System and Method for Replacement Compatibility Determination and Construction Linkage Based on Lighting Fixture Life Prediction Events

Abstract

The present invention relates to a system for determining replacement compatibility and linking construction based on lighting fixture lifespan prediction events. It acquires status data from a lighting fixture or a power supply unit (SMPS), including input voltage, output current, internal temperature, accumulated lighting time, number of on / off cycles, dimming control history, output ripple waveform, and protection circuit operation history. By analyzing this data, it can generate lifespan prediction events that include reaching a remaining lifespan threshold, entering safe foldback, accumulated overheating, and imminent blackout. Information on the installation environment of the lighting fixture where the lifespan prediction event occurred is automatically collected through NFC / RFID tag scanning, vision AI-based image analysis, and BIM database linkage. By combining this information, a replacement requirement profile can be generated that structures the technical requirements necessary for replacement. By comparing information on multiple candidate lighting fixtures and the replacement requirement profile to determine electrical, mechanical, control, and optical compatibility, unsuitable candidates can be excluded and suitable candidates selected. Furthermore, for the suitable candidates, construction feasibility information, including the expected construction scope and schedule, can be calculated and provided to a user terminal. According to the present invention, preemptive replacement of lighting fixtures is possible before failure occurs, non-conformity issues after installation can be prevented in advance through multidimensional compatibility verification, user convenience is improved through automatic collection of environmental information, and the entire replacement process can be managed in an integrated manner through construction-linked automation.

Description

Technology Field

[0001] The present invention relates to a predictive maintenance and replacement management system for lighting fixtures, and more specifically, to a lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system and method that analyzes status data collected from a lighting fixture or a power supply unit (SMPS) to generate lifespan prediction events, automatically collects installation environment information, determines electrical, mechanical, control, and optical compatibility in multiple dimensions to select suitable replacement candidates, and simultaneously calculates and provides information on feasibility of construction.

[0003] More specifically, the present invention relates to an integrated solution that actively responds to the imminent failure of a lighting fixture and automates the entire replacement process by collecting multidimensional electrical parameters of an SMPS in real time, such as input voltage, output current, internal temperature, cumulative lighting time, number of on / off cycles, dimming control history, output ripple waveform, and protection circuit operation history, and generating lifespan prediction events preemptively before failure occurs through machine learning-based time series analysis; automatically collecting installation environment information in a multimodal manner, such as NFC / RFID tag scanning, vision AI-based image analysis, BIM (Building Information Modeling) database integration, and home network system API integration; generating a replacement requirement profile based on the collected information; determining electrical, mechanical, and control compatibility with multiple replacement candidate lighting fixtures stored in a database; and simultaneously verifying optical compatibility through BIM data-based illuminance simulation to exclude unsuitable candidates and select suitable candidates; and calculating and providing construction feasibility information, including the estimated construction scope, construction time, whether additional materials are required, and available visit schedules, for the selected suitable candidates to a user terminal. Background Technology

[0004] In modern buildings, lighting systems are essential facilities that ensure the safety and convenience of occupants; in particular, in commercial buildings, public facilities, and smart home environments, the stable operation of lighting is directly linked to service continuity. Although advancements in LED lighting technology have significantly extended the lifespan of lighting fixtures, performance still degrades over time and eventually leads to failure due to factors such as the degradation of SMPS (Switching Mode Power Supply), reduced luminous flux of LED elements, and the accumulation of stress from repetitive on / off cycles.

[0006] Conventional lighting management methods mostly rely on reactive approaches that respond only after a failure occurs, or on periodic replacement methods that replace fixtures in bulk after a certain period. For example, Korean Patent Publication No. 10-2019-0092016 provides a function to collect environmental information such as temperature, humidity, and fine dust using sensors, but it has limitations in that it is limited to simple monitoring and fails to utilize the collected data for predicting the lifespan of lighting fixtures. Furthermore, Korean Patent Publication No. 10-2021-0065452 proposes a method for managing the state of a light source through the setting of rated power and voltage conversion functions of LED light sources; however, this method is limited to adjusting the current state and lacks a mechanism to predict future failure times and respond proactively.

[0008] This reactive approach causes inconvenience to users the moment a lighting fixture suddenly breaks down, and there is a risk of operational losses due to service interruption, particularly in commercial facilities or public buildings. Furthermore, during the process of urgently replacing a fault, there are difficulties in situations where re-installation is required because an unsuitable product is selected or compatibility with the installation environment is not sufficiently reviewed.

[0010] Ensuring compatibility is a critical factor when replacing lighting fixtures. While Korean Patent Publications No. 10-2019-0158929 and No. 10-2024-0084900 provide connector structures for compatibility with various modules, they focus primarily on electrical connection compatibility. They have limitations in that they fail to comprehensively verify mechanical compatibility (drilling feasibility based on ceiling opening dimensions and ceiling finishing materials), control compatibility (integration with existing dimming systems and smart homes), and optical compatibility (whether illuminance requirements are met according to spatial characteristics) in actual installation environments. In particular, the difficulty and cost of drilling differ significantly depending on whether the ceiling finishing material is gypsum board or concrete. Conventional technology faces the problem of incurring unexpected additional costs during the construction phase or encountering situations where construction itself becomes impossible because it fails to identify these site conditions in advance.

[0012] In terms of collecting environmental information, conventional technology relies on users manually inputting lighting fixture specifications, installation locations, and ceiling structures, or on experts visiting the site in person to take measurements. While Korean Patent Publications No. 10-2022-0135618 and No. 10-2024-0072980 provide lighting control functions via smartphone apps, they lack a system for automatically collecting detailed information on lighting fixtures and installation environments. This results in a heavy input burden for users and limitations in information accuracy. In particular, information such as opening dimensions or ceiling finishing materials is difficult for general users to accurately measure or identify, raising concerns about potential errors. This leads to the selection of unsuitable products, which in turn increases the failure rate of replacements.

[0014] Furthermore, even if conventional lighting management systems provide product recommendation functions, they are disconnected from the actual construction phase. Consequently, even after users select a product, they face the inconvenience of having to go through complex procedures, such as separately finding a construction company, coordinating site inspection schedules, and negotiating the scope and costs of construction. Korean Patent Publication No. 10-2023-0046711 and No. 10-2019-0003935 include energy consumption measurement and optimization functions, but they have limitations in that they fail to implement an integrated workflow that automatically calculates and provides feasibility information (estimated construction time, whether additional materials are needed, and available visit schedules) at the time when lighting replacement is required. As a result, users must endure a long waiting time ranging from several days to several weeks from the decision to replace to the completion of construction, and they face the problem of inconvenience if a lighting failure occurs during this period.

[0016] Furthermore, existing systems have limitations in adapting to environmental changes, such as the launch of new products, advancements in construction technology, and shifts in user preferences, as they statically maintain judgment logic or databases once established. Due to the absence of a closed-loop learning mechanism that collects actual construction result data to continuously improve the system's prediction accuracy or compatibility judgment algorithms, there is a concern that the system's reliability may deteriorate over time.

[0018] Due to the limitations of these conventional technologies, there is a need for a new technological approach that automates and optimizes the entire lighting replacement process by predicting lighting fixture failures in advance for preemptive response, automatically collecting installation environment information, verifying electrical, mechanical, control, and optical compatibility in a multidimensional manner, and automatically calculating and providing feasibility information.

[0020] Korean Patent Publication No. 10-2018-0107117 (September 7, 2018)

[0021] Korean Patent Publication No. 10-2024-0121551 (September 6, 2024)

[0023] Conventional lighting fixture management methods have relied on reactive approaches, such as responding only after a failure occurs or managing fixtures passively according to regular replacement cycles. This has resulted in inconvenience and safety hazards caused by unexpected lighting malfunctions. Furthermore, replacement procedures have been limited to partial compatibility checks that only consider electrical specifications or physical dimensions. Consequently, issues such as dimming protocol mismatches, unsuitable ceiling structures, and substandard illuminance performance frequently occur after installation, leading to increased re-installation costs and user dissatisfaction.

[0025] Furthermore, collecting the environmental information required for replacement necessitated users to manually measure dimensions or rely on on-site visits by experts, resulting in excessive time and cost; additionally, the possibility of selecting unsuitable products due to measurement errors could not be ruled out. Moreover, even when a suitable replacement product was selected, specific construction information—such as the actual scope of work, required time, and the need for additional materials—was not provided. This led to delays in user decision-making and resulted in reduced service completeness due to the disconnect between product purchase and construction execution. Prior art literature

[0026] Korean Patent Publication No. 10-2018-0107117 (2018.09.07) Korean Patent Publication No. 10-2024-0121551 (2024.09.06) The problem to be solved

[0027] The present invention aims to solve the problems of the conventional technology described above by providing a lighting fixture life prediction event-based replacement compatibility determination and construction linkage system and method that enables predictive maintenance by analyzing multidimensional state data collected from a power supply unit of a lighting fixture to generate life prediction events before failure occurs, eliminates measurement errors through an automatic multimodal environmental information collection system, drastically reduces the replacement failure rate by integrating and determining electrical, mechanical, control, and optical compatibility, and maximizes user convenience by automatically calculating and providing construction linkage information.

[0028] Therefore, the present invention has been devised to solve the aforementioned conventional problems, and the objectives of the present invention are as follows.

[0029] First, it involves generating life prediction events, such as reaching a remaining life threshold, output degradation, or an imminent blackout, by utilizing status data of the lighting fixture or its power supply unit.

[0030] Second, it involves collecting spatial information of the installation environment where the above event occurred and information on existing lighting fixtures to generate a replacement request profile.

[0031] Third, among multiple replacement candidates, unsuitable candidates are eliminated by determining electrical compatibility, mechanical compatibility, control method compatibility, and feasibility of construction.

[0032] Fourth, it provides actual installable replacement candidates and construction linkage information to the user terminal to minimize lighting non-turning time and on-site response delays.

[0033] Fifth, it is to enable the proposal of additional services, such as furniture, partial interiors, and space packages, in conjunction with verified compatible lighting replacement candidates when necessary. means of solving the problem

[0034] A system for determining replacement compatibility and linking construction based on a lighting fixture life prediction event according to one aspect of the present invention for solving the above problem may include: a state data acquisition unit that acquires state data from a lighting fixture or a power supply unit of the lighting fixture; a life prediction event generation unit that analyzes the state data to determine the deterioration state of the lighting fixture and generates a life prediction event; an environment information collection unit that collects installation environment information of the lighting fixture where the life prediction event occurred; a replacement request profile generation unit that generates a replacement request profile structuring technical requirements necessary for replacement by combining the life prediction event and the installation environment information; a compatibility determination unit that excludes unsuitable candidates and selects suitable candidates by determining electrical, mechanical, and control compatibility by comparing a plurality of replacement candidate lighting fixture information stored in a database with the replacement request profile; a construction linkage unit that calculates construction feasibility information including an expected construction scope and schedule for the suitable candidates; and a user terminal provision unit that displays an imminent failure notification based on the life prediction event to a user terminal while simultaneously providing the suitable candidates and the construction feasibility information.

[0036] The above status data may include at least one of input voltage, output current, internal temperature, accumulated lighting time, number of on / off repetitions, dimming control history, output ripple waveform, and protection circuit operation history, and the above life prediction event may include at least one of reaching a remaining life threshold, entering safe foldback, accumulated overheating, and an imminent blackout state.

[0038] The above-mentioned environment information collection unit may include a specification acquisition module that automatically receives a hardware specification profile of an existing light, including the hole dimensions, mounting method, wiring type, and dimming protocol of the lighting fixture, to a server as the user terminal scans a near-field communication tag or identification code attached to the lighting fixture.

[0040] The above environment information collection unit may include a space estimation module that analyzes the lighting fixture and ceiling images acquired through the camera and depth sensor of the user terminal using a vision AI algorithm to estimate the diameter of the opening of the lighting fixture and determine the material of the ceiling finishing material.

[0042] The above-mentioned environmental information collection unit may include a data linkage module that accesses a home network system or an architectural information model database server linked to the lighting fixture to extract parameters of the use, floor area, and ceiling height of the space where the lighting fixture is located.

[0044] The compatibility determination unit can remove the unsuitable candidate by performing a mechanical compatibility logic that determines whether additional drilling and anchor installation are possible by comparing the ceiling finishing material and the opening dimensions of the existing lighting, estimated through vision AI image analysis, with the required drilling dimensions of the replacement candidate lighting fixture, and an illuminance satisfaction determination logic that calculates the target illuminance based on the area, floor height, and space use of the space extracted from the building information model, and simulates whether the luminous flux and light distribution curve of the replacement candidate lighting fixture satisfy the target illuminance.

[0046] The above system may further include an additional service linkage unit that proposes to the user terminal an additional service including at least one of furniture, curtains, indirect lighting, and partial remodeling corresponding to existing furniture or space style information based on a suitable candidate that has passed the compatibility determination unit, and can store actual construction result data after the completion of replacement construction to continuously correct subsequent lifespan prediction or compatibility determination accuracy.

[0048] A method for determining replacement compatibility and linking construction based on a lighting fixture life prediction event according to another aspect of the present invention for solving the above problem may include: a step of acquiring status data from a lighting fixture or a power supply unit of said lighting fixture; a step of analyzing said status data to determine the deterioration state of said lighting fixture and generating a life prediction event; a step of collecting installation environment information of a lighting fixture in which said life prediction event occurred; a step of generating a replacement requirement profile that structures technical requirements necessary for replacement by combining said life prediction event and said installation environment information; a step of excluding unsuitable candidates and selecting suitable candidates by determining electrical, mechanical, and control compatibility by comparing a plurality of replacement candidate lighting fixture information and said replacement requirement profile; a step of calculating construction feasibility information for said suitable candidates; and a step of displaying an imminent failure notification based on said life prediction event to a user terminal while simultaneously providing said suitable candidates and said construction feasibility information.

[0050] The step of collecting the above installation environment information may include a step of estimating the opening dimensions and ceiling finishing material of the existing lighting fixture through image analysis using a camera of a user terminal, and a step of extracting the area and floor height parameters of the space by linking with an architectural information model database; and the step of determining compatibility may verify the compatibility by comparing the estimated ceiling finishing material and opening dimensions with the required drilling dimensions of the replacement candidate lighting fixture to determine whether additional drilling is possible, and determining whether the luminous flux of the replacement candidate lighting fixture satisfies the target illuminance calculated based on the extracted area and floor height parameters.

[0052] The above construction feasibility information may include the estimated construction time, available visit schedule, whether prior site verification is required, whether no drilling or partial drilling is required, whether existing switches and dimming devices can be reused, and whether additional materials are required. The step of providing the above visualizes and provides the construction feasibility information to the user terminal, while simultaneously providing a consultation request or construction reservation interface, so as to automatically link the confirmation of replacement of the suitable candidate and the construction reservation. Effects of the invention

[0053] According to the present invention, by fusionally analyzing multidimensional state data including input voltage, output current, internal temperature, accumulated lighting time, number of on / off cycles, dimming control history, output ripple waveform, and protection circuit operation history from a power supply unit of a lighting fixture, detailed lifespan prediction events such as reaching a remaining lifespan threshold, entering safe foldback, accumulated overheating, and imminent blackout are generated. This provides a significant technical effect of predicting failures in lighting fixtures in advance and preemptively replacing them, compared to conventional post-failure response methods. In particular, due to a mechanism that probabilistically predicts remaining lifespan by learning time-series patterns of multiple electrical parameters using a machine learning model, it is possible to solve technical challenges such as reduced prediction accuracy and false / missing detections that could not be resolved by existing single-indicator-based simple threshold determination methods.

[0055] Furthermore, the multimodal environmental information collection system of the present invention, which combines the automatic acquisition of specifications through near-field communication tag scanning, the estimation of opening dimensions and identification of ceiling finishing materials based on a vision AI algorithm, and the automatic extraction of spatial parameters through linkage with an architectural information model database, has the advantageous effect of significantly reducing environmental information collection time and eliminating measurement errors compared to conventional methods that required manual user measurements or on-site visits by experts. This can be achieved through a specific mechanism that maximizes the accuracy and completeness of the environmental profile by fusing multi-source information.

[0057] Furthermore, the compatibility determination unit of the present invention filters electrical compatibility, mechanical compatibility, and control compatibility in multiple stages, and in particular, determines whether additional drilling and anchor installation are possible by comparing the ceiling finishing material and opening dimensions estimated by Vision AI with the required drilling dimensions of the replacement candidate lighting fixture, and calculates the target illuminance based on the area, floor height, and use of the space extracted from the building information model, and simulates whether the luminous flux and light distribution curve of the replacement candidate lighting fixture satisfy this, thereby providing a technical effect of significantly reducing the replacement failure rate and reducing re-construction costs by eliminating in advance the possibility of problems such as dimming protocol mismatch, ceiling structure unsuitability, and illuminance performance substandard after replacement, compared to the conventional method of only checking electrical specifications or physical dimensions in a fragmentary manner.

[0059] In addition, the construction linkage unit of the present invention calculates construction feasibility information for a suitable candidate, including estimated construction time, available visit schedule, whether prior site verification is required, whether no drilling or partial drilling is required, whether existing switches and dimming devices can be reused, and whether additional materials are required; and the user terminal providing unit visualizes and provides this information while simultaneously providing a consultation request or construction reservation interface to automatically link replacement confirmation and construction reservation, thereby providing a significant effect compared to conventional systems that were limited to product recommendations, by resolving the disconnect from product selection to construction execution, drastically reducing the user's decision-making time, and improving service completeness.

[0061] Furthermore, the present invention has the advantageous effect of a self-learning mechanism through which the prediction accuracy and judgment reliability of the system continuously improve over time by storing actual construction result data after the completion of replacement construction to continuously correct the accuracy of subsequent lifespan prediction or compatibility judgment. This can be achieved through a mechanism that resolves the gap between theory and practice based on actual field data and strengthens adaptability to various environmental conditions and new products.

[0062] Meanwhile, the effects obtainable from the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present invention belongs from the description below. Brief explanation of the drawing

[0063] The following drawings attached to this specification illustrate preferred embodiments of the present invention and serve to further enhance understanding of the technical concept of the present invention together with the detailed description of the invention; therefore, the present invention should not be interpreted as being limited only to the matters described in such drawings. FIG. 1 is a system architecture diagram showing the overall network configuration of a lighting fixture life prediction event-based replacement compatibility determination and construction linkage system according to one embodiment of the present invention, illustrating the communication connection status between a lighting fixture (SMPS) (1), a user smartphone (app) (2), a home network (wall pad) / BIM server (3), a replacement compatibility determination cloud server (4), and an affiliated construction company terminal (5). FIG. 2 is a block diagram showing the internal functional block configuration of a replacement compatibility determination cloud server according to an embodiment of the present invention, illustrating each component including a state data acquisition unit (10), a lifespan prediction event generation unit (20), an environment information collection unit (30), a replacement request profile generation unit (40), a compatibility determination unit (50), a construction linkage unit (60), a user terminal provision unit (70), and an additional service linkage unit (80), and the data flow between them. FIG. 3 is a flowchart illustrating the overall operation process of a method for determining replacement compatibility based on lighting fixture lifespan prediction events and linking construction according to an embodiment of the present invention, showing the temporal flow from the data acquisition step (S10) to the user terminal provision and reservation step (S70). FIG. 4 is a conceptual diagram illustrating an automatic environmental information collection process according to an embodiment of the present invention, illustrating a method for acquiring environmental information through NFC / RFID tag scanning, vision AI-based image analysis, and BIM database linkage. FIG. 5 is a matrix diagram illustrating compatibility determination and filtering logic according to an embodiment of the present invention, showing determination results by criteria such as illuminance satisfaction, perforation size, and control method between the conditions of a replacement request profile and a plurality of replacement candidate databases. FIG. 6 is a diagram showing examples of UI / UX screens of a user terminal according to an embodiment of the present invention, illustrating a lifespan prediction event warning pop-up screen, a replacement candidate suggestion screen, and a construction reservation screen. FIG. 7 is a timing diagram illustrating the relationship with existing SMPS patents according to an embodiment of the present invention, showing the process of transmitting a trigger signal to a replacement compatibility determination cloud server at the time of entering a safe foldback or critical warning section. Specific details for implementing the invention

[0064] The above objects, other objects, features, and advantages of the present invention will be easily understood through the following preferred embodiments associated with the accompanying drawings. However, the present invention is not limited to the embodiments described herein and may be embodied in other forms. Rather, the embodiments introduced herein are provided to ensure that the disclosed content is thorough and complete and to ensure that the spirit of the invention is sufficiently conveyed to a person skilled in the art.

[0065] In this specification, when a component is described as being on another component, it means that it may be formed directly on the other component or that a third component may be interposed between them. Also, in the drawings, the thicknesses of the components are exaggerated for the effective description of the technical content.

[0066] The embodiments described herein will be explained with reference to cross-sectional and / or plan views, which are exemplary illustrations of the invention. In the drawings, the thicknesses of films and regions are exaggerated for effective explanation of the technical content. Accordingly, the shapes of the exemplary drawings may be modified by manufacturing techniques and / or tolerances, etc. Accordingly, the embodiments of the invention are not limited to the specific shapes depicted but include variations in shape produced according to the manufacturing process. For example, a region depicted as a right angle may be rounded or have a certain curvature. Accordingly, the regions illustrated in the drawings have properties, and the shapes of the regions illustrated in the drawings are intended to illustrate specific shapes of the regions of the device and are not intended to limit the scope of the invention. Although terms such as first, second, etc., have been used to describe various components in the various embodiments of this specification, these components should not be limited by such terms. These terms are used merely to distinguish one component from another. The embodiments described and illustrated herein also include their complementary embodiments.

[0067] The terms used herein are for describing the embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used herein, 'comprises' and / or 'comprising' do not exclude the presence or addition of one or more other components to the mentioned components.

[0068] In describing the specific embodiments below, various specific details have been included to explain the invention more specifically and to aid understanding. However, a reader with sufficient knowledge in the art to understand the invention will recognize that it can be used without these various specific details. In some cases, it is noted in advance that commonly known aspects that are not significantly related to the invention have been omitted to prevent unnecessary confusion in describing the invention.

[0070] The present invention relates to a system and method for determining replacement compatibility and linking construction based on lifespan prediction events of lighting fixtures. The purpose is to provide an integrated solution that analyzes status data collected from lighting fixtures or power supply units to preemptively predict the need for replacement before failure occurs, and automatically collects installation environment information to multidimensionally verify candidate lighting fixtures for replacement, thereby enabling seamless linkage to actual construction.

[0072] Conventional lighting fixture management methods primarily involved responding reactively after a failure occurred or replacing fixtures in bulk according to a regular replacement cycle, which could lead to inconvenience and safety hazards due to sudden lighting failures. Furthermore, when selecting replacement products, compatibility verification was limited to fragmentary factors such as considering only electrical specifications or checking physical dimensions. Consequently, problems such as mismatched dimming protocols, ceiling openings, and insufficient illumination occurred after actual installation, resulting in increased re-installation costs. Moreover, collecting installation environment information required manual measurements by the user or on-site visits by experts, consuming time and money. Additionally, the disconnect between the product selection and actual installation processes made it difficult for users to make replacement decisions.

[0074] To solve these problems, the present invention collects various status data in real time from the power supply of a lighting fixture, such as input voltage, output current, internal temperature, accumulated lighting time, number of on / off cycles, dimming control history, output ripple waveform, and protection circuit operation history. By analyzing this data using a machine learning-based algorithm, it generates lifespan prediction events—such as reaching a remaining lifespan threshold, entering safe foldback, accumulating overheating, or an imminent blackout—thereby preemptively notifying of the need for replacement before a failure occurs. Furthermore, by automatically collecting installation environment information using multimodal methods such as near-field communication tag scanning, vision AI-based image analysis, and integration with an architectural information model database, manual user input can be minimized and accuracy improved. Additionally, by comprehensively determining electrical, mechanical, control, and optical compatibility to select only candidates that are actually suitable for installation, the replacement failure rate can be significantly reduced. Moreover, it provides an integrated workflow that automatically calculates feasibility information, such as the scope of construction, estimated construction time, and the need for additional materials, and links with construction companies to handle everything from product selection to construction reservation in a one-stop manner.

[0076] FIG. 1 illustrates an overall network configuration diagram of a lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system according to one embodiment of the present invention. Referring to FIG. 1, the system may have a structure in which a lighting fixture and a power supply unit (1), a user terminal (2), a home network system or a building information model server (3), a replacement compatibility determination cloud server (4), and an affiliated construction company terminal (5) are organically connected through a network.

[0078] The lighting fixture and power supply (1) may include an actually installed lighting fixture and a power supply that drives it, and a sensor module and a communication module capable of measuring and transmitting status data may be built into the power supply or attached externally. The status data may include input voltage, output current, internal temperature, accumulated lighting time, number of on / off repetitions, dimming control history, output ripple waveform, protection circuit operation history, etc., and such data may be transmitted to a replacement compatibility determination cloud server (4) via a wired communication method or a wireless communication method. Bluetooth, Zigbee, Wi-Fi, etc. may be used as wireless communication methods, and protocols such as UART, I2C, and SPI may be used as wired communication methods.

[0080] The user terminal (2) may include electronic devices such as smartphones, tablets, and personal computers, and the user may receive lifespan prediction event notifications, check information on lighting fixtures that are candidates for replacement, and make construction reservations through an application installed on the user terminal (2). The user terminal (2) may be equipped with a camera, a depth sensor, a short-range communication function, etc., and through this, it may capture images of the lighting fixture and ceiling or scan a short-range communication tag to collect environmental information.

[0082] The home network system or the building information model server (3) may include a smart home platform linked to lighting fixtures within the building, a building management system, or a building information model database, and the replacement compatibility determination cloud server (4) can extract parameters such as space usage, floor area, and ceiling height through API linkage with these. The building information model data can be stored in various forms such as IFC format, Revit format, and ArchiCAD format, and the server can process it by converting it into a standardized internal schema.

[0084] The replacement compatibility determination cloud server (4) is a central server in which the core components of the present invention are implemented, and may include a state data acquisition unit, a lifespan prediction event generation unit, an environment information collection unit, a replacement request profile generation unit, a compatibility determination unit, a construction linkage unit, a user terminal provision unit, etc., and may include a database storing replacement candidate lighting fixture information, a database storing past construction history data, a machine learning model, etc. The server may be implemented in a cloud computing environment and can process multiple lighting fixtures and users simultaneously through an scalable architecture.

[0086] The affiliated construction company terminal (5) is a terminal of a construction company responsible for replacing lighting fixtures, and receives a construction request from the replacement compatibility determination cloud server (4), provides an available schedule, and can transmit actual construction result data to the server after the construction is completed. The construction result data may include actual construction time, details of additional material usage, illuminance measurements after installation, user satisfaction, etc., and can be used to continuously improve the prediction accuracy of the system.

[0088] FIG. 2 illustrates an internal functional block diagram of a replacement compatibility determination cloud server according to an embodiment of the present invention. Referring to FIG. 2, the replacement compatibility determination cloud server (4) may include a state data acquisition unit (10), a lifespan prediction event generation unit (20), an environment information collection unit (30), a replacement request profile generation unit (40), a compatibility determination unit (50), a construction linkage unit (60), a user terminal provision unit (70), and an additional service linkage unit (80), and each component may be organically connected according to the data flow.

[0090] The state data acquisition unit (10) can acquire state data from a lighting fixture or a power supply unit of the lighting fixture. The state data may include various parameters indicating the electrical state, thermal state, usage history, etc., of the lighting fixture, and specifically may include input voltage, input current, output voltage, output current, internal temperature, temperature history, cumulative lighting time, number of on / off repetitions, type of dimming signal, dimming control history, output ripple voltage, abnormal waveform information, protection circuit operation history, and estimated light output degradation. The state data acquisition unit (10) may be connected to the power supply unit of the lighting fixture via a wired or wireless communication interface and may receive state data in real time or periodically. In some embodiments, the state data acquisition unit (10) may receive data from an externally attached sensor module that can be retrofitted to the lighting fixture, and such a sensor module may operate via low-power wireless communication in a battery or energy harvesting manner. Solar panels, vibration energy harvesters, thermoelectric elements, etc., may be used as energy harvesting methods. The state data acquisition unit (10) can store the collected data in a database of a cloud server and transmit it to the life prediction event generation unit (20).

[0092] The lifespan prediction event generation unit (20) can determine the deterioration state of the lighting fixture by analyzing the state data received from the state data acquisition unit (10) and generate a lifespan prediction event. The lifespan prediction event may include various signs indicating that the failure of the lighting fixture is imminent, specifically, reaching a remaining lifespan threshold, entering safe foldback, accumulating overheating, unstable rated output, an imminent blackout state, etc. The lifespan prediction event generation unit (20) may include a deterioration indicator calculation engine, a threshold-based event trigger, a machine learning-based lifespan prediction model, an abnormal pattern detection module, etc.

[0094] The degradation index calculation engine can calculate a degradation index by synthesizing input voltage fluctuation rate, output current degradation rate, temperature rise trend, and ripple voltage increase rate. For example, the degradation index can be calculated by synthesizing cases where the output current decreases by more than a predetermined percentage compared to the design, the internal temperature rises by more than a predetermined temperature compared to the average, or the output ripple voltage increases by more than a predetermined percentage compared to the design. The threshold-based event trigger can perform multi-stage event determination logic, such as remaining life thresholds, safe foldback entry conditions, overheat accumulation limits, and blackout imminent conditions. The remaining life threshold can be set by considering accumulated lighting time, the number of on / off cycles, and the degradation index, and an event may be generated if the remaining life falls below a predetermined threshold. Safe foldback may refer to a protection mode in which the power supply limits output in an overload or overheating state, and the stress level of the power supply can be quantified by analyzing the frequency and duration of safe foldback entry. The overheating accumulation index can be calculated as an integral of temperature and time, and can assess long-term thermal stress. An imminent blackout condition can be determined by a combination of signs, such as a sudden drop in output current, a surge in ripple voltage, and frequent operation of protection circuits.

[0096] A machine learning-based lifespan prediction model may include a regression model that probabilistically predicts remaining lifespan by learning from past failure data and current state data. Machine learning models such as linear regression, random forests, support vector machines, and neural networks may be used; in particular, LSTM neural networks, which are suitable for time-series data analysis, may be utilized. The machine learning model can predict remaining lifespan by learning time-series patterns of multidimensional data, such as input voltage fluctuation rates, output current degradation rates, temperature rise trends, ripple voltage growth rates, and protection circuit operation frequency, and the prediction results may be provided in the form of a probability distribution. The anomaly pattern detection module may include an anomaly detection algorithm that detects abrupt parameter changes deviating from normal operating patterns in real time; statistical methods, clustering methods, and autoencoders may be used as the anomaly detection algorithm.

[0098] The lifespan prediction event generation unit (20) can transmit the generated lifespan prediction event to the replacement request profile generation unit (40) and transmit a notification trigger signal to the user terminal provision unit (70). The lifespan prediction event may include information such as event type, urgency, expected remaining lifespan, and time of occurrence, and the urgency may be classified into immediate replacement required, replacement recommended within the short term, long-term monitoring, etc.

[0100] The environmental information collection unit (30) can collect installation environment information of a lighting fixture where a lifespan prediction event has occurred. The installation environment information may include physical characteristics of the space where the lighting fixture is installed, specifications of the existing lighting fixture, control environment, etc. Specifically, it may include the type of installation space, area, ceiling height, type of existing lighting fixture, rated power consumption, wiring method, dimming method, ceiling opening dimensions, fastening hole spacing, required illuminance, color temperature range, waterproof or dustproof requirements, information on existing furniture or space style, etc. The environmental information collection unit (30) may include a specification acquisition module (31), a space estimation module (32), and a data linkage module (33), and these can automatically collect environmental information in a multimodal manner.

[0102] The specification acquisition module (31) can automatically receive the hardware specification profile of the lighting fixture to the server as the user terminal scans a near-field communication tag or identification code attached to the lighting fixture. Near-field communication tags such as NFC tags and RFID tags may be used, and identification codes such as QR codes and barcodes may be used. During the manufacturing of the lighting fixture or during the initial installation, a near-field communication tag or identification code may be attached to the power supply enclosure or the inside of the lighting fixture cover, and information such as the product model name, hole dimensions, mounting method, wiring type, dimming protocol, rated power, and luminous flux may be stored therein. When the user scans the tag using the NFC function of the user terminal or scans the QR code through the camera after receiving a lifespan prediction event notification, the specification acquisition module (31) can extract the stored information, convert it into structured data, and transmit it to the server. The specification acquisition module (31) can check the latest product information and discontinuation status in real time by linking with the manufacturer's server, thereby excluding discontinued products when selecting replacement candidates.

[0104] The space estimation module (32) can estimate the diameter of the opening of the lighting fixture and determine the material of the ceiling finishing material by analyzing the lighting fixture and ceiling images obtained through the camera and depth sensor of the user terminal using a vision AI algorithm. The space estimation module (32) may include a vision AI-based image analysis engine, an opening dimension estimation algorithm, a ceiling finishing material determination model, an installation method recognition module, etc.

[0106] A vision AI-based image analysis engine can analyze images of lighting fixtures and ceilings captured by a user terminal camera using deep learning models. Deep learning models that can be used include convolutional neural network-based object detection models and segmentation models; for example, models such as YOLO, Faster R-CNN, and Mask R-CNN may be used. The image analysis engine can detect the outlines of lighting fixtures, separate ceiling areas, and extract opening areas.

[0108] The aperture dimension estimation algorithm detects the outline of the lighting fixture within the image and can estimate the actual dimensions based on depth sensor data or the size of a reference object. LiDAR sensors, ToF sensors, etc., can be used as depth sensors, and they can measure the distance between the camera and the object. An object of known size, such as a user's hand or a credit card, can be used as the reference object, and the user can place the reference object near the lighting fixture during shooting. The aperture dimension estimation algorithm can estimate the diameter or outer dimension of the aperture by calculating the ratio of the pixel distance within the image to the actual distance, and the estimation error can be limited to within a predetermined range.

[0110] The ceiling finishing material identification model can classify the material of the ceiling finishing by analyzing the texture, color, and reflection characteristics of the captured ceiling. Ceiling finishing materials may include gypsum board, plywood, concrete, system ceilings, and wood, and the possibility of additional drilling or the need for anchor installation can be determined based on the material. The ceiling finishing material identification model may include a classification model based on a convolutional neural network, and data augmentation learning may be applied to ensure stable recognition even under various lighting conditions. The installation method recognition module can automatically identify installation types, such as recessed, surface-mounted, rail-mounted, and pendant-mounted, based on image patterns.

[0112] The data linkage module (33) can access a home network system or a building information model database server to which the lighting fixture is linked, and extract parameters such as the use, floor area, and ceiling height of the space where the lighting fixture is located. The data linkage module (33) may include a home network system API linkage interface, a building information model database query interface, a building management system linkage interface, etc.

[0114] The home network system API integration interface can extract spatial information by communicating with a smart home platform via a standard API. Smart home platforms may include SmartThings, Home Assistant, Google Home, Apple HomeKit, etc., and these may support protocols such as REST API and MQTT. The data integration module (33) can retrieve information about the space where the lighting fixture is installed based on the unique identifier of the lighting fixture, and can extract information such as the use and area of ​​the space.

[0116] The architectural information model database query interface can extract usage, floor area, and ceiling height parameters based on space ID from architectural information model data in IFC format. The architectural information model data may include the three-dimensional shape of the building, spatial configuration, equipment information, etc., and may be stored in various formats such as IFC, Revit, and ArchiCAD. The data linkage module (33) can apply an adapter pattern that converts these various formats into a standardized internal schema, thereby absorbing differences between formats.

[0118] The building management system linkage interface can obtain design illuminance and lighting circuit information of the corresponding zone by linking with the building management system of a commercial building. The building management system may refer to a system that integrates and manages various facilities of a building, such as lighting, air conditioning, and security, and may support protocols such as BACnet and Modbus. The data linkage module (33) can enhance security through data access rights management and encrypted communication.

[0120] The environmental information collection unit (30) can integrate environmental information collected through the specification acquisition module (31), the space estimation module (32), and the data linkage module (33) and transmit it to the replacement request profile generation unit (40). In some embodiments, the environmental information collection unit (30) can supplement information that is not automatically collected by providing a simple question interface to the user, and the user can directly input, for example, space area, ceiling height, etc.

[0122] The replacement requirement profile generation unit (40) can generate a replacement requirement profile that structures the technical requirements necessary for replacement by combining life prediction events and installation environment information. The replacement requirement profile may include electrical, mechanical, control, and optical requirements that must be satisfied when replacing a lighting fixture, and this can be used as a criterion for filtering candidate lighting fixtures in the compatibility determination unit (50). The replacement requirement profile generation unit (40) may include an event-environment mapping engine, technical requirement extraction logic, optical requirement calculation logic, constraint specification logic, etc.

[0124] The event-environment mapping engine can determine replacement urgency and priority by associating life prediction event types with environmental information. For example, if an event indicating an imminent blackout occurs, the urgency can be set to "immediate replacement required," while if an event indicating the remaining life threshold has been reached occurs, the urgency can be set to "recommend replacement within the short term." The technical requirements extraction logic can organize the electrical, mechanical, and control specifications of existing lighting into replacement conditions. Electrical specifications may include input voltage, input current, and power consumption; mechanical specifications may include dimensions, weight, and mounting methods; and control specifications may include dimming protocols and communication methods.

[0126] The logic for calculating optical requirements can set target illuminance, color rendering index (CRI), and color temperature ranges based on spatial use and area. Target illuminance can be determined according to spatial use; for example, a living room can be set to approximately 150 to 300 lux, a bedroom to approximately 100 to 150 lux, a kitchen to approximately 300 to 500 lux, and an office to approximately 500 lux. These standards can be established by referring to domestic and international standards, such as KS illuminance standards and IES recommended standards. Color rendering index (CRI) can be expressed as a value, and generally, a value of 80 or higher is recommended. Color temperature can be classified into warm white, medium white, cool white, etc., and the range can be set according to spatial use and user preference.

[0128] The constraint specification logic can list restrictions such as the feasibility of drilling based on the ceiling material, conditions for reusing existing wiring, and compatibility with switches or dimmers. For example, if the ceiling material is gypsum board, it can be set to "drilling possible" because additional drilling is easy; if it is concrete, it can be set to "drilling difficulty high" because anchor installation is required. If the existing wiring is 2-wire, 3-wire lighting fixtures require wiring modification, so this can be specified as a constraint.

[0130] The replacement request profile generation unit (40) can store the generated replacement request profile in a structured data format, and formats such as JSON and XML may be used. The replacement request profile can be transmitted to the compatibility determination unit (50) and used as a candidate filtering criterion, and can be referenced when calculating the construction scope in the construction linkage unit (60).

[0132] The compatibility determination unit (50) can exclude unsuitable candidates and select suitable candidates by comparing information on multiple replacement candidate lighting fixtures stored in a database with a replacement request profile to determine electrical, mechanical, and control compatibility. The compatibility determination unit (50) may include electrical compatibility determination logic, mechanical compatibility determination logic, control compatibility determination logic, and illuminance satisfaction determination logic, and these may select candidates through a multi-stage filtering process.

[0134] The electrical compatibility determination logic can compare the supply voltage and circuit capacity of the existing wiring with the input requirements of the candidate lighting. For example, if the existing wiring supplies AC 220V, it can verify whether the input voltage of the candidate lighting is within the AC 220V range, and flexible matching can be performed by considering the voltage range tolerance. Circuit capacity can be determined by considering factors such as circuit breaker capacity and wiring thickness, and it can be verified whether the power consumption of the candidate lighting does not exceed the circuit capacity. The electrical compatibility determination logic can also verify dimming protocol compatibility and match the existing dimming method with the supported protocol of the candidate lighting. Dimming methods may include 0-10V, PWM, DALI, Bluetooth, Zigbee, etc., and if the protocols do not match, it can determine whether a conversion adapter can be used and present an indirect compatibility option.

[0136] The mechanical compatibility determination logic can determine whether additional drilling and anchor installation are possible by comparing the ceiling finishing material and the opening dimensions of existing lighting, estimated through vision AI image analysis, with the required drilling dimensions of candidate replacement lighting fixtures. The mechanical compatibility determination logic can perform dimensional compatibility verification, evaluation of installation feasibility by ceiling material, review of weight and structural safety, and determination of mounting method compatibility.

[0138] Dimensional compatibility verification can compare the existing opening dimensions estimated by Vision AI with the required hole dimensions of the candidate lighting. If the required hole dimensions of the candidate lighting are less than or equal to the existing opening dimensions, it can be determined that no-drilling compatibility is possible; if the required hole dimensions are greater than the existing opening dimensions, it can be determined that additional drilling is required. Considering the dimensional error range, no-drilling, partial-drilling, and full-drilling scenarios can be presented.

[0140] The assessment of construction feasibility by ceiling material allows for the calculation of the possibility of additional drilling and the difficulty of construction based on the ceiling finishing material. Gypsum board may be judged to have a low difficulty level because additional drilling is easy, while concrete may be judged to have a high difficulty level because anchor installation is required. System ceilings may also be judged to have a low difficulty level because they utilize a modular replacement method, eliminating the need for drilling. The difficulty of construction by ceiling material can be quantified and utilized to predict construction time and costs.

[0142] The weight and structural safety review allows for a comparison of the weight of the candidate lighting with the load-bearing capacity of the existing ceiling structure. If the weight of the candidate lighting exceeds the load-bearing capacity of the existing ceiling structure, structural reinforcement is required, and the product may be deemed unsuitable. Mounting compatibility assesses the possibility of switching between recessed and exposed types, as well as the reusability of the rail system.

[0144] The control compatibility determination logic can verify the control method compatibility between existing wall switches and candidate lights. Wall switches may include standard switches, dimming switches, and sensor-linked switches, and the logic can check whether the candidate lights are compatible with them. The control compatibility determination logic can also verify the feasibility of smart home integration and the communication protocol compatibility between existing home network systems and candidate lights. It can check the possession of certifications for specific smart home platforms, such as Works with SmartThings and Apple HomeKit certifications. By determining the usability of a control protocol conversion gateway, it can provide indirect compatibility options.

[0146] The illuminance satisfaction determination logic calculates the target illuminance based on the space area, floor height, and space use extracted from the building information model, and can simulate whether the luminous flux and light distribution curves of candidate replacement lighting fixtures meet the target illuminance. The illuminance satisfaction determination logic can perform target illuminance calculation, luminous flux calculation and simulation, multi-light placement optimization, and energy efficiency evaluation.

[0148] Target illuminance calculation can apply recommended illuminance standards based on spatial usage, and target illuminance levels can be set for specific uses such as living rooms, bedrooms, kitchens, and offices. Luminous flux calculation and simulation can calculate average illuminance and uniformity using the luminous flux, photometric curve, and installation height of candidate lights as inputs. Illuminance simulation engines may utilize ray tracing algorithms or radiosity algorithms, enabling precise calculations that consider spatial characteristics such as ceiling reflectivity and wall color. Multi-light placement optimization can determine whether target illuminance is achieved by simulating placement locations and the number of lights when multiple lights are installed. Energy efficiency evaluation can calculate energy saving effects by comparing power consumption when the same illuminance is achieved.

[0150] The compatibility determination unit (50) can sequentially perform electrical compatibility first filtering, mechanical compatibility second filtering, control compatibility third filtering, and final verification of illumination satisfaction to remove unsuitable candidates step by step. For the suitable candidates that pass, a comprehensive score can be calculated and the ranking can be sorted, and the comprehensive score can be calculated as a weighted sum of electrical, mechanical, control, and optical compatibility scores. The compatibility determination unit (50) can transmit the selected list of suitable candidates to the construction linkage unit (60) and the user terminal provision unit (70).

[0152] The construction linkage unit (60) can calculate construction feasibility information including an estimated construction scope and schedule for a suitable candidate. The construction feasibility information may include an estimated construction time, a visit schedule, whether prior site verification is required, whether no drilling or partial drilling is required, whether existing switches and dimming devices can be reused, and whether additional materials are required. The construction linkage unit (60) may include a construction scope calculation module, an estimated construction time calculation module, a schedule coordination interface, a module for determining whether prior site verification is required, an additional materials calculation module, and a cost estimate generation module.

[0154] The construction scope calculation module can generate a list of construction items such as no drilling, partial drilling, full drilling, new wiring installation or reuse, and switch replacement or reuse. The construction scope can be determined based on the judgment result of the compatibility judgment unit (50), for example, if it is determined to be non-drilling compatible in the mechanical compatibility judgment, drilling work may not be included in the construction scope.

[0156] The estimated construction time calculation module can extract the average construction time of similar cases based on a historical construction database and correct it by reflecting site characteristics. The historical construction database can store actual construction time data collected after completion, along with variables such as ceiling height, ceiling material, number of lights, and accessibility difficulty. The estimated construction time calculation module may include a machine learning-based construction time prediction model and can output an estimated construction time using site characteristics as input through a regression model. The machine learning model can continuously learn and improve accuracy by receiving feedback on actual construction result data.

[0158] The schedule coordination interface may include a scheduling algorithm that matches the available schedule of a construction company with the user's desired schedule. The construction company can register the available schedule to the server through the affiliated construction company terminal (5), and the schedule coordination interface can propose an optimal construction schedule by comparing the user's desired schedule with the available schedule of the construction company. In the event that an emergency dispatch is required, the priority can be increased to assign an immediately available construction company.

[0160] The module for determining the necessity of a preliminary site inspection can assess the need for a site visit by comprehensively considering Vision AI estimation accuracy, architectural information model data reliability, and special construction conditions. If the Vision AI estimation accuracy is above a predetermined threshold and the architectural information model data reliability is high, it may be determined that a preliminary site inspection is unnecessary; however, if the estimation accuracy is low or special construction conditions exist, a preliminary site inspection may be recommended.

[0162] The additional material calculation module can calculate the list and quantities of necessary materials, such as anchors, wires, connectors, and conversion adapters. Additional materials can be determined based on the scope of construction; for example, if anchor installation is required, anchor bolts can be calculated as additional materials. The cost estimate generation module can calculate the total replacement cost by summing the product price, construction labor costs, and material costs. Product prices can be retrieved in real-time by linking with the manufacturer's or distributor's system, and construction labor costs can be calculated based on construction time and difficulty.

[0164] The construction linkage unit (60) can transmit the calculated construction feasibility information to the user terminal providing unit (70), and when the user confirms the construction reservation, it can automatically generate a work order by linking with the construction company system. In some embodiments, the construction linkage unit (60) can automatically collect quotes from multiple cooperating companies and provide selection options to the user.

[0166] The user terminal providing unit (70) can display a failure imminent notification based on a lifespan prediction event to the user terminal, while simultaneously providing information on suitable candidates and construction feasibility. The user terminal providing unit (70) may include a failure imminent notification module, a suitable candidate visualization interface, a construction information dashboard, an augmented reality preview function, a comparison and selection tool, a consultation request and construction reservation interface, etc.

[0168] The failure imminent notification module can immediately notify users of life prediction events via multiple channels, such as push notifications, in-app messages, and email. The notification message may include information such as the event type, urgency, and estimated remaining lifespan, and users can navigate to a detailed information screen by clicking the notification.

[0170] The suitable candidate visualization interface can display products that have passed compatibility assessments in a card-based UI, along with their images, specifications, prices, and compatibility scores. Each candidate card may display product images, model names, manufacturers, luminous flux, color temperature, power consumption, prices, and compatibility scores, and users can click on a card to view detailed information. Candidates with high compatibility scores may be displayed with a recommendation badge.

[0172] The construction information dashboard can visualize estimated construction time, available visit schedules, the need for additional materials, and whether the work is non-drilling or partially drilled using icons and timelines. The dashboard can utilize graphic elements to enable users to intuitively understand the construction scope and schedule; for example, a green icon may indicate non-drilling, a yellow icon for partial drilling, and a red icon for full drilling.

[0174] The augmented reality preview feature allows users to view the installed lighting after replacement in augmented reality through the user's device camera. The augmented reality preview feature can be implemented based on augmented reality platforms such as ARCore and ARKit, and when the user points the camera at the ceiling, a 3D model of the selected candidate light can be overlaid and displayed in the actual space. Through the augmented reality preview, users can check the size, design, and installation location of the light in advance.

[0176] The comparison and selection tool can provide a table view that compares multiple suitable candidates based on criteria such as performance, price, design, and energy efficiency. The comparison table can arrange the key specifications of each candidate side-by-side to enable easy comparison, and users can sort the candidates in their desired order by changing the sorting criteria.

[0178] The consultation request and construction reservation interface can provide a form that allows users to request an expert consultation or schedule a construction date with a single click. Users can select a candidate, click the construction reservation button to choose a desired schedule, and confirm the reservation; upon confirmation, a work order can be automatically sent to the construction company. Clicking the consultation request button allows users to proceed with a consultation with an expert via chat, phone, or video call.

[0180] The user terminal providing unit (70) can be implemented as a responsive web or app design and can provide a consistent user experience on various devices such as smartphones, tablets, and personal computers. The user terminal providing unit (70) can feed back user selection and reservation information to the construction linkage unit (60) and the database, and can collect user feedback to use for system improvement.

[0182] The additional service linkage unit (80) can propose to the user terminal an additional service that includes at least one of furniture, curtains, indirect lighting, and partial remodeling corresponding to existing furniture or space style information, based on a suitable candidate that has passed the compatibility determination unit (50). The additional service linkage unit (80) may include a style analysis engine, a recommendation algorithm, a partner linkage API, etc.

[0184] The style analysis engine can extract furniture, curtain, and wallpaper colors and styles from spatial images captured by vision AI. Through an image classification model, the engine can classify spatial styles into modern, classic, minimalism, industrial, etc., and identify key colors by extracting color palettes.

[0186] The recommendation algorithm can suggest furniture, curtains, and indirect lighting products that harmonize with the design and color temperature of the replacement lighting. The recommendation algorithm may include a hybrid recommendation system combining collaborative filtering and content-based filtering, and can improve the accuracy of personalized recommendations by learning from user selection history. For example, if the replacement lighting is a modern style with a black metal finish, it can recommend gray-toned furniture, minimalist curtains, and black-framed wall art that harmonize with it.

[0188] The partner integration API can link with furniture shopping malls and interior design company systems to link real-time product information and quotes. The partner integration API can support protocols such as REST API and GraphQL, and can retrieve information such as product images, prices, and inventory status in real time. The additional service linkage unit (80) can provide an integrated ordering option that allows ordering additional services together with lighting replacement, and can provide discount benefits when purchased together.

[0190] The system stores actual construction result data after the completion of replacement construction, thereby continuously correcting the accuracy of subsequent lifespan prediction or compatibility determination. The actual construction result data may include actual construction time, details of additional material usage, illuminance measurements after installation, user satisfaction, etc., and can be transmitted to the server via an affiliated construction company terminal (5). The server can feed the collected data back to a lifespan prediction model, a compatibility determination algorithm, and a construction time prediction model to continuously learn and improve accuracy. For example, if the actual construction time differs from the predicted construction time, the construction time prediction model can learn from the data to improve the prediction accuracy under similar conditions. If the illuminance measurements after installation differ from the simulation results, the illuminance simulation engine can increase accuracy by adjusting the correction coefficient.

[0192] FIG. 3 illustrates an overall flowchart of a method for determining replacement compatibility and linking construction based on lighting fixture lifespan prediction events according to an embodiment of the present invention. Referring to FIG. 3, the present method may include a state data acquisition step (S10), a lifespan prediction event generation step (S20), an environment information collection step (S30), a replacement request profile generation step (S40), a compatibility determination step (S50), a construction feasibility information calculation step (S60), and a user terminal provision and reservation step (S70).

[0194] In the status data acquisition step (S10), the server may acquire status data from a lighting fixture or a power supply unit of the lighting fixture. The status data may include input voltage, output current, internal temperature, cumulative lighting time, number of on / off repetitions, dimming control history, output ripple waveform, protection circuit operation history, etc., and may be collected in real time or periodically via wired or wireless communication.

[0196] In the life prediction event generation step (S20), the server can analyze status data to determine the deterioration state of the lighting fixture and generate a life prediction event. The server can calculate a deterioration index, perform a threshold-based event trigger, and predict the remaining lifespan through a machine learning-based life prediction model. The life prediction event may include reaching a remaining lifespan threshold, entering a safe foldback, accumulating overheating, or an imminent blackout state, and may also have an urgency level set.

[0198] In the environmental information collection step (S30), the server can collect installation environment information of the lighting fixture where the lifespan prediction event occurred. The environmental information collection step (S30) may include a step of estimating the opening dimensions and ceiling finishing material of the existing lighting fixture through image analysis using a camera of a user terminal, and a step of extracting area and floor height parameters of the space by linking with an architectural information model database. The server can automatically receive a hardware specification profile as the user terminal scans a near-field communication tag or identification code attached to the lighting fixture, and can estimate the opening diameter and determine the ceiling finishing material by analyzing the image with a vision AI algorithm. The server can extract space usage, floor area, and ceiling height parameters by accessing a home network system or an architectural information model database server.

[0200] In the replacement requirement profile generation step (S40), the server may generate a replacement requirement profile that structures the technical requirements necessary for replacement by combining life prediction events and installation environment information. The replacement requirement profile may include electrical requirements, mechanical requirements, control requirements, optical requirements, constraints, etc., and may be stored in a structured data format.

[0202] In the compatibility determination step (S50), the server can exclude unsuitable candidates and select suitable candidates by comparing information on multiple replacement candidate lighting fixtures and replacement requirement profiles to determine electrical, mechanical, and control compatibility. The compatibility determination step (S50) can verify compatibility by determining whether additional drilling is possible by comparing the estimated ceiling finishing material and opening dimensions with the drilling requirement dimensions of the replacement candidate lighting fixtures, and by determining whether the luminous flux of the replacement candidate lighting fixtures satisfies the target illuminance calculated based on the extracted area and floor height parameters. The server can sequentially determine electrical compatibility, mechanical compatibility, control compatibility, and illuminance satisfaction to gradually remove unsuitable candidates, and calculate a comprehensive score for the suitable candidates that pass to sort their rankings.

[0204] In the step of calculating feasibility information (S60), the server can calculate feasibility information for suitable candidates. Feasibility information may include estimated construction time, available visit schedule, whether prior site verification is required, whether no drilling or partial drilling is required, whether existing switches and dimming devices can be reused, and whether additional materials are required. The server can calculate the estimated construction time based on past construction history data, query the available schedule of construction companies, and generate a list of additional materials and cost estimates.

[0206] In the user terminal provision and reservation step (S70), the server can display an imminent failure notification based on a lifespan prediction event to the user terminal, while simultaneously providing information on suitable candidates and construction feasibility. The user terminal provision and reservation step (S70) can automatically link the confirmation of replacement of suitable candidates with construction reservation by providing visualized construction feasibility information to the user terminal and simultaneously providing a consultation request or construction reservation interface. The server can send the imminent failure notification via push notification, in-app message, email, etc., display suitable candidates using a card-type UI, visualize construction information on a dashboard, provide an augmented reality preview function, provide comparison and selection tools, and provide a consultation request and construction reservation interface. When the user selects a candidate and confirms the construction reservation, the server can automatically send a work order to the construction company and complete the reservation.

[0208] FIG. 4 illustrates a conceptual diagram of automatic environmental information collection according to an embodiment of the present invention. Referring to FIG. 4, when a user photographs a lighting fixture and a ceiling with a smartphone, the process of a vision AI scanning and recognizing the perforation dimensions and ceiling material, and the process of drawing architectural information model data from a home network system to calculate the area and floor height can be visualized. On the camera screen of the user terminal, the outline of the lighting fixture may be detected and the opening area highlighted, and the estimated opening diameter and ceiling material information may be overlaid on the screen. Information regarding space use, area, and floor height extracted from the home network system or the architectural information model server may be displayed on the user terminal screen, and the user can check and modify it if necessary.

[0210] FIG. 5 illustrates a matrix diagram of a compatibility determination and filtering logic according to an embodiment of the present invention. Referring to FIG. 5, conditions of a replacement request profile are listed on the left, and a plurality of replacement candidate lighting fixtures are arranged on the right. A schematic diagram in the form of a matrix indicating whether a candidate passes or is excluded for each condition may be displayed. For example, regarding criteria such as illuminance satisfaction, hole size, and control method, Candidate 1 passes all criteria and is selected as a suitable candidate, Candidate 2 fails to pass the hole size criterion and is classified as conditionally suitable, and Candidate 3 fails to pass the control method criterion and is excluded as unsuitable. The matrix can clearly show the compatibility determination results of each candidate visually and can help a user or system administrator understand the determination logic.

[0212] FIG. 6 illustrates an example of a user terminal UI or UX screen according to an embodiment of the present invention. Referring to FIG. 6, a smartphone screen may be arranged in three sections side by side. The first screen is a warning pop-up screen that may display a message such as, "Living room lighting entering safe foldback! Lifespan remaining at a predetermined rate." The second screen is a candidate suggestion screen that may display a list of products, such as Product A which is compatible without drilling and Product B which requires drilling into drywall, along with an estimated quote. Each product card may include an image, specifications, price, compatibility score, recommendation badge, etc. The third screen is a reservation screen that displays available construction dates in a calendar format and may include payment or reservation completion buttons. Through an intuitive UI, the user can check lifespan prediction events, compare suitable candidates, and easily proceed with construction reservations.

[0214] FIG. 7 illustrates a timing diagram of interoperability with an existing power supply patent according to an embodiment of the present invention. Referring to FIG. 7, the process of sending a trigger signal to the replacement compatibility determination cloud server of the present invention at the time when the power supply of a lighting fixture enters a safe foldback or critical warning section can be visualized. The power supply can be divided into a normal operation section, a Level 1 protection section, a Level 2 protection section, a Level 3 critical warning section, etc., in the output control timing graph, and a trigger signal can be generated at the time of entering the Level 2 protection section or the Level 3 critical warning section. The trigger signal can be transmitted to the cloud server through the communication module of the power supply, and the server can receive it to generate a lifespan prediction event and start a subsequent process. This interoperability can demonstrate that the existing hardware patent and the platform patent of the present invention operate as a single integrated ecosystem.

[0216] Specific embodiments of the present invention will be described below.

[0218] Example 1: Household LED Downlight Replacement Scenario

[0220] Assume that an LED downlight installed in the living room has triggered a life prediction event. The lighting fixture is recessed, operates on AC 220V, has an output of approximately 15W, has an opening diameter of approximately 100mm, does not support dimming protocols, and has a gypsum board finish on the ceiling.

[0222] The state data acquisition unit (10) can collect state data from a Bluetooth sensor module retrofitted to a lighting fixture. The input voltage is within the normal range of AC 220V, the output current has decreased by about 15% compared to the design, the internal temperature is trending upward by about 10 degrees compared to the average, the cumulative lighting time is about 20,000 hours, the number of on / off cycles is about 50,000 times, and the output ripple voltage has increased by about 20% compared to the design.

[0224] The life prediction event generation unit (20) analyzes data to calculate a degradation index by combining the output current reduction rate, temperature rise trend, and ripple increase rate, and the machine learning model predicts the remaining lifespan as approximately 1,000 hours, generates a "remaining lifespan threshold reached" event, and can send a push notification to the user app.

[0226] The environment information collection unit (30) can automatically receive product model name, hole dimensions, mounting method, wiring type, and dimming protocol information by scanning an NFC tag attached to a lighting fixture according to the instructions of the app. When the user photographs the lighting fixture and ceiling with the app camera, the vision AI of the space estimation module (32) analyzes the image to estimate the opening diameter as approximately 100 mm and can identify the ceiling finishing material as gypsum board. The data linkage module (33) links with the user's smart home system to confirm that the space is a living room, and can collect that the living room area is approximately 20 square meters and the ceiling height is approximately 2.5 meters through user input.

[0228] The replacement request profile generation unit (40) can generate a replacement request profile by integrating collected information. The event type is reaching the remaining life threshold, the urgency is recommended to replace within the short term, the electrical requirements are AC 220V, power consumption is about 15W or less, the mechanical requirements are recessed type, opening is 100mm, the control requirements are no dimming required, and the optical requirements are for living room use, area is 20 square meters, floor height is 2.5 meters, and target illuminance is about 150 to 300 lux.

[0230] The compatibility determination unit (50) can compare with the replacement candidate lighting fixture information in the database. Candidate A is AC 220V, 12W, recessed type, opening 100mm, non-dimmable, luminous flux 1000 lumens, and beam angle 120 degrees, and can be selected as a suitable candidate with a total score of 95 points after passing all electrical compatibility, mechanical compatibility, control compatibility, and illuminance requirements. Candidate B is AC 220V, 10W, recessed type, opening 120mm, DALI dimming, and luminous flux 800 lumens, and can be classified as conditionally suitable with a total score of 70 points because the opening 120mm is larger than the existing 100mm, requiring additional drilling and increasing construction costs.

[0232] The construction linkage unit (60) can set the construction scope for candidate A to no drilling, reuse of wiring, and reuse of switches, calculate the estimated construction time to be about 30 minutes, calculate that additional materials are unnecessary, prior site verification is unnecessary, and that a visit can be scheduled starting from 3 days later.

[0234] The user terminal providing unit (70) can display a notification on the app screen stating, "The remaining lifespan of the living room LED downlight is about 3 months. We recommend early replacement.", display candidate A with a recommendation badge, display no drilling, estimated construction time of 30 minutes, and estimated cost, provide an AR preview button, and provide a construction reservation button. When the user selects candidate A and proceeds with the construction reservation, the construction company can visit at the scheduled time to perform the replacement work.

[0236] After construction is completed, the actual construction time is 25 minutes, no additional materials are used, the illuminance measurement after installation averages approximately 210 lux, and user satisfaction is 5 out of 5. The collected data is fed back into the system to calibrate the construction time prediction model and verify the accuracy of the illuminance simulation.

[0238] Example 2: Commercial Building Office Lighting Replacement Scenario

[0240] Assume a case where an LED flat panel light, installed as a replacement for a fluorescent light in an office on the 5th floor of an office building, triggers a lifespan prediction event. The lighting fixture is a ceiling-mounted flat panel light, operates on AC 220V, has an output of 40W, measures 600mm x 600mm, supports DALI dimming, the ceiling is a system ceiling, and it is a smart building linked with a building management system.

[0242] The status data acquisition unit (10) can receive status data from the IoT module embedded in the lighting fixture through the building management system server. The input voltage is AC 220V, the output current has decreased by about 20% compared to the design, the internal temperature has risen by about 15 degrees compared to the average, the cumulative lighting time is about 30,000 hours, the dimming control history has mainly operated at 70 to 80% output, and the protection circuit operation history has recorded overheat protection operation about 10 times.

[0244] The life prediction event generation unit (20) can generate an "overheat accumulation and blackout imminent" event by combining output current reduction, temperature rise, and frequent overheat protection operations, set the urgency to require immediate replacement, and send an email and building management system dashboard notification to the building manager.

[0246] The environmental information collection unit (30) can extract that the space where the lighting is installed is the 5th floor office Zone A, the space use is an office, the floor area is about 50 square meters, the ceiling height is about 2.7 meters, the ceiling type is a system ceiling, and the design illuminance is 500 lux by the data linkage module (33) accessing the building information model database. When the building manager photographs the lighting fixture with a mobile app, the space estimation module (32) recognizes the system ceiling grid pattern and can confirm the lighting size as 600mm x 600mm.

[0248] The replacement requirement profile generation unit (40) can generate a replacement requirement profile in which the urgency is set to immediate replacement requirement, the electrical requirement is AC 220V and DALI dimming support is mandatory, the mechanical requirement is a modular system ceiling with a size of 600mm x 600mm, the control requirement is DALI protocol compatible and compatible with a building management system, and the optical requirement is office use, area of ​​50 square meters, floor height of 2.7 meters, and target illuminance of 500 lux.

[0250] The compatibility determination unit (50) can select candidate A by searching a commercial lighting database. Candidate A is AC 220V, 36W, DALI dimming, system ceiling modular type, 600mm x 600mm, luminous flux 4500 lumens, uniformity 0.7 or higher, and can be selected as a suitable candidate with a total score of 98 points after passing all electrical compatibility, mechanical compatibility, control compatibility, and illuminance requirements.

[0252] The construction linkage unit (60) sets the construction scope for candidate A to no drilling, reuse of wiring, and reconnection of the DALI line, calculates the estimated construction time as about 20 minutes, the additional material is a DALI connector, no prior site verification is required, and calculates the visit schedule as being capable of emergency response.

[0254] The user terminal providing unit (70) can display an urgent notification on the building manager's building management system dashboard and mobile app stating "Lighting blackout imminent in 5th floor office Zone A, immediate replacement needed," display candidate A, provide an emergency dispatch option, display simulation results as a heatmap, and provide approval and reservation buttons. If the building manager approves the emergency dispatch, the construction company can visit on the same day to perform the replacement work.

[0256] After construction was completed, the actual construction time was 18 minutes, the additional material required was one DALI connector, the illuminance measurements after installation averaged approximately 505 lux, the uniformity was 0.76, and the building manager satisfaction was 5 out of 5. The feedback data is stored in the system to verify the accuracy of construction time prediction and illuminance simulation.

[0258] Example 3: Smart Home Integrated Lighting Replacement and Interior Linkage Scenario

[0260] Assume a case where a pendant light in a bedroom of an apartment equipped with a smart home system triggers a lifespan prediction event. The lighting fixture is a pendant type, operates on AC 220V, has an output of 25W, supports Bluetooth dimming, is a design light, the ceiling is a concrete slab, has existing anchors installed, and is connected to a smart home hub.

[0262] The status data acquisition unit (10) can receive data from the Bluetooth module built into the lighting fixture to a cloud server via a smart home hub. The input voltage is AC 220V, the output current has decreased by about 10% compared to the design, the internal temperature is within the normal range, the cumulative lighting time is about 15,000 hours, the dimming control history has mainly operated at 50% output, and safe foldback entry has occurred about 5 times recently.

[0264] The lifespan prediction event generation unit (20) determines frequent safe foldback entry as a major indicator, generates a "safe foldback entry and remaining lifespan threshold reached" event, sets the urgency to recommend replacement within the short term, and can send a push notification to the user's smartphone app.

[0266] The environment information collection unit (30) receives product information when the user scans the lighting fixture QR code in the app, and when the user photographs the bedroom and lighting with the app camera, the space estimation module (32) analyzes the image to determine the ceiling material as a concrete slab, recognizes the existing anchor location and hanger connection method, and analyzes the bedroom furniture style as modern minimalism. The data linkage module (33) links with the smart home hub to confirm that the space is used as a bedroom, and can collect that the bedroom area is approximately 15 square meters and the ceiling height is approximately 2.4 meters through user input.

[0268] The replacement requirement profile generation unit (40) can generate a replacement requirement profile in which the urgency is set to recommend replacement within the short term, the electrical requirements are AC 220V and Bluetooth dimming support, the mechanical requirements are pendant type, concrete ceiling anchor reusable or new anchor installation, the control requirements are Bluetooth or smart home hub compatible protocol, the optical requirements are bedroom use, area 15 square meters, ceiling height 2.4 meters, target illuminance about 100 to 150 lux, and the design requirements are in harmony with a modern minimalist style.

[0270] The compatibility determination unit (50) can select candidate A by searching the design lighting database. Candidate A is AC 220V, 20W, Bluetooth dimming, pendant type, adjustable hanger length, reusable anchor, luminous flux 1200 lumens, color temperature 3000K, modern minimalism, black metal finish, and can be selected as a suitable candidate with a total score of 96 points after passing all electrical compatibility, mechanical compatibility, control compatibility, illuminance satisfaction, and design harmony.

[0272] The construction linkage unit (60) can set the construction scope for candidate A to no drilling, reuse of wiring, and replacement of hangers, calculate the estimated construction time to be about 40 minutes, calculate that additional materials are unnecessary, prior site verification is unnecessary, and that a visit can be scheduled starting from 2 days later.

[0274] The additional service linkage unit (80) can extract furniture style and color palette from a captured bedroom image using Vision AI, and the recommendation algorithm can suggest additional services that harmonize with candidate A lighting. Additional services may include a gray-toned bed cover set in a modern minimalist style, LED strip indirect lighting that can be installed under the bed, and minimal abstract wall art with a black frame, and real-time product information and prices can be displayed through integration with a partner shopping mall API.

[0276] The user terminal providing unit (70) can display a notification on the app screen stating "Frequent safe foldback of bedroom pendant light, recommended for replacement in the short term," display candidate A with a recommendation badge, provide an AR preview function, provide an illuminance simulation 3D view, display an additional service suggestion section, and provide an integrated order option. When the user selects candidate A and indirect lighting and proceeds with the construction reservation, the construction company can visit after 2 days to perform the pendant light replacement and indirect lighting installation work.

[0278] After installation is complete, the actual installation time is a total of 1 hour, consisting of 35 minutes for the pendant lighting and 25 minutes for the indirect lighting. The additional material required is double-sided tape for attaching LED strips. The illuminance measurements after installation show an average of approximately 125 lux for the pendant alone and approximately 150 lux when indirect lighting is added, with user satisfaction rated at 5 out of 5. Feedback data is stored in the system to improve the accuracy of pendant lighting installation time predictions, measure the performance of additional service recommendation algorithms, and verify the accuracy of design style matching.

[0280] According to some other embodiments of the present invention, a sensor module for collecting state data may be operated by an energy harvesting method. Solar panels, vibration energy harvesters, thermoelectric elements, etc., may be used as energy harvesting methods, thereby eliminating the need for battery replacement and reducing maintenance costs. Solar panels may be applied to lighting fixtures installed near windows, and vibration energy harvesters may be applied to factories or transportation facilities in environments with vibration.

[0282] According to some other embodiments of the present invention, some processing of lifespan prediction event generation and compatibility determination can be performed locally using an edge computing method. A lightweight machine learning model is installed on the gateway device to perform the initial lifespan prediction determination locally, thereby reducing cloud communication load and improving real-time responsiveness. The edge computing method can be applied to environments with unstable network connections or privacy-sensitive facilities.

[0284] According to some other embodiments of the present invention, product information, construction date and time, construction company, and warranty conditions may be recorded on a blockchain after the completion of replacement construction. Blockchain-based construction history management can provide tamper-proof and transparent history management, and enables verification of lighting history and transfer of warranties during second-hand transactions. Blockchain-based construction history management can be applied to asset management of commercial buildings or public facilities.

[0286] According to some other embodiments of the present invention, the system can provide multilingual and multi-regional support. It can accommodate national environments with different building information model data formats, illumination standards, and voltage specifications; databases of national electrical safety regulations and building codes can be integrated; and product information from global manufacturers can be supported in multiple languages. Multilingual and multi-regional support can be applied to global building management services or facilities of multinational corporations.

[0288] According to some other embodiments of the present invention, a user can check lifespan prediction events and schedule replacements through a voice interface. Voice assistants such as Alexa, Google Assistant, and Siri may be used, and the user can use natural language commands such as "Tell me the status of my living room lighting" or "Schedule a replacement with recommended lighting." The voice interface may be useful for users for whom accessibility is important, such as the visually impaired or the elderly, and may be applied in smart home environments or facilities that prioritize accessibility.

[0290] According to the present invention, by multidimensionally determining replacement compatibility based on lifespan prediction events of lighting fixtures and automatically linking construction, it is possible to achieve effects such as preemptive replacement before failure occurs, a significant reduction in replacement failure rates, drastically shortened decision-making time, optimized energy efficiency, innovative user experience, and expanded service ecosystem. Furthermore, through the automatic collection of multimodal environmental information, manual user input can be minimized and accuracy increased, and accuracy can be continuously improved over time through a closed-loop learning system. The present invention can be applied to various fields such as residential lighting, commercial building lighting, and public facility lighting, and can provide industrial effects such as differentiation of after-sales service by lighting manufacturers, improved building management efficiency, energy savings, and environmental contribution.

[0292] Although preferred embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements by those skilled in the art using the basic concept of the present invention as defined in the following claims also fall within the scope of the present invention. Explanation of the symbols

[0293] 1: Lighting fixtures and power supplies 2: User terminal 3: Home network system or building information model server 4: Cloud Server Replacement Compatibility Assessment 5: Affiliate Construction Company Terminal 10: Status Data Acquisition Unit 20: Life Prediction Event Generation Unit 30: Environmental Information Collection Department 31: Specification Acquisition Module 32: Spatial Estimation Module 33: Data Integration Module 40: Replacement Request Profile Generation Section 50: Compatibility determination unit 60: Construction connection section 70: User terminal providing unit 80: Value-added service linkage section S10: Status data acquisition step S20: Lifetime prediction event generation step S30: Environmental Information Collection Phase S40: Replacement request profile generation step S50: Compatibility determination stage S60: Construction feasibility information calculation step S70: User terminal provision and reservation stage

Claims

Claim 1 A state data acquisition unit that acquires state data from a lighting fixture or a power supply unit (SMPS) of the lighting fixture; a lifespan prediction event generation unit that analyzes the state data to determine the deterioration state of the lighting fixture and generates a lifespan prediction event; an environment information collection unit that collects installation environment information of the lighting fixture where the lifespan prediction event occurred; a replacement request profile generation unit that combines the lifespan prediction event and the installation environment information to generate a replacement request profile that structures the technical requirements necessary for replacement; a compatibility determination unit that excludes unsuitable candidates and selects suitable candidates by determining electrical, mechanical, and control compatibility by comparing information on multiple replacement candidate lighting fixtures stored in a database with the replacement request profile; a construction linkage unit that calculates construction feasibility information including an expected construction scope and schedule for the suitable candidates; and a user terminal provision unit that displays an imminent failure notification based on the lifespan prediction event to a user terminal while simultaneously providing the suitable candidates and the construction feasibility information. A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system, comprising: a lifespan prediction event generation unit that generates a lifespan prediction event in a Safe-Foldback entry state by analyzing the operation history of a protection circuit included in the state data; an environment information collection unit that automatically collects installation environment information where the lighting fixture is located in a multimodal manner using the generation of the lifespan prediction event in the Safe-Foldback entry state as a trigger; and a compatibility determination unit that calculates a target illuminance based on the area, floor height, and space use of the space extracted through the environment information collection unit, and performs multi-stage filtering including an illuminance satisfaction determination logic that simulates whether the luminous flux (Lumen) and light distribution curve of the replacement candidate lighting fixture satisfy the target illuminance. Claim 2 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system according to claim 1, wherein the status data includes at least one of input voltage, output current, internal temperature, accumulated lighting time, number of on / off repetitions, dimming control history, output ripple waveform, and protection circuit operation history, and the lifespan prediction event includes at least one of reaching a remaining lifespan threshold, entering Safe-Foldback, accumulated overheating, and an imminent blackout state. Claim 3 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system, wherein, in claim 1, the environment information collection unit includes a specification acquisition module that automatically receives a hardware specification profile of an existing lighting fixture, including the hole dimensions, mounting method, wiring type, and dimming protocol of the lighting fixture, to a server as the user terminal scans a near-field communication tag (NFC / RFID) or identification code (QR code) attached to the lighting fixture. Claim 4 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system, wherein the environment information collection unit includes a spatial estimation module that analyzes the lighting fixture and ceiling images acquired through the camera and depth sensor of the user terminal using a vision AI algorithm to estimate the diameter of the opening of the lighting fixture and determine the material of the ceiling finishing material. Claim 5 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system, wherein, in claim 1, the environment information collection unit includes a data linkage module that accesses a home network system or a Building Information Model (BIM) database server linked to the lighting fixture and extracts parameters of the use, floor area, and ceiling height of the space where the lighting fixture is located. Claim 6 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system according to claim 1, wherein the compatibility determination unit further includes mechanical compatibility logic that determines whether additional drilling and anchor installation are possible by comparing the ceiling finishing material and the opening dimensions of the existing lighting estimated through vision AI image analysis with the required drilling dimensions of the replacement candidate lighting fixture, thereby removing the unsuitable candidate. Claim 7 A lighting fixture lifespan prediction event-based replacement compatibility determination and construction linkage system according to claim 1, further comprising an additional service linkage unit that proposes to the user terminal an additional service including at least one of furniture, curtains, indirect lighting, and partial remodeling corresponding to existing furniture or space style information based on a suitable candidate that has passed the compatibility determination unit, wherein the system stores actual construction result data after the completion of replacement construction and continuously corrects the accuracy of subsequent lifespan prediction or compatibility determination. Claim 8 A method for determining replacement compatibility based on lighting fixture lifespan prediction events and linking construction using a linkage system according to claim 1, comprising: (a) acquiring status data from a lighting fixture or a power supply unit of said lighting fixture; (b) analyzing said status data to determine the deterioration state of said lighting fixture and generating a lifespan prediction event; (c) collecting installation environment information of the lighting fixture where said lifespan prediction event occurred; (d) combining said lifespan prediction event and said installation environment information to generate a replacement requirement profile that structures the technical requirements necessary for replacement; (e) excluding unsuitable candidates and selecting suitable candidates by determining electrical, mechanical, and control compatibility by comparing a plurality of replacement candidate lighting fixture information and said replacement requirement profile; (f) calculating construction feasibility information for said suitable candidates; and (g) displaying an imminent failure notification based on said lifespan prediction event to a user terminal while simultaneously providing said suitable candidates and said construction feasibility information; characterized by comprising: Claim 9 In claim 8, the above step (c) includes a step of estimating the opening dimensions and ceiling finishing material of an existing lighting fixture through image analysis using a camera of a user terminal, and a step of extracting area and floor height parameters of the space by linking with a Building Information Model (BIM) database, and the above step (e) is characterized by determining whether additional drilling is possible by comparing the estimated ceiling finishing material and opening dimensions with the required drilling dimensions of the replacement candidate lighting fixture, and verifying the compatibility by determining whether the luminous flux of the replacement candidate lighting fixture satisfies the target illuminance calculated based on the extracted area and floor height parameters. Claim 10 In claim 8, the construction feasibility information of step (f) includes the estimated construction time, the schedule for a visit, whether prior site verification is required, whether no drilling or partial drilling is required, whether existing switches and dimming devices can be reused, and whether additional materials are required; and step (g) is characterized by providing the construction feasibility information to the user terminal in a visualized manner, and simultaneously providing a consultation request or construction reservation interface to automatically link the confirmation of replacement of the suitable candidate and the construction reservation.

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