Intelligent property management system based on multi-technology fusion

Abstract

The invention is suitable for the technical field of intelligent property management, and provides an intelligent property management system based on multi-technology fusion, which comprises an infrastructure module, a user access module, a data fusion module, a data support module, an intelligent property module and an intelligent decision module. The infrastructure module collects data through equipment such as a sensor and performs edge calculation preprocessing; the user access module provides a multi-port entrance and adopts unified identity authentication and authorization; the data fusion module integrates multi-source heterogeneous data and constructs a user portrait; the data support module realizes distributed data storage and standardized management; the intelligent property management module integrates multiple management functions and realizes automation of a business process; and the intelligent decision-making module performs fault prediction, demand analysis and the like by using data analysis and machine learning. According to the invention, information islands are broken, the equipment monitoring capability and the service individuation level are improved, data sharing and business collaboration are realized, the management efficiency is improved, the cost is reduced, and intelligent decision support is provided for property management.

Description

Technical Field

[0001] The present invention belongs to the field of smart property management technology, and in particular relates to a smart property management system based on multi-technology integration. Background Art

[0002] With the acceleration of urbanization and the improvement of people's living standards, the importance of property management has become increasingly prominent. Currently, smart property management technology has received widespread attention and development. Some property management companies use information systems for basic business management, such as fee management and repair management. Some high-end properties have also introduced professional equipment monitoring systems and intelligent security equipment to improve management efficiency and service quality.

[0003] However, existing technologies still have numerous shortcomings. For one thing, low system integration makes data sharing difficult, creating information silos and leading to inefficient management. For example, data between different functional modules cannot be interoperable, hindering comprehensive decision-making. Furthermore, the intelligent control and monitoring capabilities of front-end equipment are limited, making it difficult to fully and realistically understand the operating status of equipment, and resulting in delayed warnings of equipment failures. Furthermore, services lack personalization, failing to accurately meet the diverse needs of owners. Furthermore, the human and material resources required are substantial, resulting in high costs. These issues urgently need to be addressed. Summary of the Invention

[0004] The purpose of the present invention is to provide a smart property management system based on multi-technology integration, aiming to solve the technical problems existing in the existing technology identified in the background technology.

[0005] The present invention is implemented as follows: a smart property management system based on multi-technology integration includes a user access module, a data fusion module, a data support module, a smart property module, an intelligent decision-making module and an infrastructure module. Each module works in coordination through a standardized interface and data sharing mechanism.

[0006] Infrastructure: This module uses sensors (temperature, humidity, vibration, and current sensors), RFID / NFC readers, and other sensing hardware to collect IoT data such as equipment operating status and personnel access in real time using wired (RS485, Ethernet) or wireless (Wi-Fi, LoRa) communication technologies. Edge computing nodes are deployed to locally pre-process the collected data (such as filtering abnormal data and determining real-time thresholds) and execute preliminary decisions (such as local alarms for equipment anomalies), reducing cloud computing pressure and data transmission latency.

[0007] User access module: provides multi-terminal entrances such as computers, mobile apps, WeChat official accounts, and WeChat mini-programs. It uses the OAuth2.0 protocol to implement third-party login authorization. Through unified identity authentication and role-based authority management (owners, property management personnel, and merchants), customized interactive functions (such as convenient repair reporting on the owner side, work order processing on the property management side, and product management on the merchant side) are designed to meet the operational needs of different users in different scenarios.

[0008] Data Fusion Module: This module extracts, transforms, and loads heterogeneous data from multiple sources (user data, asset data, IoT data, and business data) using ETL tools. Data mapping technology is used to unify data formats (e.g., standardized conversion of different device protocols). User identification and association algorithms are used to integrate dispersed user information, creating a unified user profile that includes information such as owner reporting preferences and consumption records. Furthermore, a standard API is provided to enable data interaction and functional integration with third-party systems (e.g., fire protection and parking management systems), completely breaking down information silos.

[0009] Data support module: Establish a distributed data storage system that supports high-concurrency reading and writing and massive structured / semi-structured data storage (such as equipment operating parameters and work order processing records). Use data warehouse technology to integrate and manage all data, define data structure and source through metadata management, and standardize field names and relationships through a data dictionary to ensure data consistency and traceability.

[0010] Smart Property Management Module: Integrates multi-dimensional management functions and automates business processes through workflow engines and task scheduling algorithms:

[0011] Property Operation Unit: Supports customized configuration of business processes such as owner check-in and renovation application (such as node approvers and flow rules), and publishes real-time property announcements and community event notifications through message push technology to enhance owner participation.

[0012] The Super Work Order Unit utilizes a task scheduling algorithm with priority queuing and load balancing, combined with real-time equipment status data (such as fault warnings) from the equipment monitoring unit. This automatically assigns incident and repair work orders to the most appropriate maintenance personnel, achieving a closed-loop management process of "fault discovery - work order generation - task assignment - progress tracking." Work order processing results are synchronized with the billing management unit, automatically generating service fee invoices to avoid manual verification errors.

[0013] Equipment monitoring unit: This unit collects operating parameters of smart water and electricity meters, access control systems, parking barriers, and other equipment in real time through the MQTT protocol. It uses condition monitoring algorithms such as vibration analysis and temperature trend analysis to determine the health status of the equipment, enabling real-time fault warnings and remaining life prediction. It also optimizes inspection plans based on the analysis results (e.g., increasing the inspection frequency of equipment with high failure rates).

[0014] AI Vision Unit: Utilizes computer vision technology to conduct real-time analysis of surveillance videos, accurately identifying abnormal behaviors such as human intrusion and items left behind, automatically generates alarm work orders and pushes them to security personnel, enhancing proactive security precautions.

[0015] Intelligent decision-making module: Through data cleaning tools, cluster analysis tools, text analysis tools, etc., it conducts in-depth mining of equipment operation history data and owner report text data:

[0016] Model historical trends of equipment data to predict the probability of failure in advance, turning post-fault repairs into pre-fault maintenance.

[0017] Extract keywords and classify issues from owner-reported incidents to identify high-frequency service needs (such as elevator failures and water and electricity repairs) and optimize resource allocation;

[0018] Through chart libraries such as ECharts and Highcharts, the analysis results are presented in visual forms such as bar charts and heat maps, providing management with intuitive decision-making basis (such as comparison of equipment failure rates in various communities and distribution of owner satisfaction).

[0019] The beneficial effects of the present invention are:

[0020] Integrated architecture: This breaks the isolation of traditional property management business systems and integrates core functional modules such as property operations, billing management, and equipment monitoring into a unified platform. Through unified user management, data fusion, and open interface technologies, real-time data sharing and seamless business collaboration between modules are achieved. For example, the work order information generated by the incident reporting and repair module can be automatically linked to the equipment monitoring module to obtain equipment status data. At the same time, the billing management module can accurately bill based on the work order service content, changing the inefficient model of existing technology where data is not circulated between systems and business operations require manual coordination.

[0021] Intelligent Decision Support: Leveraging advanced data analytics and AI technologies, we provide intelligent decision-making support for property management. The data center platform conducts in-depth mining and analysis of massive amounts of user data, business data, and IoT data, generating visual reports and decision-making recommendations. For example, by analyzing historical trends and real-time status of equipment operating data, AI algorithms can be used to predict equipment failures in advance. Compared to existing technologies that only require post-repair or regular inspections, this significantly reduces equipment failure rates and repair costs. Furthermore, we analyze data such as owner consumption behavior and reporting preferences to provide precise strategic guidance for community operations and service optimization.

[0022] Convenient multi-terminal interaction: Provides multi-terminal user access methods such as computer, mobile APP, WeChat public account, WeChat mini-program, etc. to meet the usage needs of different users in different scenarios. Each terminal interface is customized according to the user role (owner, property staff, merchant), and the operation is convenient and smooth. Owners can submit incident reports, pay fees, and participate in community activities through the mobile APP anytime and anywhere; property staff use mobile terminals to efficiently receive work orders and perform inspection tasks; merchants manage products and process orders on the computer, etc., which greatly improves user experience and work efficiency, and solves the problems of single user interaction channels and inconvenient operation in existing technologies.

[0023] Comprehensive Equipment Monitoring and Management: Utilizing advanced IoT sensing technology and equipment monitoring systems, comprehensive, real-time monitoring of property facilities and equipment is achieved. This not only monitors equipment operating status and provides fault warnings, but also optimizes equipment performance and predicts lifespan through AI analysis. For example, smart water and electricity meters collect energy consumption data in real time, analyzing data to identify abnormal energy consumption and providing timely warnings. Access control systems, parking barriers, and other equipment are connected to the platform in real time, providing immediate alarms and recording of abnormal openings. This significantly improves the intelligence and sophistication of equipment management, surpassing the limitations of existing equipment monitoring technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is an architecture diagram of a smart property management system based on multi-technology integration provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0026] like Figure 1 As shown in the figure, the smart property management system based on the integration of multiple technologies adopts a layered architecture design, supports the combination of cloud deployment and local deployment, and is suitable for multiple property scenarios such as residential, commercial, and office buildings.

[0027] 1. Infrastructure Module: Data Collection and Edge Computing

[0028] Device perception hardware: includes sensors, RFID / NFC, readers / recorders, locators, smart tags, etc., which collect data such as device status, personnel location, and item information, and provide raw perception data for the platform.

[0029] Intelligent hardware deployment: This includes smart water and electricity meters, access control, parking barriers, elevator controls, and other intelligent hardware, enabling intelligent control and management of property facilities, improving property automation and security. Through data sharing and exchange mechanisms, data flow and collaboration are achieved across all levels.

[0030] 1. Hardware deployment:

[0031] Device sensing hardware is installed in the community: vibration sensors and temperature sensors are deployed in elevators to monitor the elevator operation status in real time; smart water and electricity meters (supporting MQTT protocol) are installed in water and electricity wells to collect energy consumption data; high-definition cameras (with built-in AI chips) and RFID readers are deployed in public areas (for recording people entering and leaving).

[0032] Deploy edge computing nodes (such as industrial-grade gateways) on the device side to perform local pre-processing of elevator sensor data: calculate the vibration frequency and temperature thresholds in real time. When the vibration is abnormal (over 50Hz) or the temperature exceeds 60°C, the edge node immediately generates a local warning and encrypts key data (timestamps, abnormal parameters) and uploads it to the cloud. Non-abnormal data is only synchronized periodically (once every 10 minutes) to reduce cloud traffic pressure.

[0033] 2. Communication network:

[0034] Sensor data is transmitted to edge nodes via the LoRa wireless protocol, and the edge nodes are connected to the cloud via 4G / Ethernet. The owner's app accesses the platform via Wi-Fi / 4G to ensure the stability and security of data transmission.

[0035] 2. User Access Module: Multi-Terminal Interaction Implementation

[0036] 1. Terminal development:

[0037] It provides multiple access methods such as computer, mobile APP, WeChat public account, WeChat mini-program, etc., which makes it convenient for owners and property staff to access the platform and meet the needs of different usage habits and scenarios.

[0038] Owner side: Develop iOS / Android mobile APP and WeChat mini-program to provide functions such as reporting incidents and repairs, paying fees, and registering for community activities. The interface is customized according to the owner's role.

[0039] Property management: The PC management backend supports work order processing, inspection plan formulation, and report export; the mobile terminal (employee APP) receives work order push in real time, and maintenance personnel can use the APP to scan the equipment QR code to view historical maintenance records, take photos and upload maintenance results, and submit them to the owner for evaluation.

[0040] 2. Identity Authentication:

[0041] The OAuth2.0 protocol is used to connect to WeChat and Alipay third-party logins. Owners bind their room number information when logging in for the first time, and property staff log in with their work number + password. The system automatically assigns role permissions.

[0042] 3. Data Fusion Module: Multi-Source Data Integration

[0043] Unified user: Integrate user information from different sources, build a unified user identity, implement single sign-on, and improve user management efficiency and security.

[0044] Data fusion: Clean, convert, and associate multi-source heterogeneous data to eliminate data silos and achieve data interoperability and sharing.

[0045] Process / form engine: supports customized business processes and form design, flexible configuration of various property business processes, and rapid generation of personalized forms.

[0046] Resource management: Effectively manage and allocate various platform resources such as hardware equipment, software authorization, storage space, etc.

[0047] System monitoring: Real-time monitoring of the platform's operating status, including server performance, network conditions, application operation status, etc., to ensure stable system operation.

[0048] AI capabilities: Integrate artificial intelligence algorithms and models to provide the platform with AI services such as image recognition, intelligent analysis, prediction and early warning.

[0049] Open interface: Provides standard API interface to achieve data interaction and functional docking with third-party systems, and expand platform application scenarios and capabilities.

[0050] 1. Data extraction and conversion:

[0051] Use ETL tools to regularly extract data from third-party systems: extract smoke alarm records from the fire protection system, extract parking space usage data from the parking system, and convert them into a unified JSON format (such as device ID, timestamp, status code).

[0052] The text data of owner reports (such as "abnormal noise in the elevator of Building 3") is analyzed through the natural language processing (NLP) algorithm, and keywords ("Building 3", "elevator", "abnormal noise") are extracted and associated with the elevator number of the equipment monitoring module.

[0053] 2. User portrait construction:

[0054] Integrate owners' reporting records, consumption records, and activity participation data to build personalized labels ("high-frequency equipment repair users", "active community activity users") to provide a basis for subsequent service recommendations.

[0055] 4. Data Support Module: Multi-source Data Storage and Standardized Management

[0056] The data support module serves as the data center of the system and is responsible for the storage, integration, and standardized management of massive structured / semi-structured data.

[0057] It aggregates user data, asset data, IoT data, business data, etc., providing a data foundation for each functional module of the platform to ensure normal business operation and analytical decision-making.

[0058] 5. Smart Property Module: Business Process Automation

[0059] Property Operations: This service covers business processing, property announcements, community activities, and online butler services. It supports owners in handling various property matters online and receiving timely property announcements. It organizes a variety of community activities to enhance owner interaction and community cohesion. Online butlers provide real-time consultation and services to enhance the owner experience.

[0060] Super Work Order: This includes functions such as incident reporting, repair reporting, quality management, patrol management, and facility and equipment management. Incident reporting and repair reporting enable rapid response and processing, quality management ensures service compliance, patrol management ensures property safety, and facility and equipment management tracks and maintains equipment throughout its lifecycle.

[0061] Billing Management: Features include a billing center, discounts, a payment collection platform, and report statistics. Accurately calculate various expenses and generate bills, supporting diverse discount settings. It also provides convenient payment channels and generates financial reports to facilitate financial management.

[0062] AI Vision: Features include Vision Home, Smart Inspection, Report Analysis, and AI Settings. Leverages AI technology to intelligently monitor and inspect property areas, analyze monitoring data, and generate reports. Flexible AI-related parameters can be set.

[0063] Equipment Monitoring: This platform enables remote facility and equipment monitoring, alarms / early warnings, AI-powered data analysis, and online management. This platform provides real-time visibility into equipment operating status, issues timely alarms and early warnings for abnormalities, predicts faults through AI-powered analysis of equipment data, and supports online equipment management.

[0064] 1. Property Operation Unit: Business Process Customization and Intelligent Access

[0065] Automated process configuration: Using a low-code workflow engine, property management personnel can drag and drop to configure business processes through a visual interface. Take the owner's renovation application process as an example:

[0066] The owner submits the decoration application on the APP and uploads the decoration drawings and construction personnel information.

[0067] A timeout warning is set for each node (for example, if the project review is overdue, the supervisor will be automatically reminded to intervene), and the process processing efficiency is improved by 60% compared with traditional paper approval.

[0068] Smart message push: Send targeted notifications to owners through the push interface:

[0069] Payment notice: A property fee bill will be automatically generated on the 5th of each month, with a WeChat payment link attached;

[0070] Event notifications: Push customized event invitations based on owner profiles to increase click-through rates.

[0071] 2. Super work order unit:

[0072] Work order generation: When the equipment monitoring unit detects abnormal elevator vibration (edge ​​node warning), it automatically triggers the super work order unit to generate a maintenance work order. The work order title is preset as "Abnormal elevator vibration in Unit 1, Building 3", and the attachments include real-time vibration waveforms and temperature data.

[0073] Intelligent allocation: The task scheduling algorithm prioritizes tasks assigned to maintenance personnel with elevator maintenance qualifications and low current load, and pushes work order details (location, fault type, and urgency level) through the app.

[0074] Closed-loop management: After arriving at the scene, maintenance worker A scans the elevator QR code through the app to confirm his check-in. After the maintenance is completed, he uploads photos of the replaced parts. The owner rates the service on the app, and the rating data is synchronized to the data support module for service quality analysis.

[0075] 3. Billing management unit:

[0076] For maintenance work orders, the billing rule configuration engine automatically matches charging items, generates the bill, and pushes it to the owner via WeChat template messages, supporting online payment and historical bill inquiries.

[0077] 4. AI Vision Unit: Real-time video intelligent analysis and alarm

[0078] Abnormal behavior recognition engine: Based on computer vision algorithms (YOLOv8 target detection + LSTM behavior analysis), it processes surveillance videos in real time:

[0079] Area intrusion detection: Set up electronic fences in prohibited areas of the community, and generate alarm work orders when abnormal behavior is detected entering;

[0080] Left-behind item detection: Identify items such as luggage and parcels that have been stationary for an extended period of time, automatically mark them, and notify security personnel to conduct an inspection.

[0081] Automation of alarm work orders: When an anomaly is detected, the system automatically captures the video clip as an attachment and pushes it to different positions based on the alarm level.

[0082] 5. Equipment monitoring unit: intelligent management of the entire life cycle

[0083] Multi-protocol data collection: Connect smart water and electricity meters, elevator controllers, and access control systems through the MQTT protocol to achieve real-time collection of equipment operating parameters.

[0084] Fault prediction and maintenance strategy: Building a digital twin model based on historical equipment data:

[0085] When a significant difference is detected between the monitored equipment and the historical operating parameter average, a preventive maintenance work order is automatically generated.

[0086] Inspection plan optimization: Dynamically adjust inspection frequency based on equipment health status.

[0087] 6. Intelligent Decision-Making Module: Data-Driven Optimization

[0088] 1. Equipment failure prediction:

[0089] Vibration data and maintenance records of elevators over the past year are collected, and a fault prediction model is trained using a machine learning algorithm. For example, when the vibration frequency is set to >40Hz and the temperature is >55°C, the predicted fault probability exceeds 70%. An inspection work order is generated 48 hours in advance, prompting the property management to prepare spare parts in advance.

[0090] 2. Owner demand analysis:

[0091] Conduct cluster analysis on community activity registration data and adjust activity plans accordingly.

[0092] Data processing and interaction process:

[0093] Data Collection: Device sensing hardware and intelligent hardware collect real-time data on device operating status, energy consumption, personnel access, and owner operations, and transmits it to the data support layer via network communications for storage. Simultaneously, data on user operations performed on each terminal (such as incident and repair report submissions and fee payments) is also recorded and stored.

[0094] Data Fusion and Analysis: The data fusion layer cleans, converts, and fuses collected multi-source data to form a unified data view. The data analysis module conducts in-depth mining of the fused data, applying statistical analysis, machine learning, deep learning, and other algorithms to extract valuable information and knowledge. For example, cluster analysis of equipment operation data identifies groups of equipment with similar operating modes and compares and analyzes fault differences. Text analysis of owner report data extracts high-frequency problem keywords to provide guidance for service improvements.

[0095] Business collaboration and decision support: The functional modules of the smart property management layer collaborate and make decisions based on data analysis results. For example, if the equipment monitoring module detects an equipment failure warning, it will automatically trigger the super work order module to generate and assign a repair work order. The billing management module generates expense invoices based on the service records and billing rules provided by the business module. The decision support layer provides management with visual reports and decision-making recommendations based on data analysis results, assisting in the formulation of property management strategies.

[0096] User interaction feedback: Users access the platform through various terminals to conduct business operations and information inquiries. The platform provides real-time feedback based on user operations. At the same time, user evaluations and suggestions on services are collected and fed back to the data analysis module to further optimize services and management strategies.

[0097] Business process description:

[0098] Service initiation: Owners initiate service requests on the owner side, such as reporting an incident, paying bills, or making purchases. These requests are transmitted via the network to the property management platform. Upon receiving the request, the platform parses and categorizes it, and assigns the task to the appropriate property management personnel or business system based on pre-set rules and business logic.

[0099] Task allocation and processing stage: Taking incident and repair requests as an example, the platform automatically assigns work orders to the most suitable maintenance personnel's work terminal (employee app or PC) based on factors such as the type of report, urgency, and the maintenance personnel's work status and skill level. After receiving the work order, the maintenance personnel will go to the site to handle it according to the work order information. During the processing, the maintenance personnel can use the app to record the maintenance progress, equipment detection data and other information in real time and upload it to the platform. For payment requests, the platform transmits them to the billing management system for processing. The billing management system calculates the fees according to the preset charging rules and generates invoices, providing a variety of payment methods for owners to choose from.

[0100] During the business execution phase, property management personnel carry out tasks as required, such as maintenance personnel repairing equipment and merchants processing orders and shipping them. During this process, relevant data is transmitted back to the platform in real time, which monitors and manages this data to ensure the progress and quality of business processing. For example, during equipment maintenance, the platform can track the progress in real time. If any delays are detected, maintenance personnel and relevant management personnel will be promptly notified so that appropriate measures can be taken.

[0101] Data Feedback and Analysis Phase: After the service is completed, the owner evaluates the service. This evaluation data, along with various other data generated during the service process, is aggregated into the platform's data storage and processing center. The platform utilizes data analytics to conduct in-depth analysis of this data, assess service quality, and identify business issues. For example, by analyzing incident and repair report data, the frequency and processing time of incidents in different regions and types of reports are analyzed to identify high-frequency problem areas and types, providing a basis for optimizing resource allocation. By analyzing owner consumption data, we can understand their consumption habits and preferences, providing a reference for product recommendations and marketing strategy development for community e-commerce services.

[0102] Decision Support and Optimization Phase: Management develops management strategies and service optimization plans based on data analysis results. For example, based on equipment failure rate and repair cost data, equipment maintenance plans are adjusted, with inspections of high-failure equipment increased and vulnerable parts replaced in advance to reduce repair costs. Based on customer consumption data and feedback, the product assortment and inventory management of community e-commerce services are optimized to improve sales efficiency and customer satisfaction. Furthermore, through analysis of various business data, the effectiveness of property management strategies is evaluated, allowing for timely adjustments and optimization to achieve continuous improvement in property management.

[0103] Example 1: Device Management and Fault Response Optimization

[0104] 1. Scenario:

[0105] At 14:00 on August 15, 2024, the edge computing node of the fire water pump in Unit 2, Building 3 detected that the current fluctuation exceeded ±15% (preset threshold) and immediately uploaded the abnormal data to the cloud.

[0106] 2. System processing flow:

[0107] The equipment monitoring unit analyzes the data and determines it to be a potential fault of "water pump motor bearing wear" (historical similar data matching rate is 85%), and automatically generates a yellow warning work order.

[0108] The super work order unit is assigned to maintenance worker B (currently processing 2 work orders, load 70%) based on the maintenance worker's skill tags ("water and electricity maintenance" and "senior technician").

[0109] Maintenance worker B checked the fault history on the app (the water pump had been repaired at the same location six months ago), took a spare bearing to the site, and completed the replacement within 30 minutes, avoiding the fire hazard caused by the water pump shutdown at night.

[0110] 3. Effect:

[0111] Compared with traditional manual inspections (once a day), faults are discovered 6 hours earlier, maintenance time is shortened by 40%, and equipment downtime is reduced by 80%.

[0112] Example 2: Owner repair reporting and service closed loop

[0113] 1. Scenario:

[0114] Owner A submitted a repair report through the WeChat mini-program: "The corridor lights in Unit 3, Building 2 are not on", with attached on-site photos (taken at 9:00 on September 10, 2024).

[0115] 2. System processing flow:

[0116] The super work order unit identifies it as "public lighting failure", and the urgency level is automatically marked as "medium", and assigned to maintenance worker C who is responsible for Building 2 (there are currently no pending work orders).

[0117] Maintenance worker C arrived at the scene at 9:15 and found that the light bulb was burned out. After replacing it, he took a photo and uploaded the repair results. The system automatically recorded the work order processing time as 25 minutes.

[0118] Owner A receives a repair completion notification on the mini program and rates the service. The rating data enters the data support module and is used for the monthly maintenance team assessment (average rating 9.2 points).

[0119] 3. Effect:

[0120] The average time for processing repair reports has been shortened from the traditional 2 hours to 40 minutes. Owners can track the progress in real time, and satisfaction has increased to 92%.

[0121] Example 3: Intelligent Security Monitoring and Incident Prevention

[0122] 1. Scenario: At 23:00 on October 5, 2024, the AI ​​Vision Unit analyzes the surveillance video at the community entrance and detects a suspicious person (who continues to wander around and is identified as a non-owner) wandering near the unit door for more than 10 minutes (behavior recognition algorithm threshold).

[0123] 2. System processing flow:

[0124] The AI ​​vision unit automatically captures video clips, generates a red alarm ticket, and pushes it to the security personnel's mobile app (with real-time location and screenshots).

[0125] Security personnel arrived at the scene within 5 minutes, confirmed that the person was a courier looking for lost items, and guided him to register and leave, avoiding potential safety risks.

[0126] 3. Effect:

[0127] The accuracy rate of abnormal behavior identification reached 95%, the security response time was shortened from 15 minutes to 8 minutes, and there were zero thefts in the community in 2024.

[0128] Implementation effect:

[0129] 1. Equipment Management and Response: Property management companies deploy this smart property management platform within their management area. By connecting to various device sensing hardware, such as sensors and smart water and electricity meters, the platform collects real-time equipment operating data. This data is processed by the data fusion layer and visualized in real time in the equipment monitoring module. Compared to traditional methods that rely on manual inspections to detect faults, this significantly reduces fault response time and improves management efficiency, effectively preventing inconvenience caused to property owners by equipment failures.

[0130] Optimized repair service: Homeowners can conveniently submit repair requests online through the platform's mobile app, WeChat mini-program, and other portals. Upon receiving the repair request, the platform's Super Work Order module automatically assigns the work order to the most appropriate repair personnel based on pre-set criteria, such as fault type and urgency. Repair personnel receive and process the work order in real time on their mobile device, while homeowners can track the repair progress in real time at the terminal where they submitted the request. Statistics show that after implementing this platform, the average repair processing time has been reduced by 50%, significantly increasing homeowner satisfaction with the repair service.

[0131] Intelligent Security Monitoring: Leveraging the platform's AI Vision feature, property management implements 24 / 7 intelligent monitoring of public areas. AI algorithms analyze surveillance video in real time, accurately identifying unusual behavior, such as unusual gatherings of people or items left behind. When a suspicious individual is detected loitering for an extended period in a residential community's public passageway, the system automatically triggers an alarm. Security personnel quickly receive the alert and respond, successfully preventing multiple potential security incidents and ensuring the personal and property safety of community residents.

[0132] Unified Management of Multiple Residential Areas: Through the data fusion layer, user data, business data, and equipment data from multiple residential areas are integrated and processed, enabling unified management of multiple residential areas. In terms of resource allocation, maintenance personnel can be rationally dispatched based on data such as equipment failure frequency and maintenance personnel workload in each residential area, resulting in a more optimized allocation of human resources. In terms of service strategy formulation, differentiated community activities and service plans are developed based on the needs and preferences of owners in different residential areas, improving overall operational efficiency and data management capabilities, and driving property services towards intelligent and efficient development.

[0133] The system has achieved significant improvements in property management efficiency, cost, service quality and data utilization, effectively solved the problems existing in existing technologies, and has outstanding beneficial effects.

[0134] Improved Management Efficiency: The integrated platform integrates multiple business systems, breaking down information silos and enabling real-time data sharing and business collaboration. For example, in incident management, the automatic work order allocation function accurately assigns reports to the most appropriate maintenance personnel based on preset rules, significantly reducing processing time. According to statistics, shortened work order turnover times, improved customer service staff efficiency, and increased per capita service area have significantly improved management efficiency.

[0135] Reduced operating costs: Intelligent equipment monitoring and management enable early prediction of equipment failures and precise maintenance. The facility equipment management system monitors and analyzes equipment operating data in real time, identifying potential faults and minimizing the high repair costs associated with sudden equipment failures. Furthermore, optimized inspection plans reduce inspection time and staffing, effectively lowering labor costs. Comprehensive calculations reduce maintenance work order processing costs and project costs.

[0136] Improve service quality: Deeply explore owner needs and provide personalized services. The community operations module organizes community activities tailored to owner interests based on owner behavior data and feedback, increasing participation. The community mall provides owners with a convenient shopping experience and a rich variety of products to meet their diverse needs and enhance their satisfaction.

[0137] Enhanced security: The AI ​​video cloud system leverages artificial intelligence technology to provide comprehensive, real-time monitoring of property areas. It automatically identifies unusual behavior, such as intrusions and the accumulation of debris, and sends timely and automatic alerts, improving alert accuracy. It also automatically generates work orders and assigns them to relevant personnel, effectively improving security and protecting the lives and property of property owners.

[0138] Optimizing Data Utilization: The data center platform conducts in-depth analysis of various data types to provide strong support for decision-making. By analyzing equipment operation data, we optimize equipment maintenance plans and improve equipment availability. By analyzing owner consumption data, we optimize community mall product categories and marketing strategies, thereby increasing product sales.

[0139] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0141] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. The intelligent property management system based on multi-technology integration is characterized by: The system comprises: User access module, used to establish multi-terminal entrances, adopts a unified identity authentication and authorization mechanism, and conducts customized interaction design based on user roles; The data fusion module is used to extract, transform, and load multi-source heterogeneous user data, asset data, IoT data, and business data through ETL tools. It also uses data mapping technology to unify data formats, integrates user information from different systems through user identity recognition and association algorithms, builds a unified user profile, and establishes a standard API open interface for data interaction with third-party systems. The data support module is used to establish a distributed data storage system to store multi-source structured and semi-structured data, integrate and manage them using data warehouse technology, and standardize the management of multi-source structured and semi-structured data through metadata management and data dictionary; The smart property module integrates property operations, super work orders, billing management, and equipment monitoring functions, and controls business process automation through a workflow engine and task scheduling algorithm. The intelligent decision-making module uses data analysis tools and machine learning algorithms to clean, model and analyze the structured and semi-structured data stored in the data support module, and convert the analysis results into visual charts.

2. The system according to claim 1, wherein: The user access module provides multi-terminal access mode. The user access module uses the OAuth2.0 protocol to establish third-party login authorization, and each terminal interface is customized to design interactive functions according to the user role.

3. The system according to claim 1, wherein: The data fusion module integrates AI capability units, including image recognition algorithms, natural language processing algorithms, and intelligent recommendation algorithms: The image recognition algorithm is used to identify abnormal behavior in surveillance videos in real time; The natural language processing algorithm is used to extract keywords from the owner's report text data; The intelligent recommendation algorithm is used to generate personalized service recommendations based on the owner's consumption behavior data and reporting preference data.

4. The system according to claim 1, wherein: The multi-source structured and semi-structured data stored in the data support module include: User data: owner identity information, reporting preferences, and consumption records; Asset data: basic equipment attributes, maintenance records, and inspection logs; IoT data: equipment operating parameters, energy consumption data, and surveillance videos; Business data: work order processing records, fee payment records, and community activity participation data; Define the structure, attributes and sources of structured and semi-structured data through metadata management, and standardize field names, formats and relationships through data dictionaries.

5. The system according to claim 1, wherein: The smart property module includes: The property operation unit is used to customize business processes based on the workflow engine and publish announcements and event notifications through message push technology; The device monitoring unit is used to collect the operating parameters of IoT devices through the MQTT protocol, apply the status monitoring algorithm to determine the health status of the device, and perform fault warning and life prediction; The super work order unit is used to automatically distribute business-related work order data based on work order type, urgency, and personnel skills, using a task scheduling algorithm with priority queuing and load balancing, combined with the output of the equipment monitoring unit; The billing management unit is used to perform multi-dimensional billing through the billing rule configuration engine and calculate discounts in combination with the discount policy engine; The AI ​​vision unit uses computer vision technology to perform real-time analysis on surveillance video data collected by IoT devices, identify abnormal behavior, and generate alarm work orders.

6. The system according to claim 1, wherein: The data analysis tools described in the intelligent decision-making module include data cleaning tools, cluster analysis tools, and text analysis tools; The intelligent decision-making module functions include: Model historical trends of equipment operation data and predict equipment failures; Classify problems and identify high-frequency problems based on owner-reported data; Optimize the configuration of service resources; The analysis results of the intelligent decision-making module are visualized through a chart library.

7. The system according to claim 1, wherein: It also includes an infrastructure module for collecting equipment status and personnel entry and exit data through wired and wireless communications, and performing local pre-processing through edge computing nodes to reduce the cloud computing load.

8. The system according to claim 1, wherein: The data fusion module also includes a system monitoring submodule for real-time monitoring of platform operating indicators and setting a threshold alarm mechanism.

9. The system according to claim 5, characterized in that The super work order unit communicates data with the equipment monitoring unit and the billing management unit: When the equipment monitoring unit detects a fault, it automatically triggers the super work order unit to generate a maintenance work order; The processing results of the super work order unit are synchronized to the billing management unit to generate a service fee bill.

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