Whole house intelligent control system based on BIM

Abstract

The invention discloses a BIM-based whole house intelligent control system. The system is mainly formed by mutual cooperation of a BIM model data integration unit, an Internet of Things access unit, a control and management unit, an energy consumption analysis and optimization unit and a user interaction and platform integration unit. The invention provides a BIM-based whole house intelligent control system, and the system achieves the deep fusion of a BIM model (a building information model) and intelligent household equipment (i.e., Internet of Things equipment), thereby achieving the bidirectional data interaction between the BIM model and the household Internet of Things equipment, achieving the equipment management, energy consumption optimization, automatic control and remote operation and maintenance, and achieving the intelligent control of the whole house. And the living experience of the user and the equipment management efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of building information modeling (BIM) and smart home, and in particular to a technology for integrating and collaboratively controlling smart home devices based on BIM technology. Background Art

[0002] With the rapid development of smart cities and Internet of Things technologies, smart home systems are increasingly used to enhance living experience, optimize energy management and achieve automated control.

[0003] However, most current smart home systems are still based on independent devices and lack a standardized integration platform. Devices of different brands and protocols are difficult to achieve compatibility and collaboration, resulting in information islands and increasing the complexity of system integration and management.

[0004] In addition, traditional smart homes rely on decentralized control platforms. For example, users need to operate lighting, temperature control, security and other equipment separately, which reduces the convenience of operation and user experience. At the same time, although many devices have energy-saving functions, they usually operate in isolation and lack systematic analysis and optimization methods for the overall energy consumption of the building, which cannot effectively support the realization of green building goals.

[0005] Furthermore, the prior art also provides a solution for using the building information model (BIM) to achieve intelligent management of equipment in the building. However, in the existing solution, the real-time data interaction between the BIM model and the real-time smart home devices is not high, and the data interaction capability is limited, and it is impossible to achieve two-way control and status connection between virtual and real scenes. Summary of the invention

[0006] In view of the problems that existing smart home solutions are scattered and independent, with low integration and complex management, the purpose of the present invention is to provide a whole-house intelligent control system based on BIM. This system solution innovatively realizes equipment management, energy consumption optimization, automatic control and remote operation and maintenance through two-way data interaction between BIM models and smart home devices, thereby improving users' living experience and equipment management efficiency.

[0007] In order to achieve the above-mentioned object, the whole-house intelligent control system based on BIM provided by the present invention comprises: a BIM model data integration unit, an Internet of Things access unit, a control and management unit, an energy consumption analysis and optimization unit, and a user interaction and platform integration unit;

[0008] The Internet of Things access unit is configured to achieve unified access and management of multiple types and multiple protocols of Internet of Things devices, receive data from multiple types of Internet of Things devices, and perform data analysis and standard processing on the received data of the Internet of Things devices; the BIM model data integration unit associates the status of the Internet of Things device with the building structure and pipeline distribution based on the virtual-real combination mode, and provides spatial and geometric data to the energy consumption analysis and optimization unit to support the construction and optimization analysis of the overall energy consumption model of the building; the energy consumption analysis and optimization unit combines the operation data of the Internet of Things device with the BIM information, generates an energy consumption management strategy through energy consumption modeling, prediction and optimization algorithms, and transmits it to the control and management unit for execution; the control and management unit dynamically regulates the Internet of Things device through the Internet of Things access unit according to the optimization strategy, and feeds back the execution results to the platform integration unit through user interaction.

[0009] Furthermore, the BIM model data integration unit is configured to obtain the detailed spatial layout, pipeline arrangement and attribute information of the building components by importing standardized BIM model data, and bind the installation location and device parameters of the Internet of Things device with the spatial data in the BIM model to achieve a one-to-one correspondence between the building and the equipment.

[0010] Furthermore, the BIM model data integration unit is configured to be able to define logical relationships and scene linkage between devices through the BIM model.

[0011] Furthermore, the Internet of Things access unit is configured with an edge computing module, and the edge computing module can execute corresponding control logic in local calculation.

[0012] Furthermore, the IoT access unit is configured with a dynamic device identification and adaptive access module, which can quickly identify and access IoT devices of different brands and types through device registration and data frame automatic parsing mechanism.

[0013] Furthermore, the control and management unit is provided with a scene automation operation module, which is based on rule engine technology and realizes flexible configuration and real-time adjustment of scene automation operation through predefined rules and dynamic scene logic generation function.

[0014] Furthermore, the control and management unit is configured with an event-driven and priority scheduling algorithm module, which is based on a distributed control architecture and is equipped with an efficient task distribution and execution mechanism. Through the event-driven and priority scheduling algorithm, concurrent control and resource optimization configuration of multiple devices are performed.

[0015] Furthermore, the energy consumption analysis and optimization unit obtains real-time energy usage data by interacting and collaborating with the Internet of Things access unit data, and monitors and analyzes energy consumption in combination with the building structure and equipment layout information provided by the BIM model data integration unit. At the same time, it can also generate corresponding optimization strategies based on the analysis results and feed them back to the control and management unit to execute dynamic energy efficiency adjustment.

[0016] Furthermore, the multi-source data fusion module in the energy consumption analysis and optimization unit can dynamically associate the real-time energy consumption data collected by the Internet of Things access unit with the building geometry, spatial distribution and equipment attribute data in the BIM model, and map the real-time data of the Internet of Things device to the specific space or component of the BIM model through standardized data interfaces and semantic models, thereby realizing dynamic association and scenario-based expression of energy consumption information.

[0017] Furthermore, the user interaction and platform integration unit is configured with a multi-terminal interaction module and / or a cross-platform integration and open interface.

[0018] The BIM-based whole-house intelligent control system solution provided by the present invention can achieve deep integration of smart home devices and building information, and improve management and use efficiency.

[0019] The solution of the present invention uses the three-dimensional data of the BIM model to associate the spatial layout and pipeline distribution of the building with the installation location of the smart device, forming a virtual-real mapping, and realizing centralized management and visual monitoring of the equipment. Unlike traditional smart home systems, this system is compatible with multiple Internet of Things protocols, breaking down the communication barriers between devices, realizing the coordinated operation of multi-brand and multi-type devices, and avoiding the problem of information islands; based on this, users can remotely control the system through the platform, greatly improving the living experience.

[0020] The solution of the present invention performs energy consumption analysis based on BIM data, monitors the energy consumption of each device in real time, identifies high-energy consumption areas, and provides energy-saving optimization suggestions, such as intelligent adjustment of lighting and temperature control equipment, to promote the development of green buildings.

[0021] The solution of the present invention can monitor the health status of equipment operation by linking sensors with BIM models. Once a fault occurs, the system will automatically push an alarm message, support remote repair and predictive maintenance, reduce downtime and extend equipment life.

[0022] The solution of the present invention has good scalability and can be seamlessly connected with the property management platform, energy management system and smart community services to form a smart ecosystem, providing users and managers with efficient, intelligent and sustainable living and operation solutions, reducing comprehensive management costs, and facilitating the intelligent and sustainable operation of buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0024] Figure 1 This is a system schematic diagram of the BIM-based whole-house intelligent control system in the present invention.

[0025] Figure 2 This is a schematic diagram of the structure of the model data integration unit in the present invention;

[0026] Figure 3 This is a schematic diagram of the composition of the Internet of Things access unit in the present invention;

[0027] Figure 4 This is a schematic diagram of the structure of the control and management unit in the present invention;

[0028] Figure 5 This is a schematic diagram of the composition of the energy consumption analysis and optimization unit in the present invention;

[0029] Figure 6 This is a schematic diagram of the composition of the user interaction and platform integration unit in the present invention. DETAILED DESCRIPTION

[0030] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further described below with reference to specific diagrams.

[0031] By fully studying the technical characteristics and problems of the composition and operation scheme of the building information model (BIM) and smart home devices, the solution of the present invention builds a new data fusion and dynamic mapping mechanism between the building information model (BIM) and smart home devices to support real-time status updates, thereby realizing two-way control and status connection of virtual and real scenes.

[0032] In the solution of the present invention, an Internet of Things access unit is provided, based on which real-time data of smart home devices of multiple types and multiple protocols (i.e., Internet of Things devices) are connected to the system, and the device data is mapped to the corresponding components or spaces in the BIM model through data analysis and standardized interfaces.

[0033] On this basis, the solution of the present invention provides a BIM model data integration unit, and uses the architectural geometry information, spatial distribution and attribute data of the BIM model to associate and fuse with the mapped IoT device data, thereby forming a dynamic association with the operating status of the IoT device and realizing device mapping that integrates virtual and real.

[0034] Furthermore, the solution of the present invention provides an intelligent analysis unit and an energy consumption analysis and optimization unit. The intelligent analysis unit generates cross-device collaborative control strategies based on fused data, such as automatic scene switching, multi-device linkage, etc., through adaptive algorithms and scenario rule engines; at the same time, the energy consumption analysis and optimization unit uses the global spatial data and real-time energy consumption information of the BIM model to model and optimize the overall energy consumption of the building, generate dynamic energy-saving strategies and transmit them to the control and management unit for execution.

[0035] On this basis, the present invention provides a whole-house intelligent control system based on BIM, which realizes the deep integration of BIM model (Building Information Model) and smart home devices (i.e., Internet of Things devices), thereby realizing two-way data interaction between BIM model and home Internet of Things devices, realizing equipment management, energy consumption optimization, automatic control and remote operation and maintenance, and improving users' living experience and equipment management efficiency.

[0036] See also Figure 1 The BIM-based whole-house intelligent control system 600 provided by the present invention is mainly composed of five functional units, namely, a BIM model data integration unit 100, an Internet of Things access unit 200, a control and management unit 300, an energy consumption analysis and optimization unit 400, and a user interaction and platform integration unit 500, which cooperate with each other.

[0037] In this control system, the BIM model data integration unit 100 is configured to achieve close coupling and efficient collaboration with the Internet of Things access unit 200, the control and management unit 300, and the energy consumption analysis and optimization unit 400 through data flow and functional logic; on this basis, the three-dimensional BIM model of the building and the Internet of Things device can be data-fused, and a virtual-reality mapping can be formed between the building structure, pipeline distribution and the status of the Internet of Things device.

[0038] Specifically, the BIM model data integration unit 100 can receive the operation data collected by the IoT device in real time through the IoT access unit 200, and dynamically map the data to the three-dimensional BIM model to form a virtual-real integrated building information representation. The generated mapping information is transmitted to the control and management unit 300 through the data interface, so that the control and management unit 300 can realize dynamic monitoring of the building structure, equipment status and pipeline operation.

[0039] At the same time, the BIM model data integration unit 100 also sends the processed fusion data to the energy consumption analysis and optimization unit 400 for functional analysis such as fault diagnosis, energy consumption optimization and equipment life prediction.

[0040] The BIM model data integration unit 100 also interacts with the platform integration unit 500 through data interaction with the user, and displays the dynamic building information mapped between virtual and real to the user in the form of a three-dimensional model, thereby enhancing the system's operational intuitiveness and management efficiency.

[0041] Furthermore, the BIM model data integration unit 100 can also interact with the operation and maintenance management unit to provide data support for the entire life cycle of the building and achieve efficient operation and maintenance based on the actual status.

[0042] See also Figure 2 As a further explanation, when implemented, the BIM model data integration unit 100 is configured with a standardized data interface module 110, which integrates multiple data communication protocols and multi-protocol adaptation function modules, thereby effectively overcoming the data format and protocol differences between the BIM model and multiple types of IoT devices, and achieving efficient data interaction and integration.

[0043] The BIM model data integration unit 100 is provided with a dynamic data mapping module 120, which can parse the status information of the received IoT devices in real time and map it to the corresponding building components or space elements in the BIM model, thereby realizing dynamic update of virtual-reality mapping.

[0044] The BIM model data integration unit 100 is configured with a rule engine-based logic association algorithm module 130, which can automatically generate collaborative relationships and control logic between IoT devices in combination with the geometry and attribute data of the BIM model.

[0045] Furthermore, when such a BIM model data integration unit 100 is implemented, it is preferably based on a distributed data processing architecture to accelerate the parsing and processing of multi-device data through distributed computing.

[0046] In addition, in response to real-time requirements, an event-driven mechanism is adopted to achieve efficient linkage between the IoT device status and BIM model updates.

[0047] In this control system, the Internet of Things access unit 200 is configured to achieve unified access and management of multi-type and multi-protocol Internet of Things devices. Through unified protocol adaptation and interface standardization, the Internet of Things access unit 200 achieves seamless connection with the BIM model data integration unit 100, the control and management unit 300, the energy consumption analysis and optimization unit 400 and the user interaction and platform integration unit 500 in this system.

[0048] Specifically, the IoT access unit 200 is configured to receive data from multiple types of IoT devices, and can parse and standardize the received data from the IoT devices and pass them to the data processing unit for preprocessing, while providing the BIM model data integration unit 100 with real-time status information of the IoT devices for dynamic mapping and model updating.

[0049] The IoT access unit 200 can also collaborate with the operation and maintenance management unit to achieve unified management of device status and fault alarm functions, thereby building an efficient data collection and management system.

[0050] See also Figure 3 As a further explanation, when the IoT access unit 200 is implemented, it is specifically configured with a multi-protocol unified adaptation layer 210. The multi-protocol unified adaptation layer 210 is based on multi-protocol adaptation technology and integrates support for mainstream IoT protocols including MQTT, CoAP, ZigBee, BACnet, etc., thereby effectively solving data compatibility issues in a multi-device, multi-protocol environment.

[0051] The IoT access unit 200 is provided with a dynamic device identification and adaptive access module 220, which can realize rapid identification and access of IoT devices of different brands and types through device registration and data frame automatic parsing mechanism, thereby improving access efficiency.

[0052] The IoT access unit 200 is also configured with an edge computing module 230, which can sink part of the data processing functions to the access node to reduce the system data transmission delay and improve real-time performance.

[0053] The IoT access unit 200 is also embedded with a standardized data model generation module 240. Based on the standardized data model generation module 240, the device operation data can be converted into a unified data structure to achieve unified data management, which is convenient for subsequent units to use.

[0054] The IoT access unit 200 preferably uses a distributed cache mechanism to temporarily store and optimize transmission of device status and operation data to enhance system stability in high-concurrency scenarios.

[0055] In this control system, the control and management unit 300 is configured to be able to perform one or more operations including centralized control, status monitoring, fault management or scene automation operations on the connected IoT devices.

[0056] The control and management unit 300 specifically obtains the real-time status information of the connected IoT devices and the mapping information in the three-dimensional BIM model fed back by the BIM model data integration unit 100 through data interaction with the IoT access unit 200 and the BIM model data integration unit 100, and implements centralized control, status monitoring and fault management operations based on the analysis results.

[0057] The control and management unit 300 is also configured to work in conjunction with the energy consumption analysis and optimization unit 400 to execute scene automation operations or optimize control strategies based on prediction results.

[0058] The control and management unit 300 is also configured to cooperate with the operation and maintenance management unit to achieve synchronous updating of equipment operation and maintenance records and closed-loop management of abnormal events.

[0059] The control and management unit 300 is also configured to be able to interact with the user and the platform integration unit 500 to exchange data, and present the control status and operation feedback in a visual form to ensure the real-time and transparency of the operation.

[0060] See also Figure 4 As a further explanation, in the specific implementation, the control and management unit 300 is configured with an event-driven and priority scheduling algorithm module 310. The event-driven and priority scheduling algorithm module 310 is based on a distributed control architecture and is provided with an efficient task distribution and execution mechanism. Through the event-driven and priority scheduling algorithm, concurrent control and resource optimization configuration of multiple devices are realized.

[0061] The control and management unit 300 is provided with a scene automation operation module 320 . The scene automation operation module 320 is based on rule engine technology and realizes flexible configuration and real-time adjustment of scene automation operation through predefined rules and dynamic scene logic generation function.

[0062] The control and management unit 300 has an embedded machine learning model 330, which is specifically used for equipment fault prediction and operation mode optimization. It can dynamically adjust the control strategy in combination with real-time status data, and can effectively improve the intelligence level of the system.

[0063] The control and management unit 300 is provided with a standardized instruction conversion module 340, which can support unified control of multiple IoT protocols, thereby effectively realizing centralized management of cross-protocol devices.

[0064] A bidirectional data flow mechanism is provided in the control and management unit 300 to achieve low-latency synchronization of control instructions and device feedback, thereby ensuring system response speed and execution reliability.

[0065] The control and management unit 300 is configured with a visualization module 350, which enables the control and management unit to display device status and execution feedback in real time, providing an intuitive interactive experience for the user.

[0066] In the present control system, the energy consumption analysis and optimization unit 400 is configured to monitor, analyze and optimize the energy usage status of the building in real time.

[0067] The energy consumption analysis and optimization unit 400 obtains real-time energy usage data by interacting and collaborating with the Internet of Things access unit 200, and monitors and analyzes energy consumption in combination with the building structure and equipment layout information provided by the BIM model data integration unit 100. It can also generate corresponding optimization strategies based on the analysis results and feed them back to the control and management unit to execute dynamic energy efficiency adjustment.

[0068] The energy consumption analysis and optimization unit 400 can also collaborate with the operation and maintenance management unit to record historical energy consumption data for optimizing equipment maintenance plans, and visually display energy consumption status and optimization suggestions through a visual interaction unit, forming a closed-loop management system of monitoring, analysis, and optimization.

[0069] See also Figure 5 As a further explanation, when the energy consumption analysis and optimization unit 400 is implemented, it is specifically configured with a multi-source data fusion module 410. The multi-source data fusion module 410 can dynamically associate the real-time energy consumption data collected by the Internet of Things access unit 200 with the building geometry, spatial distribution and equipment attribute data in the BIM model, and map the real-time data of the Internet of Things device to the specific space or component of the BIM model through a standardized data interface and semantic model, thereby realizing the dynamic association and scenario-based expression of energy consumption information.

[0070] The energy consumption analysis and optimization unit 400 is configured with an energy consumption prediction algorithm module 420. The energy consumption prediction algorithm module 420 is based on artificial intelligence and uses an LSTM machine learning model algorithm to perform trend analysis on the historical energy consumption data and real-time operating status of the building to generate high-precision energy consumption prediction results.

[0071] The energy consumption analysis and optimization unit 400 is also configured with an adaptive optimization algorithm module 430, which uses a heuristic particle swarm optimization algorithm to generate an optimal energy consumption control strategy that meets constraints (such as comfort and equipment load), thereby optimizing energy use.

[0072] The energy consumption analysis and optimization unit 400 further utilizes a distributed computing architecture to perform parallel processing on large-scale data, ensuring the real-time and high efficiency of the energy consumption analysis, converting the analysis results into executable optimization instructions, and implementing them through the control and management unit 300.

[0073] In this control system, the user interaction and platform integration unit 500 is configured to integrate a multi-terminal interaction mode, and can control and manage the connected Internet of Things devices.

[0074] Specifically, the user interaction and platform integration unit 500 realizes remote control, status viewing and operation instruction transmission of the IoT device by the user through data connection with the control and management unit 300; at the same time, it connects with the energy consumption analysis and optimization unit 400 to present the energy consumption status and optimization suggestions to the user terminal. It dynamically displays the real-time data of the access device through data interaction with the IoT access unit 200, and can also be linked with the BIM model data integration unit 100 to provide a three-dimensional visual interactive interface.

[0075] Furthermore, the user interaction and platform integration unit 500 can also collaborate with the operation and maintenance management unit to achieve synchronous update of equipment operation and maintenance information and push of fault notifications, thereby enhancing the convenience and intelligence of system operation.

[0076] See also Figure 6 As a further explanation, the user interaction and platform integration unit 500 is configured with an interface module 510 during its specific implementation. The interface module 510 adopts multi-protocol adaptation technology and integrates support for mainstream communication protocols including RESTfulAPI, MQTT, and WebSocket, thereby enabling efficient data interaction between user terminals and IoT devices.

[0077] The user interaction and platform integration unit 500 is configured with a real-time data push mechanism, which combines event-driven architecture and data flow technology to ensure low-latency transmission of device status, alarm information and control feedback; at the same time, through voice recognition and natural language processing (NLP) technology, it supports users to achieve convenient interaction in various scenarios in the form of voice or text.

[0078] The user interaction and platform integration unit 500 preferentially introduces the cross-platform development framework Flutter, integrates the BIM model visualization technology, and uses the three-dimensional rendering engine Unity3D to dynamically display the building structure, equipment distribution and status information.

[0079] In the BIM-based whole-house intelligent control system 600 formed based on the above scheme, the Internet of Things access unit 200 serves as a data entry to complete the access and real-time collection of status data of multi-type and multi-protocol devices, and transmits the information to the BIM model data integration unit 100 through standardized data conversion, ensuring dynamic mapping between device information and three-dimensional models.

[0080] As the data hub of the system, the BIM model data integration unit 100 uses virtual-real integration technology to associate the equipment status with the building structure and pipeline distribution, and provides space and geometric data to the energy consumption analysis and optimization unit 400 to support the construction and optimization analysis of the overall energy consumption model of the building. At the same time, the energy consumption analysis and optimization unit 400 combines the equipment operation data with BIM information, generates an efficient energy consumption management strategy through energy consumption modeling, prediction and optimization algorithms, and passes it to the control and management unit 300 for execution. As the core execution module, the control and management unit 300 dynamically regulates the equipment according to the optimization strategy, and feedbacks the execution results to the platform integration unit 500 through user interaction.

[0081] In this whole-house intelligent control system 600, the four units of BIM model data integration unit 100, Internet of Things access unit 200, control and management unit 300, and energy consumption analysis and optimization unit 400 form a tight logical closed loop through data flow, optimization strategy and execution feedback, realizing the whole process coordination from data collection to analysis and optimization to control execution.

[0082] With respect to the BIM-based whole-house intelligent control system 600 provided in the present invention, its implementation scheme and corresponding technical features are explained below through specific examples.

[0083] The BIM model data integration unit 100 in this control system, when implemented, first obtains the detailed spatial layout, pipeline layout and property information of the building components by importing standardized BIM model data (including IFC, RVT, RFA and other formats); the installation location and equipment parameters of the IoT device are obtained through the IoT access unit, including the initial location information and equipment identification code recorded by the equipment management system when the equipment is installed, and the dynamic parameter data collected in real time by sensors and controllers when the equipment is running. In addition, static data such as equipment type, model and operating characteristics are directly obtained through the standardized equipment configuration file provided by the equipment manufacturer or the communication protocol interface with the equipment. This information is integrated with the BIM model after data standardization processing to achieve accurate data input.

[0084] On this basis, the installation location and device parameters of the IoT device are further bound to the spatial data in the BIM model, where the device data and the spatial information in the BIM model are realized through a binding scheme based on a unique identifier (UID). Each IoT device is assigned a unique device ID in the IoT access unit, and a matching ID attribute is added to the corresponding spatial position or component in the BIM model. Through geometric coordinate positioning and attribute matching algorithms, the actual installation location of the device is associated with the spatial node or component in the BIM model to ensure that the equipment operation data can be accurately mapped to the building model, and dynamic binding and real-time updates are achieved to determine the one-to-one correspondence between the building and the equipment. Based on this, it is possible to achieve data fusion between the three-dimensional model of the building and the IoT device, realize the virtual-real mapping of the building structure, pipeline distribution and the status of the intelligent device, and provide support for the unified management and operation and maintenance of the equipment.

[0085] In some embodiments, through this mapping, the control system can display the status information of lighting, temperature control, sensors and security equipment in real time in the three-dimensional BIM model, so that users and managers can intuitively understand the distribution and operation of the equipment and improve the accuracy and efficiency of management.

[0086] In some embodiments, the BIM model data integration unit 100 is also configured to support multiple types of building models and data formats. Specifically, a multi-format parsing engine is built into the BIM model data integration unit 100 to support automatic recognition and parsing of common BIM formats (such as IFC, RVT, RFA, DWG, etc.). The parsing process converts building geometry information, spatial layout, and component attributes in different formats into a unified data structure through semantic model mapping.

[0087] In some embodiments, the BIM model data integration unit 100 is configured to adopt a dynamic expansion mechanism based on a data model, connect with an external system through an open API interface, and obtain progress information in the construction phase and equipment operation data in the operation and maintenance phase.

[0088] As a further explanation, in terms of processing logic, the data is first standardized to ensure format consistency; then the parsed data is bound to the corresponding BIM object through the attribute matching algorithm; finally, the incremental update mechanism is used to dynamically integrate multi-stage data to ensure the real-time and accuracy of the model information, thereby supporting the management and application of model data throughout the life cycle, thus ensuring seamless connection with the data in the design, construction and operation and maintenance stages.

[0089] In some embodiments, the BIM model data integration unit 100 reads standardized model files such as IFC and RVT by configuring a multi-format parsing engine, extracts the building's geometric information, spatial layout, room attributes, and pipeline layout, and converts them into a unified semantic data structure. Subsequently, the multi-source model data is dynamically integrated through attribute matching and geometric positioning algorithms to form a complete building information model integration.

[0090] As a further explanation, during the model integration process, the unit automatically identifies the best installation location for the equipment through the built-in spatial analysis engine and geometric calculation module, combined with the room functions, pipeline layout and spatial geometric characteristics in the BIM model. Furthermore, logically, the system first performs semantic analysis on the functional partitions of the room and matches the corresponding equipment types; calculates installation constraints (such as space dimensions, location accessibility, etc.) based on the equipment operation requirements and the geometric characteristics of the building; finally, by simulating the equipment operation path and the spatial interaction effect, the installation plan is optimized and reference suggestions are output. Based on this optimized setting, the system can automatically read and analyze the spatial structure, room functions and pipeline layout of the building, and provide a reference for the installation and operation of smart devices.

[0091] In some embodiments, the BIM model data integration unit 100 may also be configured with an automatic identification function module, which is used to scan and identify installed smart devices, and collect the unique identification information of the device through RFID, NFC or QR code scanning technology, and obtain the device model, status and protocol data through the protocol parsing module of the Internet of Things access unit. In this way, the formed system can match the device type library in the BIM database by scanning the device identification; using dynamic data parsing and standardized processing technology, the information such as the device operating status and communication protocol is entered into the BIM database and bound to the corresponding model object. This can further reduce manual operations and improve the efficiency of equipment registration and management.

[0092] In some embodiments, the BIM model data integration unit 100 is specifically configured to adopt a two-way data interaction mechanism, obtain the device status in real time through the Internet of Things access unit 200, synchronize the updated data to the BIM model, and send the control instructions or configuration parameters in the BIM model to the device.

[0093] In the specific implementation, the system introduces event-driven mechanism and real-time communication technology based on WebSocket to ensure low-latency upload of equipment data and dynamic update of BIM model. At the same time, through standardized interface and protocol conversion module, two-way parsing and transmission of control instructions and equipment data are realized, forming continuous synchronization and efficient interaction between equipment and BIM model.

[0094] Accordingly, when the state of an IoT device changes, the IoT access unit 200 captures the change through an event-driven mechanism and uploads the state data to the BIM model data integration unit 100. The BIM model data integration unit 100 standardizes the data through the state analysis module, matches the corresponding BIM model object through the device unique identifier, and updates its properties (such as light brightness, temperature value) in real time. The updated information is dynamically presented in the BIM model through the three-dimensional rendering engine, allowing users to intuitively view the latest operating status of the device and its architectural space association in the three-dimensional interface, and achieve real-time feedback.

[0095] Furthermore, when the user sends a control command through the BIM model platform, the command processing module of the system converts the operation into a standardized command that can be recognized by the device, and locates the target device through the device unique identifier. After the command is parsed by the protocol conversion module of the Internet of Things access unit 200, it is transmitted to the corresponding Internet of Things device for execution in real time. After the device completes the command, the Internet of Things access unit 200 obtains the execution result information, and feeds the execution result back to the BIM model data integration unit 100, updates the device status in the three-dimensional model, and realizes virtual-real synchronization.

[0096] The above-mentioned two-way interaction mechanism ensures the accuracy of remote control, while providing real-time data support and efficient execution capabilities for scene automation management.

[0097] In some embodiments, the BIM model data integration unit 100 also supports multi-device linkage control in complex scenarios, and realizes the definition of logical relationships between devices and scene linkage through the BIM model. Specifically, the BIM model data integration unit 100 defines the linkage logic between devices (such as light adjustment with temperature changes) based on the spatial layout and device attributes in the BIM model, combined with the scene rule library; in this way, when the trigger condition is met, the rule engine generates a linkage instruction and distributes the instruction to the relevant equipment through the Internet of Things access unit; at the same time, the linkage result is fed back to the BIM model in real time, and the device status is dynamically updated to achieve accurate execution and intuitive display of multi-device collaborative operations.

[0098] Accordingly, this system solution can obtain the spatial layout, equipment location and pipeline layout information of the building through the BIM model data integration unit 100, and realize automatic equipment control in combination with the scene logic defined by the rule engine. When the user leaves, the system triggers the linkage rule and shuts down non-essential equipment through the control unit to improve energy efficiency. In addition, when the equipment fails, the system uses the three-dimensional pipeline data and equipment identification of the BIM model to quickly locate the fault point, and calculates the shortest maintenance path through the path optimization algorithm, and presents it visually, helping managers to efficiently complete fault diagnosis and maintenance tasks and realize intelligent operation and maintenance management.

[0099] Specifically, based on this, the system can generate maintenance plans and life predictions for equipment based on data such as equipment operating time and frequency of use, combined with the location and maintenance records in the BIM model. The system collects dynamic data such as equipment operating time and frequency of use through the Internet of Things access unit 200, and uses regression analysis to predict equipment life in combination with the equipment location and historical maintenance records in the BIM model. Based on the prediction results and equipment operating characteristics, the system generates an optimized maintenance plan through a rule engine, integrates it with the spatial information of the equipment location, and outputs a visual maintenance path and maintenance task table. This logical process realizes accurate prediction and efficient maintenance of equipment status, providing technical support for full life cycle management. As an example, when a device is about to enter a fault state, the system will issue an early warning and mark the installation location of the specific equipment in the BIM model to support predictive maintenance and reduce equipment downtime.

[0100] In some embodiments, the BIM model data integration unit 100 is also configured with corresponding visual BIM editing tools to improve the flexibility of the system. The module provides that users can adjust the equipment layout, update equipment information or add new equipment according to actual needs to achieve dynamic expansion of the system.

[0101] In some embodiments, the IoT access unit 200 in the system realizes unified access of multiple types of devices through a multi-protocol adaptation layer during specific implementation, and supports parsing and conversion of mainstream protocols including MQTT, ZigBee, CoAP and private protocols.

[0102] On this basis, dynamic device identification and registration technology is further adopted to automatically register device information through a unique device ID. At the same time, based on the edge computing framework, some data processing functions are transferred to access nodes to reduce the system center load and improve real-time response capabilities.

[0103] The IoT access unit 200 also uses a standardized data model to unify the format of access data, ensuring efficient transmission of device status information and control instructions, and providing a stable connection for the whole-house smart system.

[0104] In some implementations, the IoT access unit 200 specifically integrates multiple communication protocols (including Wi-Fi, ZigBee, Bluetooth BLE, LoRa, etc.), and adopts a protocol analysis and conversion mechanism to realize the unified conversion of data from devices of different brands into a standardized format, and semantically integrates device information through semantic model mapping. On this basis, dynamic device adaptation technology and a unified interface API are used to achieve seamless docking and centralized management of different types of devices, and support seamless docking of smart devices of different brands and types with the system, which can effectively solve the problems of poor device compatibility and data islands in traditional smart homes.

[0105] In some embodiments, the IoT access unit 200 integrates automatic discovery protocols (such as mDNS, UPnP) and broadcast mechanisms to achieve rapid access and identification of devices. In a specific implementation, the unit scans the devices in the network, parses the type, status, and parameter information of the devices through the protocol adaptation layer, and generates a unique identifier (such as device ID). The device information is transmitted to the BIM model data integration unit through a standardized data interface, and the device is bound to the corresponding space or component in the BIM model in combination with the geometric coordinates and attribute matching algorithm. On this basis, this unit updates the real-time status of the device to the BIM model through a dynamic data synchronization mechanism, realizing centralized management and three-dimensional visual monitoring of the entire house equipment. This can greatly improve the efficiency of device access and the intuitiveness of system operation.

[0106] In some embodiments, the IoT access unit 200 uses multi-level data collection and communication technology during device access to achieve efficient data transmission and reliable device management. Specifically, the unit implements diversified access to devices with different communication protocols by embedding multi-protocol communication modules including Wi-Fi, ZigBee, BLE, and LoRa.

[0107] Among them, data collection is divided into three layers: device-side data, network layer data, and system status data: the device side collects operating status through sensors, the network layer uses the edge computing framework to monitor data flow and latency in real time, and the system layer aggregates and transmits device control instructions through an event-driven mechanism. This Internet of Things access unit 200 preferably uses Kafka distributed queue management multi-protocol communication to ensure orderly data transmission under high concurrency, and combines data standardization and semantic parsing technology to integrate multi-level data into a unified format and transmit it to the system core module, achieving stable and efficient data collection and communication capabilities.

[0108] In some embodiments, the IoT access unit 200 has built-in corresponding protocol converters and gateway management functions. The protocol converter uses dynamic adaptation technology to support data format parsing and standardized conversion between protocols such as Wi-Fi, ZigBee, BLE, and LoRa; the gateway management function is based on dynamic routing algorithms and load balancing technology to optimize device communication paths and ensure low latency and high reliability. In addition, the unit integrates a bidirectional buffer and data retransmission mechanism to achieve complete synchronization and loss compensation of data in the event of network fluctuations, ensuring stable communication and system connection performance of multi-protocol devices. In this way, devices with different communication protocols can achieve stable connections in complex network environments.

[0109] As an example, sensor data that can be accessed through the ZigBee protocol will be automatically uploaded to the system platform, and Wi-Fi devices can interact directly through the LAN connection.

[0110] In some implementations, a corresponding edge computing module is provided in the IoT access unit 200 to implement rapid execution of local control logic through a lightweight computing framework (such as Docker or K3s).

[0111] Specifically, the technical means of implementation include built-in rule engines and event-driven mechanisms, which sink simple logic such as light adjustment or temperature sensing to local processing; data is collected in real time through device sensors and directly executes control instructions after being parsed by edge nodes. This process does not rely on the cloud, reduces data round-trip delays, and improves response speed and real-time device control, ensuring that the system still has efficient operation capabilities in low-bandwidth or offline scenarios.

[0112] As an example, the edge computing module can execute some simple control logic locally on the device, such as automatic lighting adjustment and temperature sensing control, thereby reducing network latency and improving response speed.

[0113] In some embodiments, the IoT access unit 200 can also automatically scan the network environment, so that when a new device is added, it can promptly discover the new device and guide the user to quickly pair and register. When the new device responds, the module extracts the device type, ID and other information through protocol parsing technology, and guides the user to complete the quick pairing and registration in combination with the user interaction interface. The device information is then recorded in the system database through standardized processing and bound to the BIM model, achieving seamless access and centralized management of the device, thereby greatly improving the convenience of device expansion.

[0114] In some implementations, the IoT access unit 200 adopts a distributed network architecture and a multi-layer security strategy to ensure the stability and security of device access.

[0115] In some implementations, the Internet of Things access unit 200 supports flexible configuration of the main network and subnets through a built-in network hierarchical management module.

[0116] Specifically, dynamic routing allocation algorithms and load balancing technology can be used to automatically divide subnets according to the number of devices and network load, and adjust the distribution of devices between the main network and subnets to optimize traffic. Using the subnet gateway management mechanism, device communications are handled within the subnet to reduce congestion in the main network. The main network and subnets achieve efficient data aggregation and synchronization through gateway nodes, ensuring communication stability and system response efficiency in large-scale device access scenarios.

[0117] In some implementations, the IoT access unit 200 ensures the security of device access through a multi-layer security mechanism.

[0118] Specifically, TLS / SSL end-to-end encryption technology can be used to ensure the confidentiality of data during transmission; the integrated device authentication module verifies the device identity through digital certificates based on the public key infrastructure (PKI) to prevent unauthorized device access. At the same time, the permission management module is used to assign access rights according to device type and user role to restrict sensitive operations. In addition, the intrusion detection system (IDS) is combined to monitor abnormal behavior in real time and take blocking measures to effectively defend against malicious attacks and illegal access.

[0119] Accordingly, during normal operation, the IoT access unit 200 will regularly collect the operating data of the equipment and synchronize it to the three-dimensional model of the BIM platform to achieve visual monitoring of the equipment status. When an abnormal situation is found in the equipment (such as overload, disconnection or sensor failure), the system will automatically send an alarm notification and mark the location of the specific equipment in the BIM model to help users or property management personnel quickly locate and handle the problem.

[0120] In some implementations, the IoT access unit 200 supports the access of smart meters, lighting equipment, and air conditioning systems, and utilizes multi-protocol adaptation technology to collect power consumption data of each device in real time.

[0121] Specifically, after the data is standardized, it is bound to the regional space in the BIM model through a dynamic data mapping mechanism and transmitted to the energy consumption analysis tool configured in the energy consumption analysis and optimization unit 400. In this way, the system combines the spatial layout and equipment distribution of the BIM model to intuitively present the energy consumption of different areas in the form of heat maps or layered maps, helping users to quickly identify high-energy consumption areas, optimize electricity consumption strategies, and achieve refined management of building energy consumption.

[0122] In some implementations, the IoT access unit 200 is connected to an energy management system (EMS) via a standardized interface, and uses distributed control technology to achieve intelligent scheduling of distributed energy.

[0123] Specifically, the IoT access unit 200 can collect data from photovoltaic, battery energy storage and load devices in real time, and the energy consumption analysis and optimization unit 400 uses load prediction algorithms and optimization scheduling algorithms (such as linear programming or dynamic programming) to calculate the optimal energy allocation strategy. The strategy is sent to relevant energy devices through the protocol conversion module to achieve dynamic scheduling and real-time balance of energy. The feedback data is updated to the EMS through a closed-loop correction mechanism to improve the system's responsiveness to energy fluctuations and ensure the overall energy utilization efficiency and operational stability of large buildings or communities.

[0124] In some embodiments, the IoT access unit 200 achieves real-time control and data synchronization of complex scenarios by integrating high-speed communication protocols including Wi-Fi6, 5G, and edge computing frameworks.

[0125] Specifically, the communication layer uses UDP and WebSocket low-latency data transmission technology to ensure millisecond-level response of instructions and feedback. The edge computing module pre-processes real-time data, reduces the processing load of core nodes and improves data synchronization efficiency through event-driven architecture and distributed caching mechanism, and realizes real-time collaborative control in complex scenarios.

[0126] In some implementations, the IoT access unit 200 supports open connection with a third-party platform, and is integrated with smart property and smart community platforms through an API interface to further enhance the management capabilities of the system.

[0127] In some embodiments, the control and management unit 300 in the system is implemented in detail, through deep integration with the BIM model data integration unit 100 and the Internet of Things access unit 200, and uses a logical mapping technology based on a semantic model to bind the device location and attributes in the BIM with the unique identifier of the Internet of Things device to achieve accurate device identification. The control instructions are converted into standardized instructions through the protocol adaptation layer and transmitted to the target device through the Internet of Things access module; at the same time, the device status is synchronized to the BIM model in real time through an event-driven mechanism, and the operating status is updated in combination with three-dimensional visualization technology; on this basis, the control and management unit 300 also uses a rule engine and a priority scheduling algorithm to dynamically generate a multi-device collaborative control strategy to improve user experience and management efficiency.

[0128] In some implementations, the control and management unit 300 implements remote control and scenario-based management of smart devices through a built-in rule engine and an automated scenario management module.

[0129] Specifically, during implementation, dynamic rule generation based on the logic rule base is used to drive the collaborative operation of multiple devices through user-defined trigger conditions (such as time and environmental parameters). The scene management module combines device attributes, operating status and spatial information provided by the BIM model, adopts priority scheduling algorithms and energy consumption optimization strategies, and automatically performs personalized operations (such as lighting adjustment and temperature control optimization). Instructions are issued through the protocol conversion layer, combined with real-time data feedback to form a closed-loop control, realizing comprehensive intelligence and efficient management of the system.

[0130] In some embodiments, the control and management unit 300 is also configured to have a centralized control function for the equipment, and the equipment status data collected by the Internet of Things access unit is mapped to the BIM model; combined with the WebGL three-dimensional rendering engine, an interactive equipment view is dynamically generated. The user issues a control instruction through the PC interface, which is converted into a standardized instruction recognizable by the device after being processed by the rule engine, and is transmitted to the target device through the protocol adapter module to update the BIM model status in real time. In this way, the user can log in to the system through the PC application interface and manage the whole house equipment based on the visual interface of the BIM model. The user can view the real-time status of each device in the three-dimensional view of the BIM model, such as the switch status of the light, the temperature setting of the air conditioner, the operating status of the electrical appliance, etc., and control the device with a simple click.

[0131] In some implementations, the control and management unit 300 implements multi-device linkage control through a built-in rule engine and a logic association module.

[0132] Specifically, the control and management unit 300 uses a semantic model to analyze the logical relationship between the operation instructions issued by the user and the equipment based on the predefined scenario rule library. The rule engine dynamically generates a linkage strategy, sorts the multi-device control instructions by priority, and sends them to the relevant equipment synchronously through the protocol adapter module. The execution results are fed back to the BIM model in real time through the event-driven mechanism, the equipment status is updated and the linkage effect is verified, ensuring the accuracy and real-time performance of the collaborative operation of multiple devices, and meeting the intelligent control requirements in complex scenarios.

[0133] In some embodiments, the control and management unit 300 also supports users to preset scene modes and define trigger conditions and device linkage logic through a built-in scene management engine, using a rule engine and logic modeling technology. Users set scene trigger conditions (such as time, environmental parameters) and device linkage rules through a visual configuration interface, and the rule engine converts the settings into a logical tree structure and stores them in the scene rule library. When the trigger conditions are met, the scene management engine dynamically parses the logic tree and generates a linkage instruction set, which is synchronously sent to the target device through the protocol adapter module, and the BIM model status is updated in real time to achieve precise control and efficient execution of scene modes. As an example, the user can set the "away mode". When the system detects that the access control is closed and no one is staying, the system will automatically turn off the lights and electrical appliances, and enable the security mode; in the "home mode", the system will automatically turn on the lighting, adjust the temperature, and play background music when the user opens the door to provide a comfortable living environment.

[0134] Furthermore, with the data support of the BIM model, the scene management engine can intelligently optimize the equipment control plan according to the spatial layout and equipment distribution, thereby improving the efficiency and coordination of the system operation.

[0135] On this basis, it is also possible to further support automatic scene switching within seasonal or time periods, automatically adjust air-conditioning settings according to outdoor temperature, or automatically reduce lighting brightness at night to help users save energy.

[0136] In some implementations, the control and management unit 300 achieves refined energy consumption management by deeply integrating with BIM models and smart meters and adopting multi-source data fusion and dynamic data mapping technology.

[0137] Specifically, the control and management unit 300 collects the power consumption data of the equipment and area in real time through the Internet of Things access unit 200, and formats it using a standardized data model. After semantic analysis, these data are mapped to the corresponding space or device node in the BIM model through a unique identifier. The real-time power consumption information is dynamically presented in the user interface through a three-dimensional visualization engine, and the energy consumption distribution of the equipment and area is displayed in the form of a heat map or a layered map, which supports users to quickly identify high-energy consumption points and optimize energy use strategies. Based on this, the system can automatically generate analysis reports based on energy consumption data to help users understand high-energy consumption equipment and areas, and put forward specific energy-saving optimization suggestions, such as reducing standby energy consumption, adjusting air-conditioning temperature, or adjusting the operating time of electrical appliances. The control and management unit 300 also supports time-of-use electricity price management. During peak electricity price periods, the system will automatically reduce the operation of non-essential equipment to achieve green building goals.

[0138] In some embodiments, the control and management unit 300 continuously monitors the health status of the equipment and improves maintenance efficiency through a built-in health management and fault warning module combined with real-time operation data collected by sensors and IoT devices.

[0139] Specifically, the control and management unit 300 uses regression analysis and anomaly detection algorithms to perform trend analysis on equipment operating parameters (such as temperature, current, vibration, etc.), generate health scores and predict potential faults. After the data is standardized through the Internet of Things access unit 200, it is dynamically bound to the geometric information and attribute data of the equipment in the BIM model to update the health status and usage of the equipment in real time. Fault warning information is triggered by an event-driven mechanism and dynamically presented in the visual interface of the BIM model with color codes or identifiers, which makes it easy for managers to quickly locate problem equipment and formulate maintenance plans. At the same time, combined with the equipment's historical data, the system generates optimized maintenance suggestions and inspection paths to ensure the efficiency and safety of equipment operation, greatly improving the system's intelligent operation and maintenance capabilities and overall management efficiency.

[0140] Accordingly, when the system detects an abnormality (such as overload of temperature control equipment, long-term high-temperature operation of electrical appliances, sensor failure, etc.), it will automatically trigger an early warning and push notifications to users or managers. At the same time, the system marks the location and fault type of abnormal equipment in the BIM model, making it easier for maintenance personnel to quickly locate and handle problems. The module also supports predictive maintenance, predicting the risk of equipment failure based on the historical operating data and frequency of use of the equipment, and arranging maintenance plans in advance to avoid downtime losses caused by equipment failure.

[0141] As a further explanation, the control and management unit 300 is configured with remote control and authority management functions, and supports users to perform remote operations via the Internet. Even if the user is not at home, he can view the device status and control it through the mobile phone APP.

[0142] Furthermore, the control and management unit 300 provides a flexible permission management function, which can allocate device access rights according to the roles and needs of different users. For example, family members can enjoy full device control rights, while visitors are limited to accessing lights and air conditioning equipment in public areas.

[0143] Furthermore, the control and management unit 300 also supports seamless integration with the property management platform. When a device fails, the system will automatically generate a repair work order and notify the property management personnel to handle it, reducing the user's management burden.

[0144] In some embodiments, the energy consumption analysis and optimization unit 400 in the system is implemented based on the data fusion of BIM models and IoT devices to dynamically collect and analyze the operating conditions of various electrical appliances, lighting systems, air-conditioning equipment, and other energy consumption sources, so as to provide users and managers with accurate energy consumption monitoring and optimization strategies. Through multi-dimensional data processing and intelligent algorithms, the unit can identify high-energy consumption equipment and operating modes, make energy-saving suggestions, and support automated control strategies to achieve efficient management of whole-house energy.

[0145] Specifically, the energy consumption analysis and optimization unit 400 is deeply integrated with energy equipment such as smart meters, lighting equipment, air conditioning systems, and household appliances through multi-protocol adaptation technology to build an energy consumption data collection system. The energy consumption analysis and optimization unit 400 uses the Internet of Things access unit 200 to collect data such as the power, operating hours, and environmental parameters of the equipment in real time, unifies the format through a standardized data processing module, and associates the unique identifier of the equipment. The collected data is bound to the corresponding equipment and regional nodes in the BIM model through dynamic data mapping technology, and combined with the time series database to store the historical energy consumption information of the equipment, providing an accurate data basis for energy consumption analysis and optimization, and supporting the overall energy consumption management of the building.

[0146] Based on this, the energy consumption data of all equipment will be uploaded to the system in real time and associated with the spatial information and usage scenarios in the BIM model. Specifically, the power consumption of the lighting system will be linked to the location and purpose of the specific room, and the energy consumption of the air conditioner will be associated with weather data and usage frequency. Through this data integration, users can intuitively view the real-time energy consumption data and historical records of each room, floor or equipment in the three-dimensional view of the BIM model, identify high-energy consumption areas or equipment, and adjust the equipment usage strategy based on data analysis.

[0147] In some embodiments, the energy consumption analysis and optimization unit 400 integrates the BIM model data through the energy consumption analysis tool, combines time series analysis and random forest algorithm to identify the power consumption pattern and equipment operation efficiency, and generates the optimization strategy through the rule engine. The equipment operation parameters are dynamically adjusted based on the load distribution algorithm, such as reducing the lighting power or adjusting the air conditioning operation cycle. For peak power consumption scenarios, the priority scheduling algorithm is used to control the start and stop of non-essential equipment, thereby optimizing the energy consumption distribution. The generated energy-saving instructions are transmitted to the target device through the protocol adapter module of the Internet of Things access unit, and the execution results are collected in real time and fed back to the analysis tool to achieve refined energy consumption management for green building goals.

[0148] Specifically, the energy consumption analysis and optimization unit 400 deeply explores the energy consumption patterns of equipment and regions by integrating LSTM, cluster analysis and anomaly detection algorithms. The system uses time series data analysis technology to process historical and real-time energy consumption data and extract periodic and abnormal features. Through model training, the system establishes an energy consumption baseline and monitors deviations in real time. When electricity consumption exceeds the baseline range, the anomaly detection module triggers an alarm and highlights the problem area or equipment in the BIM model through dynamic data mapping, supporting managers to quickly locate the source of the anomaly and optimize the energy consumption strategy. Accordingly, when the lighting system of a room is turned on for a long time without anyone, the system will automatically mark the abnormal behavior and prompt the user to adjust it; if the air-conditioning equipment is frequently started and the energy consumption increases abnormally, the system will combine the spatial layout of the BIM model to analyze whether there are problems such as windows not being closed or insufficient insulation measures, and give optimization suggestions. In addition, the module supports time-of-use electricity price management and automatically adjusts the equipment operation time according to the real-time electricity price information of the power company.

[0149] Furthermore, the energy consumption analysis and optimization unit 400 realizes an automated energy-saving control strategy through built-in dynamic programming and genetic algorithms. The system combines the spatial layout and equipment distribution of the BIM model to dynamically analyze real-time energy consumption data and environmental parameters. Based on the linkage logic predefined by the rule engine, energy-saving control strategies are automatically generated, such as adjusting lighting brightness, optimizing air-conditioning temperature, or adjusting equipment start and stop time. The strategy is synchronously sent to the device through the protocol adapter module of the Internet of Things access unit 200, and the execution effect is monitored in real time, and the optimization results are fed back to the BIM model to realize intelligent linkage and dynamic energy consumption management between devices. Based on this, the system can automatically adjust the operating status of the air conditioner and fan according to the weather forecast data and the feedback from the indoor temperature sensor; when there is sufficient light, the system will automatically lower the lighting brightness or turn off some lamps to reduce power consumption.

[0150] Furthermore, the energy consumption analysis and optimization unit 400 is equipped with an energy forecasting and early warning function, which specifically combines historical energy consumption data, equipment usage frequency and external weather factors, and establishes a forecasting model through multivariate regression model training. In this way, short-term and medium-term energy consumption forecasts are generated by inputting real-time data into the model after standardization. The forecast results generate targeted energy-saving strategies (including adjusting the operating time or load distribution of peak power equipment) through the rule engine and optimization algorithm. At the same time, the early warning module uses the prediction deviation to detect possible energy consumption anomalies, trigger an alarm and dynamically mark the problem area in the BIM model. Based on this, the system predicts future energy consumption trends and plans energy-saving strategies in advance by analyzing historical energy consumption data, equipment usage frequency, weather and other external factors.

[0151] In this way, the system can predict the surge in air conditioning energy consumption caused by hot weather, and recommend users to set the air conditioning temperature in advance to avoid excessive power load during peak hours. If a device has abnormal energy consumption or reduced efficiency, the module will generate a fault warning and mark the device location in the BIM model to prompt management personnel to perform maintenance. This predictive maintenance mechanism not only reduces the risk of equipment failure, but also avoids energy waste caused by equipment loss.

[0152] In this way, in commercial buildings, the system can be linked with the central air-conditioning system and the elevator management system to dynamically adjust the equipment operation status and improve energy efficiency; in smart communities, the system can be connected with distributed energy systems (such as photovoltaic power stations or energy storage devices) to achieve intelligent scheduling and balance of local energy. In addition, the module supports report generation and analysis of energy consumption data. Users and managers can regularly view detailed energy consumption reports, understand the energy consumption structure of the building, and optimize management strategies based on the analysis results.

[0153] In some embodiments, the energy consumption analysis and optimization unit 400 also supports multi-level user management and authority control. Different user roles (such as residents, property managers or energy operators) can view and manage corresponding data and equipment according to their authority to ensure the security and flexibility of the system.

[0154] In some embodiments, the user interaction and platform integration unit 500 in the system is implemented by integrating multiple terminal interaction methods, including PC management platform, voice assistant, wall control panel, etc., to enable users to flexibly control and manage the whole house equipment. The module also supports deep integration with BIM models, allowing users to perform intuitive operations in a three-dimensional visualization interface. In addition, it has high scalability and openness, and connects with third-party platforms and services through API interfaces to meet the needs of diverse scenarios in homes, businesses and communities.

[0155] In some embodiments, the user interaction and platform integration unit 500 integrates the BIM model to make user interaction more intuitive and efficient. The user can view the distribution and status of the equipment in the three-dimensional visualization interface and directly control the corresponding equipment by clicking on the objects in the model. When the user selects a room in the BIM model, he can quickly view all the lighting, air conditioning and electrical equipment in the space and perform batch control. The BIM model also supports real-time updates. The operating status, fault warnings and energy consumption data of the equipment will be synchronously displayed in the model to help users better understand the operation of the system. At the same time, when new equipment is connected or the scene changes, the system will automatically update the BIM model to ensure data consistency and real-time performance.

[0156] In some implementations, the user interaction and platform integration unit 500 supports multiple user accounts and permission hierarchical configuration, and different users can obtain corresponding device control permissions according to their roles.

[0157] For example, family members can enjoy control of all devices, while visitors can only control some devices in the public area. Property managers can view the operating status of public devices through the platform and receive system fault alerts.

[0158] In some embodiments, the user interaction and platform integration unit 500 realizes the learning and memory function of user preferences through the built-in user behavior analysis module and machine learning algorithm. The system uses behavioral data collection technology to record the user's operating habits, commonly used devices and preferred scenarios in the interface, and stores these data in the form of time series in the behavior database. Through collaborative filtering and K-means clustering algorithms, the system extracts the user's operating mode and preference characteristics. Based on the analysis results, the system dynamically adjusts the interface layout and places the user's commonly used devices, scenarios or functions in a prominent position (such as the main interface shortcut operation area). In this way, the system is more in line with user needs. The system will remember the user's commonly used devices and scenarios, and place them in a prominent position on the interface to improve the convenience of operation.

[0159] In some embodiments, the user interaction and platform integration unit 500 is configured with a cross-platform integration and open interface, thereby enabling in-depth docking with various third-party platforms and services through a standardized API interface to achieve functional expansion and interoperability.

[0160] For example, in smart communities, the system can be linked with the access control system to achieve seamless entry and exit based on facial recognition technology; in commercial buildings, the system can be connected with the energy management system (EMS) to optimize the operating logic of air conditioners and elevators and improve energy utilization efficiency.

[0161] In some implementations, the user interaction and platform integration unit 500 also supports integration with a property management system to achieve automated processing of fault alarms, equipment inspections, and work order management, thereby improving property management efficiency. For smart home users, the system can be connected to mainstream smart speakers and home appliance brand platforms to expand device compatibility and operational flexibility.

[0162] In some embodiments, the user interaction and platform integration unit 500 uses multiple identity authentication and data encryption technologies, and all user operations and data transmissions are strictly encrypted to prevent data leakage and illegal access, thereby ensuring the security and privacy of the system.

[0163] Specifically, the user interaction and platform integration unit 500 requires dual identity authentication when the user logs in for the first time, and can set up biometric (such as fingerprint or face) login as needed.

[0164] In some implementations, the user interaction and platform integration unit 500 has detailed operation logs and monitoring functions, and users and administrators can view the system's operation records at any time to promptly discover and handle abnormal behaviors.

[0165] In some implementations, the user interaction and platform integration unit 500 provides a multi-layer backup and data recovery mechanism to ensure the integrity and availability of data in the event of a network outage or system anomaly.

[0166] In some embodiments, the user interaction and platform integration unit 500 is configured with an intelligent notification and feedback mechanism, thereby supporting multi-channel notifications, including SMS, email, and voice reminders. When a device fails or detects an abnormality, the system will push alarm information in a timely manner. At the same time, users can report problems or make improvement suggestions to the system through the feedback mechanism, and the system will continuously optimize and upgrade according to user feedback to enhance the interactive experience.

[0167] Based on the above scheme, it can be known that the BIM-based whole-house intelligent control system scheme provided by the present invention is based on the data support capability of BIM (Building Information Model) for the entire life cycle of the building. By integrating BIM with IoT devices, the system can achieve unified management of devices of different brands and protocols, and improve the efficiency of device linkage control. At the same time, users can perform remote control and automated scene management through the BIM platform, such as automatically turning off lights and air conditioners in away mode, and adjusting room temperature and security equipment in sleep mode. This integration method simplifies user operations and improves the collaborative efficiency of equipment.

[0168] Based on the combination of BIM and the Internet of Things, the system can also monitor the energy consumption data of various types of equipment in real time and intuitively display high-energy consumption areas in the BIM model. Based on the analysis results, the system can provide optimization suggestions, such as adjusting the lighting brightness or reducing the air conditioning operation time, to achieve energy conservation and emission reduction goals. In addition, the system uses sensors to collect equipment health status data to support fault detection and predictive maintenance. When an abnormality occurs, the system will automatically push an alarm and mark the specific equipment location in the BIM model to help users and property management personnel perform remote operation and maintenance in a timely manner. Through this proactive maintenance mode, not only equipment downtime is reduced, but also maintenance costs are reduced.

[0169] In addition, the system has good scalability and is suitable for a variety of scenarios such as residential, commercial buildings and smart communities. It can also be seamlessly connected with property management and energy management platforms to form an efficient building operation and maintenance ecosystem. Overall, the BIM-based IoT whole-house smart system integrates the data of virtual buildings and physical equipment, realizes intelligent control, energy consumption optimization and efficient operation and maintenance, provides an innovative path for the digital transformation of the construction field, and promotes the development of smart buildings and smart cities.

[0170] The BIM-based whole-house intelligent control system solution given in this example solution can constitute a corresponding software program in specific applications. When the software program is running, it will realize the functions of the above-mentioned BIM-based whole-house intelligent control system and be stored in the corresponding storage medium for the processor to call and execute.

[0171] Based on the above-mentioned BIM-based whole-house intelligent control system solution, an embodiment of the present invention further provides a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, the functions of the above-mentioned BIM-based whole-house intelligent control system are realized.

[0172] An embodiment of the present invention further provides a processor, which is used to run a program, wherein the program realizes the functions of the above-mentioned BIM-based whole-house intelligent control system when running.

[0173] An embodiment of the present invention also provides a terminal device, which includes a processor, a memory, and a program stored in the memory and executable on the processor, wherein the program code is loaded and executed by the processor to implement the functions of the above-mentioned BIM-based whole-house intelligent control system.

[0174] The present invention also provides a computer program product, which, when executed on a data processing device, realizes the functions of the above-mentioned BIM-based whole-house intelligent control system.

[0175] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0176] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0177] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0178] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0179] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0180] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0181] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0182] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0183] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0184] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0185] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0186] The above-mentioned method of the present invention, or a specific system unit, or a part of the same, is a pure software architecture, which can be arranged on a physical medium, such as a hard disk, an optical disk, or any electronic device (such as a smart phone, a computer-readable storage medium) through program code. When the machine loads the program code and executes it (such as a smart phone loading and executing it), the machine becomes a device for implementing the present invention. The above-mentioned method and device of the present invention can also be transmitted in the form of program code through some transmission media, such as cables, optical fibers, or any transmission mode. When the program code is received, loaded and executed by a machine (such as a smart phone), the machine becomes a device for implementing the present invention.

[0187] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. The whole house intelligent control system based on BIM is characterized by: include: BIM model data integration unit, IoT access unit, control and management unit, energy consumption analysis and optimization unit, and user interaction and platform integration unit; The IoT access unit is configured to enable unified access and management of IoT devices of multiple types and protocols, receive data of IoT devices of multiple types, and perform data analysis and standard processing on the data received from IoT devices; The BIM model data integration unit associates the IoT device status with the building structure and pipeline distribution based on a virtual-real combination mode, and provides space and geometric data to the energy consumption analysis and optimization unit to support the construction and optimization analysis of the overall energy consumption model of the building; The energy consumption analysis and optimization unit combines the IoT device operation data and BIM information, generates an energy consumption management strategy through energy consumption modeling, prediction and optimization algorithms, and transmits it to the control and management unit for execution; the control and management unit dynamically regulates the IoT device through the IoT access unit according to the optimization strategy, and feeds back the execution results through user interaction and the platform integration unit.

2. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The BIM model data integration unit is configured to obtain the detailed spatial layout, pipeline arrangement and attribute information of the building components by importing standardized BIM model data, and bind the installation location and device parameters of the Internet of Things device with the spatial data in the BIM model to achieve a one-to-one correspondence between the building and the equipment.

3. The BIM-based whole-house intelligent control system according to claim 1 is characterized in that: The BIM model data integration unit is configured to be able to perform logical relationship definition and scene linkage between devices through the BIM model.

4. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The Internet of Things access unit is configured with an edge computing module, which can execute corresponding control logic in local calculation.

5. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The Internet of Things access unit is configured with a dynamic device identification and adaptive access module, which can quickly identify and access Internet of Things devices of different brands and types through device registration and data frame automatic parsing mechanism.

6. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The control and management unit is provided with a scene automation operation module, which is based on rule engine technology and realizes flexible configuration and real-time adjustment of scene automation operation through predefined rules and dynamic scene logic generation function.

7. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The control and management unit is configured with an event-driven and priority scheduling algorithm module. The event-driven and priority scheduling algorithm module is based on a distributed control architecture and is provided with an efficient task distribution and execution mechanism. Through the event-driven and priority scheduling algorithm, concurrent control and resource optimization configuration of multiple devices are performed.

8. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The energy consumption analysis and optimization unit obtains real-time energy usage data by interacting and collaborating with the Internet of Things access unit data, and monitors and analyzes energy consumption in combination with the building structure and equipment layout information provided by the BIM model data integration unit. It can also generate corresponding optimization strategies based on the analysis results and feed them back to the control and management unit to execute dynamic energy efficiency adjustment.

9. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The multi-source data fusion module in the energy consumption analysis and optimization unit can dynamically associate the real-time energy consumption data collected by the Internet of Things access unit with the building geometry, spatial distribution and equipment attribute data in the BIM model, and map the real-time data of the Internet of Things equipment to the specific space or component of the BIM model through standardized data interfaces and semantic models, thereby realizing dynamic association and scenario-based expression of energy consumption information.

10. The whole-house intelligent control system based on BIM according to claim 1 is characterized in that: The user interaction and platform integration unit is configured with a multi-terminal interaction module and / or a cross-platform integration and open interface.

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