration, dynamic response lag and the like, a distributed sensor network is adopted to collect environment, equipment and energy data in real time, a dynamic energy efficiency index matrix is generated through spatial-temporal feature fusion, and the dynamic energy efficiency index matrix is subjected to dynamic energy efficiency analysis. In combination with a deep reinforcement learning model, carbon emission, energy consumption cost and comfort are collaboratively optimized, and the system adopts a cloud edge collaboration architecture: an edge terminal realizes equipment-level millisecond response, cloud digital twin global optimization is performed, and a heterogeneous gateway and an energy router complete multi-protocol equipment linkage and energy scheduling. The innovative technology comprises air conditioner variable air volume control, illumination self-adaptive dimming, elevator colony and ant colony scheduling and actual measurement display, the comprehensive energy consumption of the system is reduced by 32.7%, the demand response reaches the second level, the PMV thermal comfort index is stabilized to be + / -0.5, and a building cluster is supported to participate in a virtual power plant. And an intelligent building low-carbon integrated scheme is provided.

The invention relates to the technical field of building automation and robots, and discloses a floor robot cutting system based on self-adaptive visual guidance. The technical problems that an existing floor cutting robot excessively depends on a preset path, and the adaptability is poor and the cutting precision is low when the actual working conditions that errors exist between on-site marking lines and design drawings and the ground is uneven exist are solved. An actual cutting datum line is captured and recognized in real time through a visual perception module carried on a robot body, and structured path information is generated; and then the self-adaptive control module dynamically plans and corrects the motion trail of the robot according to the deviation between the visual feedback information and the current pose of the robot so as to guide the cutting execution mechanism to accurately work, so that the accuracy loss caused by environment change and construction errors in a traditional scheme is effectively overcome, and the cutting efficiency is improved. And the operation precision, the field environment adaptability and the automation level of automatic floor cutting are remarkably improved.

The invention discloses a subway station air conditioning load adjusting system and method, and the system comprises a load simulation module which is used for simulating the time sequence change of cold loads and heat loads of different types of stations under different meteorological conditions and operation conditions, and generating a system training data set; the passenger travel behavior modeling module is used for establishing a time-period passenger distribution model by using subway historical passenger flow data and urban public transport survey data; outputting passenger flow densities of different areas by using a time period passenger flow distribution model; the machine learning prediction model is used for extracting multi-dimensional features as input features; a system training data set is utilized to learn the mapping relation between the input features and the target cold / heat load, and a load preset value is output; the intelligent load adjusting control module dynamically adjusts the output capacity of the air conditioning system through the building automation system according to the load preset value, and closed-loop control is achieved. According to the invention, TRNSYS simulation, behavior modeling and intelligent control are integrated, and accurate load prediction and energy-saving regulation and control are realized.

The invention discloses an air conditioner intelligent control method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the air conditioner intelligent control method comprises the steps that firstly, a first adaptation vector is constructed by fusing region features and strategy features, and the adaptation degree of a controlled region and a to-be-started control strategy is represented; and inputting the vector into a pre-trained air conditioner intelligent control model, evaluating the adaptation degree through a working condition association method under the constraint of a target strategy priority tensor table, outputting an optimized second adaptation vector, and finally dynamically starting an adaptive control strategy for multiple controlled areas according to the vector. According to the method, intelligent matching of regional characteristics and strategies is achieved through an artificial intelligence model, strategy priorities are managed through a tensor constraint mechanism, the problems that in a traditional control scheme, multi-region adaptability is insufficient, and strategy optimization efficiency is low are solved, the energy efficiency and user comfort of the air conditioning system can be dynamically improved, and the user experience is improved. The method is suitable for air conditioner cooperative control of multiple scenes such as intelligent buildings and building automation.

For ticket classification in a building automation system, a large language model (LLM) is used to classify. In one approach, a prompt is generated for zero-shot classification, and a prompt is generated for few-shot classification. In another approach, a hybrid annotation provides corrections (review) by an expert to correct LLM classification for sample tickets to be used as examples in the few-shot classification. The LLM may operate on a diverse and complex range of tickets in an efficient and scalable manner.

A control system configurable by a configuration application and comprising one or more control processors, one or more gateways, a communication network, a portable electronic device executing the configuration application and one or more controllable devices wherein the controllable device is represented by one or more virtual devices.

The embodiment of the invention discloses a building automation system, a control method, a device, equipment, a medium and a product. The system comprises a database used for storing equipment data of a building; the intelligent agent is used for receiving natural language statements related to the building; the large language model is used for executing semantic understanding on the natural language statement and generating an operation task based on a semantic understanding result; wherein the intelligent agent is also used for accessing the database to obtain the equipment data associated with the operation task from the equipment data of the building, and executing the operation task based on the equipment data associated with the operation task. And the large language model is cooperated with the intelligent agent, so that the building task is automatically completed, and the intelligence of building control is improved.

The invention relates to the technical field of building automation maintenance, and discloses a concrete crack repairing method fusing unmanned aerial vehicle vision and a 3D printing technology, and the method comprises the steps: collecting a high-resolution image and three-dimensional point cloud data of a crack through an inspection unmanned aerial vehicle; processing the data by using a central processing unit to generate a crack three-dimensional digital model; according to the crack three-dimensional digital model, a three-dimensional printing deposition path and a flight path are generated for a printing unmanned aerial vehicle; and finally, the printing unmanned aerial vehicle deposits a repairing material into the crack through the carried 3D printing system along the planned path. According to the method, the high-precision three-dimensional model is established, and accurate filling of the repairing material is achieved. The deposition process is dynamically corrected by adopting a closed-loop quality control step, and long-acting healing is realized by utilizing a microbial self-repairing material, so that automation and intelligence of crack repairing are realized, the operation efficiency and safety are improved, and the method is particularly suitable for environments such as bridges, high-rise buildings and the like which are highly endangered and difficult to reach by manpower.

The invention relates to the technical field of building automation and intelligent operation and maintenance, in particular to a building equipment fault positioning method based on a sensor network and a layer model, and the method comprises the steps: data collection and preprocessing, dual-time scale concept drift detection, dynamic model management and adaptive correction, and fault positioning and output. According to the method, system changes with sudden change and slow change can be captured at the same time through the double-time-scale design, the dynamic model pool and the historical concept reproduction recognition mechanism enable the system to memorize and reuse the historical operation mode, false alarms caused by periodic changes such as season switching are avoided, and the reliability of the system is improved. The problems that a traditional static or simple online updating model is poor in adaptability in a dynamic environment and the accuracy rate is reduced are fundamentally solved.

The invention belongs to the technical field of intelligent building automation communication, and discloses a KNX protocol hierarchical communication system and method, and the system comprises a microcontroller subsystem and a main control subsystem. The main control subsystem runs a standard Linux operating system and deploys a standard KNX protocol stack, the standard KNX protocol stack comprises a link layer, a network layer, a transmission layer and an application layer and provides a standard programming interface for upper-layer application, and a Web server running on the same Linux system calls the standard programming interface to process KNX communication; the microcontroller subsystem is used for realizing a physical layer function of a KNX protocol; the master control subsystem is connected with the microcontroller subsystem through a USB interface, and the USB interface adopts a private protocol to carry out data transmission. By decoupling a hardware processing layer and a software protocol part, the overall architecture of hierarchical communication is used as a KNX equipment communication node, a complex algorithm can be realized, a bus signal can be responded at a microsecond-level speed, and completeness and reliability of data transmission are ensured by constructing a self-defined private protocol.

The invention relates to the technical field of building automation and machine vision, and particularly discloses a building decoration assembly system and method based on image point cloud processing. According to the system, semantic annotation and feature enhancement are performed on a three-dimensional point cloud through an image semantic segmentation map, and a semantic enhanced point cloud is generated; iterative registration based on semantic consistency is carried out on the decoration component digital model and the semantic enhancement point cloud, and an accurate installation pose is output; planning a collision-free assembly track according to the pose and the semantic segmentation map; and the robot is driven to execute assembly along the track, and pose deviation detection and dynamic compensation are carried out based on the real-time image and the point cloud. According to the method, deep penetration and unified driving of image semantic information in the whole process of environment perception, pose calculation, path planning and closed-loop execution are realized, and the technical problems of insufficient precision, poor adaptability and dependence on manual intervention caused by disjunction of perception, planning and execution links of an existing assembly system are effectively solved.

This application relates to an automated building modeling method based on multimodal information and knowledge graphs. The method includes three key steps: first, a feature extraction and preprocessing process for modeling tasks is constructed for heterogeneous data such as drawings, text, and tables to ensure the accurate acquisition of key modeling parameters; second, a unified semantic framework is constructed based on the IFC standard, and the multimodal information knowledge graph is constructed with the help of the graph database Neo4j, realizing structured data management and semantic association modeling; finally, the semantic retrieval capability of the graph is combined with the IfcOpenShell programming interface to complete the automatic mapping of parameters and components and model generation, output IFC files that comply with industry standards, and realize the visualization of three-dimensional models. This method effectively improves the extraction integrity of multimodal data and the accuracy of model construction, providing new ideas for the automated construction and intelligent management of building information models.

The invention discloses a building comprehensive management control method and device and a medium, and belongs to the technical field of building automation control, and the method comprises the steps: building a dual-medium coupling model between an air medium and a building structure medium, and carrying out the parameterization; establishing a heat flux balance equation based on a parameterization result; building operation data and environment data are collected and processed; the air medium enthalpy difference change rate and the building structure body temperature change rate are calculated and substituted into the heat flux balance equation, the real-time heat flux difference is obtained, and a coupling state vector is generated; and inputting the coupling state vector into a dynamic balance optimization control equation to execute iterative solution, obtaining a control variable, and generating a control signal to adjust a building operation state. According to the method, an energy transfer rule is accurately described through double-medium coupling modeling, a heat flux balance equation is established to realize dynamic balance control, control variables are divided into air side and building structure body side adjustment components to realize multi-system collaborative optimization, and the control precision and the energy-saving effect are improved.

The invention relates to the technical field of multi-robot cooperative control and building automation, and discloses a building-machine-oriented multi-robot cloud edge cooperative operation system and a building-machine-oriented multi-robot cloud edge cooperative operation method. The invention aims to solve the problem that the existing robot operation is low in efficiency and excessively depends on cloud communication due to field deviation. According to the invention, a target-oriented task package containing a lightweight artificial intelligence model is generated through a cloud and is distributed to an edge controller; the edge controller performs local analysis and performs closed-loop fine adjustment on the field deviation by using an artificial intelligence model; and after the task is completed, the edge controller asynchronously uploads the structured empirical data packet containing the model parameter increment for the cloud to iterate the global model. The cooperative mechanism constructed by the invention effectively improves the operation efficiency and the self-adaptive capability of the system, and reduces the dependence on real-time cloud side communication.

A building automation system (BAS) includes building equipment located within a building and a BAS network configured to facilitate communications between the building equipment. The building equipment operate to affect a variable state or condition within the building. The BAS includes a BAS-BIM integrator configured to receive BAS points from the BAS network and to integrate the BAS points with a building information model (BIM). The BIM includes a plurality of BIM objects representing the building equipment. The BAS includes an integrated BAS-BIM viewer configured to use the BIM with the integrated BAS points to generate a user interface. The user interface includes a graphical representation of the BIM objects and the BAS points integrated therewith.

A system and method for detecting and diagnosing faults in a building automation system (100). Time-series data (202) are received from the building automation system (100). Label rationality (214, 216, 218, 220, 222) is determined for each set of time-series data and the corresponding label associated with that set, based on a tree-based classifier (224) and an image transformation classifier (226). The tree-based classifier (224) and the image transformation classifier (226) receive the same data input and operate independently of each other.

The present application relates to the technical field of building automation, in particular to an outdoor louver canopy automatic control method and system, comprising the following steps: based on historical and real-time environmental data, using an autoregressive integrated moving average model, analyzing the trend and seasonal variation of illumination, temperature and wind speed data, using a random forest algorithm to process the nonlinear relationship of the data, constructing a model to predict environmental changes, analyzing and predicting the future trend of illumination and temperature parameters, and generating environmental prediction data.In the present application, the autoregressive integrated moving average and random forest algorithm accurately predict environmental changes, the gradient boosting machine algorithm reduces prediction error, the long short-term memory network timely identifies structural damage and functional failure, enhances reliability and safety, the fuzzy logic control handles input uncertainty, improves control accuracy, the PID algorithm adjusts the control amount according to real-time data, realizes accurate adjustment, real-time data stream analysis monitors the state, and ensures effective execution of the strategy.

A computerized method of assigning a building automation system point type to a plurality of unclassified data points is provided. The method includes receiving unclassified data points and attributes for each data point. The method includes receiving classifications for a first subset of the unclassified data points. Each classification associates a data point with a building automation system point type. The method includes generating a term set containing substrings that appear in the attributes. The method includes generating a first matrix describing a frequency that the substrings appear in the attributes. The method includes calculating an indicator of a probability that the presence of the selected substring results in the data point belonging to the selected point type. The method includes assigning a point type to a second subset by finding the substring and potential point type pair having the greatest indication of probability.

The invention relates to the field of industrial automation control, and provides a remote equipment control method, an edge controller and a building automatic control system. The method is applied to a remote control agent module of an edge controller, and comprises the following steps: if it is determined that remote equipment controlled by the edge controller comprises a to-be-configured physical point location, locally creating a local agent point location corresponding to the to-be-configured physical point location; related configuration information of the to-be-configured physical point location is written into the local agent point location to establish a mapping relation between the local agent point location and the to-be-configured physical point location; and performing remote monitoring on the to-be-configured physical point location of the remote equipment based on the mapping relation. According to the invention, the number of point locations which can be supported to be monitored by the edge controller can be obviously increased, network and bus communication load balancing of the building automatic control system can be realized, centralized control of massive physical point locations on the edge side can be realized, and reasonable and effective utilization of edge side resources can be realized.

The invention relates to the technical field of building automation control, and discloses a green building carbon emission optimization system and method.The system comprises an energy consumption decision-making unit, a quota distribution module, a carbon quota scheduling module and a system monitoring module, and the energy consumption decision-making unit carries out autonomous decision-making based on a utility function containing function expression degree, carbon cost, reputation rating and strategy entropy. The quota allocation module allocates an initial quota according to historical data and the reputation rating; the carbon quota scheduling module schedules quota circulation among units through real-time exchange and long-term reservation functions. The system monitoring module evaluates the unit behavior to update the reputation rating, and provides a basis for the redistribution of the initial quota. By establishing the internal carbon quota market and introducing the reputation mechanism, the energy consumption unit is converted into the collaborative decision-making main body, the carbon quota utilization efficiency is improved, refined self-adaptive optimization of the total carbon emission of the building is realized, and the problem that the carbon emission control in the existing building energy consumption management lacks dynamic self-adaptive optimization capability is solved.

The invention relates to the technical field of equipment detection, and provides an equipment abnormity alarm method and device, electronic equipment and a storage medium. The method comprises the following steps: receiving state information sent by at least two different access devices in the building automation control system; determining an alarm rule corresponding to each access device, and verifying the state information corresponding to each access device through the alarm rule corresponding to each access device; and if the verification result of the state information of any access device is abnormal, generating device abnormity alarm information corresponding to any access device. According to the method and the device, the state information and the alarm rule of the access devices are managed in a centralized manner in the upper computer monitoring system, so that unified analysis and processing of alarm states of multiple devices are realized; therefore, the efficiency of fault positioning and abnormal response is improved, and the overall monitoring capability and the operation and maintenance management level of the building automation system are improved. The problem that troubleshooting is affected due to the fact that the alarm information of the access equipment is managed by respective equipment engines is avoided.

The present invention relates to a computer-implemented method for generating a building automation project for a building automation system BAS, comprising the following steps: receiving structural information related to building equipment via an interface; generating a semantic model of the building automation system, including the step of automatically extracting equipment information from the structural information related to the building equipment; extending the semantic model of the building automation system by providing application information; and generating a building automation project adapted for loading on a building automation device based on the equipment information and application information of the extended semantic model of the building automation system.

A building automation system includes a ceiling-mounted sensor module comprising a millimeter-wave radar sensor, thermal array sensor, and ambient light sensor. The millimeter-wave radar sensor detects stationary occupants by measuring chest movements corresponding to breathing patterns and generates three-dimensional position coordinates for each detected occupant. A control unit processes sensor data locally and automatically controls a lighting system, window covering system, climate control system, and audio system based on occupancy patterns and environmental conditions. The control unit adjusts lighting brightness and color temperature according to a solar schedule determined from GPS coordinates and time of day, and prevents lighting activation when ambient light levels exceed a predetermined threshold despite detected occupancy. The system operates independently during network disruptions through local data processing within the residential structure.

The invention provides a data processing method, device and system, a storage medium and a program product, and relates to the field of data processing. The data processing method comprises the following steps: acquiring data in a building automatic control system; classifying the data to obtain a first type of data and a second type of data, the first type of data being data used for participating in equipment operation control in real time, and the second type of data being data except the first type of data; in response to the fact that the network state is an abnormal state, the first type of data is sent to a digital base, the second type of data is cached, and the cached second type of data is complementarily transmitted to the digital base under the condition that the network state is recovered to the normal state.

For ticket classification (220) in a building automation system, a large language model (LLM) (552) is used to classify (220). In one approach, a prompt (300) is generated (210) for zero-shot classification, and a prompt (400) is generated (210) for few-shot classification. In another approach, a hybrid annotation provides corrections (review) (8) by an expert to correct LLM classification for sample tickets (410) to be used as examples in the few- shot classification. The LLM (552) may operate on a diverse and complex range of tickets in an efficient and scalable manner.

There is disclosed a building automation system, and a method thereof, for managing causal chain. Facility data of the building automation system is collected. One or more suggested causes and one or more causal chains are generated based on the facility data. One or more responsive actions are determined based on the suggested cause or causes, the causal chain or chains, and a cause-action mapping. A particular causal chain is provided based on the at least one responsive action and manager information.

The invention relates to a method (100) for controlling and / or regulating a usage scenario relating to at least one part of a building installation (10). The method (100) provides that at least one user-related characteristic is recorded (102). On the basis of the recorded (102) at least one user-related characteristic, control and / or regulating parameters for the purpose of realizing the usage scenario relating to at least one part of the building installation (10) are determined (104) by means of a computer-implemented algorithm. The determined (104) control and / or regulating parameters are output (106) by means of the computer-implemented algorithm. Furthermore, the usage scenario is controlled or regulated (108) on the basis of the output (106) control and / or regulating parameters.