A conference projection management system and method based on big data

Abstract

The present invention relates to the field of big data technology, and specifically to a conference projection management system and method based on big data, comprising: a projection data acquisition module, a database, a data analysis module, a projection device matching module and a conference projection selection management module, wherein the projection data acquisition module collects user demand data on projection devices and performance data of projection devices, the database stores all collected data, the data analysis module compares and analyzes user demand data on projection devices and performance data of projection devices, the projection device matching module analyzes the matching degree between different projection devices and user demand, the conference projection selection management module selects and matches projection devices for users, better selects more suitable projection devices for users, and improves the convenience and experience of using projection devices in different user meetings.

Description

Technical Field

[0001] The present invention relates to the technical field of big data, and in particular to a conference projection management system and method based on big data. Background Art

[0002] With the development of technology, projectors are increasingly used in business meetings. When choosing a projector, users need to consider factors such as image quality, functionality, and reliability. For example, different meeting rooms have different environments. Some meeting rooms are brighter, while others are darker. In order to clearly display meeting information and enable participants to clearly see the meeting content, it is necessary to select projection equipment with different projection brightness. Choosing the right projection equipment for users can enhance the user's experience in using the equipment.

[0003] However, there are still some problems with the existing conference projection equipment selection and management methods: users often choose projection equipment based on subjective judgment without data reference, and there is a problem that the final selected projection equipment does not match the actual needs. Different users have different needs for projection equipment. The existing technology cannot analyze user demand data through big data and match users with suitable projection equipment to improve the convenience of using projection equipment in meetings of different users; secondly, different users focus on different performance when choosing projection equipment, and there may be more than one projection equipment performance that they focus on, and the stability of these performances also needs to be considered. The existing technology cannot take into account the stability of equipment performance when selecting projection equipment for users so as to better select more suitable projection equipment for users.

[0004] Therefore, people need a conference projection management system and method based on big data to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a conference projection management system and method based on big data to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a conference projection management system based on big data, the system comprising: a projection data acquisition module, a database, a data analysis module, a projection device matching module and a conference projection selection management module;

[0007] The output end of the projection data acquisition module is connected to the input end of the database, the output end of the database is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the projection device matching module, and the output end of the projection device matching module is connected to the input end of the conference projection selection management module;

[0008] The projection data acquisition module is used to collect user demand data for the projection device and performance data of the projection device, and transmit all the collected data to the database;

[0009] The database is used to store all collected data;

[0010] The data analysis module is used to compare and analyze the user's demand data for the projection device and the performance data of the projection device;

[0011] The projection device matching module is used to analyze the matching degree between different projection devices and user needs;

[0012] The conference projection selection management module is used to select and match projection equipment for users.

[0013] Further, the projection data acquisition module includes a demand data acquisition unit and a device parameter acquisition unit;

[0014] The output ends of the demand data acquisition unit and the equipment parameter acquisition unit are connected to the input end of the database;

[0015] The demand data collection unit is used to collect demand index data for different performances of conference room projection equipment proposed by different users;

[0016] The device parameter acquisition unit is used to acquire index data of different performances possessed by different projection devices.

[0017] Furthermore, the data analysis module includes a data comparison unit and a key indicator screening unit;

[0018] The input end of the data comparison unit is connected to the output end of the database, and the output end of the data comparison unit is connected to the input end of the key indicator screening unit;

[0019] The data comparison unit is used to compare the user's demand index data and the performance index data of the projection device, and analyze the difference between the user's demand index for different performances of the projection device and the corresponding performance index;

[0020] The key indicator screening unit is used to retrieve user demand data, screen out key performance data of projection devices that different users value, and retrieve key performance indicator data of different projection devices.

[0021] Furthermore, the projection device matching module includes a key indicator analysis unit and a matching degree analysis unit;

[0022] The input end of the key indicator analysis unit is connected to the output end of the key indicator screening unit, and the output end of the key indicator analysis unit is connected to the input end of the matching degree analysis unit;

[0023] The key indicator analysis unit is used to normalize the key performance indicators of the same projection device and analyze the stability of the key performance indicators of the projection device;

[0024] The matching degree analysis unit is used to analyze the matching degree between the user demand and the projection device according to the difference degree and the stability degree.

[0025] Further, the conference projection selection management module includes a projection device selection unit and a suggestion information transmission unit;

[0026] The input end of the projection device selection unit is connected to the output end of the matching degree analysis unit, and the output end of the projection device selection unit is connected to the input end of the suggestion information transmission unit;

[0027] The projection device selection unit is used to compare the matching degree between the user demand and different projection devices, and select the projection device with the highest matching degree;

[0028] The recommendation information transmission unit is used to transmit the performance information of the screened projection devices to the corresponding user terminal for reference.

[0029] A conference projection management method based on big data includes the following steps:

[0030] Z1: Collect user demand data for projection equipment and performance data of projection equipment;

[0031] Z2: Compare and analyze the user's demand data for projection equipment and the performance data of projection equipment;

[0032] Z3: Filter out the key performance data of projection equipment that users value;

[0033] Z4: Analyze the stability of key performance of projection equipment;

[0034] Z5: Select and match projection equipment for users.

[0035] Further, in step Z1: collect the demand index data for different performances of the conference room projection equipment proposed by the user, obtain a random user's demand index set for different performances of the projection equipment as R = {R1, R2, ..., Rn}, collect different performance index data of the projection equipment, filter out the projection equipment with performance indicators lower than the corresponding user demand indicators, obtain the performance index set corresponding to the remaining random projection equipment as S = {S1, S2, ..., Sn}, where n represents the number of performance indicators of the projection equipment, and collect the key performance data of the projection equipment that different users value;

[0036] During the data collection process, projection devices with a performance indicator lower than the user's required indicator are preferentially screened out, and projection devices that intuitively do not meet the user's required indicators are screened out. This is beneficial to reducing invalid data analysis when matching projection devices for users and speeding up the matching speed of projection equipment for conference rooms.

[0037] Further, in step Z2: the difference Wj between a random user's demand index for different performances of a projection device and a random projection device's corresponding performance index is calculated according to the following formula:

[0038]

[0039] Among them, Ri represents a random user's demand index for a random performance of a projection device, and Si represents a random performance index of the remaining random projection devices corresponding to the demand index;

[0040] The performance of the projection equipment meets the indicators required by the user, namely the demand indicators. The smaller the difference between the performance indicators of the projection equipment and the demand indicators, the smaller the degree of difference, that is, the performance indicators of the corresponding projection equipment are closer to the user's demand standards. Through big data collection and analysis of the user's demand indicator data and the performance indicator data of the projection equipment, the difference between the performance indicator and the demand indicator is summed up. The purpose is to judge the overall difference between the performance indicators of the projection equipment and the user's needs, provide more accurate reference data for the subsequent matching of users and projection equipment, and further improve the adaptability of the matched projection equipment and users.

[0041] Further, in step Z3: a total of m key performance indicators of a random projection device that a user cares about are screened out, and the key performance indicator set corresponding to the random projection device is S represents the performance indicator set corresponding to the remaining random projection device;

[0042] In step Z4: normalize the key performance indicators to obtain a set of key performance indicators X = {X1, X2, ..., X i , …, X m},in, s i Indicates a random key performance indicator of the corresponding projection device that users value, s min and max Respectively represent the minimum and maximum values ​​in the set s, and the stability of the key performance of the corresponding projection equipment Cj is analyzed according to the following formula:

[0043]

[0044] Among them, X i Represents a random key performance indicator after normalization;

[0045] Different users focus on different performance when selecting a projection device, and there may be more than one performance of the projection device that they focus on. In addition to the performance indicators needing to match the demand indicators, the indicators of the performance of the projection device that users focus on, that is, the key performance indicators, also need to be balanced and stable. On the basis that all the performance indicators of the projection device are closer to the user demand indicators, the smaller the difference between the key performance indicators, the more stable the key performance of the projection device is judged, and the projection device can better meet the user's needs;

[0046] Secondly, since different performance indicators of the projection device have different dimension units, directly analyzing the stability of the key performance, the performance indicators are not comparable. After normalizing the key performance indicators and then analyzing the stability, the original indicators are linearly transformed so that each indicator is at the same order of magnitude, which is beneficial to improving the comparability between the performance indicators and further improving the accuracy of the analysis results.

[0047] Furthermore, in step Z5: set the difference degree weight base as k and the stability degree weight base as 1 - k, where 0 < k < 1 and k > 1 - k. According to the formula Calculate the matching degree Fj of a randomly selected projection device and the corresponding user demand. By the same method, the set of matching degrees of the projection device and the corresponding user demand is obtained as F = {F1, F2,..., Fj,..., Fz}, where Wj ≠ 0, z represents the number of projection devices. Compare the matching degrees and screen out the projection device with the highest matching degree with the corresponding user demand, and transmit the performance information of the screened projection device to the corresponding user terminal for reference;

[0048] Analyze the matching degrees of different projection devices and user demands by combining the difference degrees between the user demand indicators for different performances of the projection device and the corresponding performance indicators of the projection device, and the stability degrees of the key performances of the projection device. The projection device selected based on the matching degree can meet two requirements: First, all the performance indicators of this projection device are overall closest to the user demand indicators; Second, the key performances that users attach importance to of this projection device can be more balanced and stable;

[0049] In addition, when calculating the matching degree between the projection equipment and the user's needs, the weight parameters of the degree of difference and the degree of stability are added. Compared with the stability of the key performance, it is judged that the user pays more attention to the fit between his own needs and the performance of the projection equipment. Therefore, the weight base of the degree of difference should be set larger than the weight base of the degree of stability. Secondly, since the number of key performances that users pay attention to is different, the more the number, the more performance requirements the user has for the projection equipment. A dynamic stability weight parameter is set, and the weight changes with the number of key performances required by the user. This is conducive to better selecting more suitable projection equipment for users and improving the convenience and experience of using projection equipment in different user meetings.

[0050] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0051] The present invention collects and analyzes the user's demand index data and the performance index data of the projection device through big data, sums the difference between the performance index and the demand index, judges the overall difference between the performance index of the projection device and the user's demand, and provides more accurate reference data for subsequent matching of users and projection devices, thereby further improving the adaptability of the matched projection device to the user; different users focus on different performance when selecting projection devices, and may focus on more than one performance of the projection device. In addition to the need to match the performance index with the demand index, selecting a projection device with stable key performance can make the screened projection device more in line with the user's demand, and after the key performance index is normalized, Re-analyzing the degree of stability improves the comparability between performance indicators and further improves the accuracy of the analysis results; combining the difference between the user's demand indicators for different performance of the projection equipment and the corresponding performance indicators of the projection equipment, as well as the stability of the key performance of the projection equipment, the matching degree between different projection equipment and user needs is analyzed to select suitable projection equipment for users. When calculating the matching degree between the projection equipment and user needs, weight parameters of the degree of difference and the degree of stability are added, and a dynamic stability weight parameter is set. The weight changes with the number of key performances required by the user, which is conducive to better selecting more suitable projection equipment for users and improving the convenience and experience of using projection equipment in meetings of different users. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 It is a structural diagram of a conference projection management system based on big data of the present invention;

[0054] Figure 2 It is a flow chart of a conference projection management method based on big data of the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0056] Combine the following Figure 1-Figure 2 The present invention is further described with reference to the accompanying drawings and specific embodiments.

[0057] Embodiment 1:

[0058] like Figure 1 As shown, this embodiment provides a conference projection management system based on big data, the system includes: a projection data acquisition module, a database, a data analysis module, a projection device matching module and a conference projection selection management module;

[0059] The output end of the projection data acquisition module is connected to the input end of the database, the output end of the database is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the projection device matching module, and the output end of the projection device matching module is connected to the input end of the conference projection selection management module;

[0060] The projection data acquisition module is used to collect the user's demand data for the projection equipment and the performance data of the projection equipment, and transmit all the collected data to the database;

[0061] The database is used to store all the collected data;

[0062] The data analysis module is used to compare and analyze the user's demand data for the projection equipment and the performance data of the projection equipment;

[0063] The projection equipment matching module is used to analyze the matching degree between different projection equipment and user needs;

[0064] The conference projection selection management module is used to select and match projection equipment for users;

[0065] The performance data indicates various performance parameters of the projection device, including the horizontal resolution, horizontal scanning frequency, output light energy and video bandwidth of the projection device.

[0066] The projection data acquisition module includes a demand data acquisition unit and an equipment parameter acquisition unit;

[0067] The output ends of the demand data acquisition unit and the equipment parameter acquisition unit are connected to the input end of the database;

[0068] The demand data collection unit is used to collect demand index data for different performances of conference room projection equipment proposed by different users;

[0069] The device parameter acquisition unit is used to collect index data of different performances of different projection devices.

[0070] The data analysis module includes a data comparison unit and a key indicator screening unit;

[0071] The input end of the data comparison unit is connected to the output end of the database, and the output end of the data comparison unit is connected to the input end of the key indicator screening unit;

[0072] The data comparison unit is used to compare the user's demand index data and the projection device's performance index data, and analyze the difference between the user's demand index for different performances of the projection device and the corresponding performance index;

[0073] The key indicator screening unit is used to retrieve user demand data, screen out key performance data of projection equipment that different users value, and retrieve key performance indicator data of different projection equipment.

[0074] The projection equipment matching module includes a key indicator analysis unit and a matching degree analysis unit;

[0075] The input end of the key indicator analysis unit is connected to the output end of the key indicator screening unit, and the output end of the key indicator analysis unit is connected to the input end of the matching degree analysis unit;

[0076] The key indicator analysis unit is used to normalize the key performance indicators of the same projection equipment and analyze the stability of the key performance indicators of the projection equipment;

[0077] The matching degree analysis unit is used to analyze the matching degree between the user demand and the projection device according to the difference degree and the stability degree.

[0078] The conference projection selection management module includes a projection device selection unit and a suggestion information transmission unit;

[0079] The input end of the projection device selection unit is connected to the output end of the matching degree analysis unit, and the output end of the projection device selection unit is connected to the input end of the suggestion information transmission unit;

[0080] The projection device selection unit is used to compare the matching degree between the user demand and different projection devices, and select the projection device with the highest matching degree;

[0081] It is suggested that the information transmission unit is used to transmit the performance information of the screened projection devices to the corresponding user terminal for reference.

[0082] Embodiment 2:

[0083] like Figure 2 As shown, this embodiment provides a conference projection management method based on big data, which is implemented based on the management system in the embodiment and specifically includes the following steps:

[0084] Z1: Collect user demand data and performance data of projection equipment, collect demand index data of different performance of projection equipment for conference rooms proposed by users, obtain a random user's demand index set of different performance of projection equipment as R = {R1, R2, ..., Rn}, collect different performance index data of projection equipment, filter out projection equipment with performance index lower than the corresponding user demand index, obtain the performance index set corresponding to the remaining random projection equipment as S = {S1, S2, ..., Sn}, where n represents the number of performance indexes of the projection equipment, and collect key performance data of projection equipment that different users value;

[0085] For example, the required indicators of a random user for the horizontal resolution, horizontal scanning frequency, output light energy and video bandwidth of the projection device are obtained as R1=768; R2=70; R3=1800; R4=46, and the performance indicator set corresponding to the remaining random projection device is obtained as S={S1, S2, S3, S4}={1024, 80, 1900, 50};

[0086] Z2: Compare and analyze the user's demand data for projection equipment and the performance data of projection equipment, according to the formula Calculate the difference Wj between a random user's demand index for different performances of a projection device and a random projection device's corresponding performance index, where Ri represents a random user's demand index for a random performance of a projection device, and Si represents a random performance index corresponding to the remaining random projection device and the demand index;

[0087] For example, the difference between a random user's demand index for the above three performances of the projection device and a random projection device's corresponding performance index Wj=370 is calculated;

[0088] Z3: Filter out the key performance data of the projection equipment that the user cares about. There are m key performance indicators of a random projection equipment that the user cares about. The key performance indicator set corresponding to the random projection equipment is s = {s1, s2, ..., s m}, S represents the performance indicator set corresponding to the remaining random projection device;

[0089] For example, there are m=3 key performance indicators of projection equipment that users value, namely horizontal resolution, output light energy and video bandwidth. The key performance indicator set corresponding to a random projection equipment is s={s1, s2, s3}={1024, 1900, 50};

[0090] Z4: Analyze the stability of the key performance of the projection device, perform normalization processing on the key performance indicators, and obtain the set of processed key performance indicators as X = {X1, X2, X3} = {0.53, 1, 0}, where, s i represents any one of the key performance indicators that users attach importance to and that the corresponding projection device has. s min and s max represent the minimum value and the maximum value in the set s respectively. According to the formula analyze the stability of the key performance of the corresponding projection device Cj≈2.45, where X i represents any one of the key performance indicators after normalization processing;

[0091] Z5: Select and match a projection device for the user. Set the weight base of the difference degree as k = 0.6, and the weight base of the stability degree as 1 - k = 0.4, where 0 < k < 1 and k > 1 - k. According to the formula calculate the matching degree Fj≈0.74 of any one projection device and the corresponding user requirements. By the same method, obtain the set of matching degrees of the projection devices and the corresponding user requirements as F = {F1, F2, F3} = {0.75, 0.56, 0.49}, where Wj≠0, z represents the number of projection devices. Compare the matching degrees and screen out the projection device with the highest matching degree with the corresponding user requirements: the projection device corresponding to F1. Transmit the performance information of the projection device corresponding to F1 to the corresponding user terminal for reference.

[0092] Finally, it should be noted that the above are only preferred examples of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A conference projection management system based on big data, characterized by: The system includes: a projection data acquisition module, a database, a data analysis module, a projection device matching module and a conference projection selection management module; The output end of the projection data acquisition module is connected to the input end of the database, the output end of the database is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the projection device matching module, and the output end of the projection device matching module is connected to the input end of the conference projection selection management module; The projection data acquisition module is used to collect user demand data for the projection device and performance data of the projection device, and transmit all the collected data to the database; The database is used to store all collected data; The data analysis module is used to compare and analyze the user's demand data for the projection device and the performance data of the projection device; The projection device matching module is used to analyze the matching degree between different projection devices and user needs; The conference projection selection management module is used to select and match projection equipment for users; The data analysis module includes a data comparison unit and a key indicator screening unit; The input end of the data comparison unit is connected to the output end of the database, and the output end of the data comparison unit is connected to the input end of the key indicator screening unit; The data comparison unit is used to compare the user's demand index data and the performance index data of the projection device, and analyze the difference between the user's demand index for different performances of the projection device and the corresponding performance index; The key indicator screening unit is used to retrieve user demand data, screen out key performance data of projection devices that different users value, and retrieve key performance indicator data of different projection devices; The projection device matching module includes a key indicator analysis unit and a matching degree analysis unit; The input end of the key indicator analysis unit is connected to the output end of the key indicator screening unit, and the output end of the key indicator analysis unit is connected to the input end of the matching degree analysis unit; The key indicator analysis unit is used to normalize the key performance indicators of the same projection device and analyze the stability of the key performance indicators of the projection device; The matching degree analysis unit is used to analyze the matching degree between the user demand and the projection device according to the difference degree and the stability degree; Collect the demand index data of different performances of conference room projection equipment proposed by users, obtain a random user's demand index set of different performances of projection equipment as R = {R1, R2, ..., Rn}, collect different performance index data of projection equipment, filter out projection equipment with performance indicators lower than the corresponding user demand indicators, obtain the performance index set corresponding to the remaining random projection equipment as S = {S1, S2, ..., Sn}, where n represents the number of performance indicators of the projection equipment, and collect key performance data of projection equipment that different users value; The difference between a random user's demand index for different performance of a projection device and a random projection device's corresponding performance index Wj is calculated according to the following formula: Among them, Ri represents a random user's demand index for a random performance of a projection device, and Si represents a random performance index of the remaining random projection devices corresponding to the demand index; There are m key performance indicators of a random projection device that a user cares about. The key performance indicator set corresponding to a random projection device is s = {s1, s2, ..., s m }, S represents the performance indicator set corresponding to the remaining random projection device; The key performance indicators are normalized to obtain a set of key performance indicators X = {X1, X2, ..., X i , …, X m },in, s i Indicates a random key performance indicator of the corresponding projection device that users value, s min and max Respectively represent the minimum and maximum values ​​in the set s, and the stability of the key performance of the corresponding projection equipment Cj is analyzed according to the following formula: Among them, X i Represents a random key performance indicator after normalization; Set the difference degree weight base as k and the stability degree weight base as 1 - k, where 0 < k < 1 and k > 1 - k. According to the formula Calculate the matching degree Fj between a randomly selected projection device and the corresponding user requirements. By the same method, the set of matching degrees between projection devices and the corresponding user requirements is obtained as F = {F1, F2,..., Fj,..., Fz}, where Wj ≠ 0, z represents the number of projection devices. Compare the matching degrees and select the projection device with the highest matching degree with the corresponding user requirements. Transmit the performance information of the selected projection device to the corresponding user terminal for reference.

2. A conference projection management system based on big data according to claim 1, characterized in that: The projection data acquisition module includes a demand data acquisition unit and an equipment parameter acquisition unit; The output ends of the demand data acquisition unit and the equipment parameter acquisition unit are connected to the input end of the database; The demand data collection unit is used to collect demand index data for different performances of conference room projection equipment proposed by different users; The device parameter acquisition unit is used to acquire index data of different performances possessed by different projection devices.

3. According to the big data-based conference projection management system of claim 1, it is characterized by: The conference projection selection management module includes a projection device selection unit and a suggestion information transmission unit; The input end of the projection device selection unit is connected to the output end of the matching degree analysis unit, and the output end of the projection device selection unit is connected to the input end of the suggestion information transmission unit; The projection device selection unit is used to compare the matching degree between the user demand and different projection devices, and select the projection device with the highest matching degree; The recommendation information transmission unit is used to transmit the performance information of the screened projection devices to the corresponding user terminal for reference.

4. A conference projection management method based on big data, characterized by: The following steps are involved: Z1: Collect user demand data for projection equipment and performance data of projection equipment; Z2: Compare and analyze the user's demand data for projection equipment and the performance data of projection equipment; Z3: Filter out the key performance data of projection equipment that users value; Z4: Analyze the stability of key performance of projection equipment; Z5: Select and match projection equipment for users; In step Z1: collecting the demand index data of different performances of conference room projection equipment proposed by users, obtaining a random user's demand index set of different performances of projection equipment as R = {R1, R2, ..., Rn}, collecting different performance index data of projection equipment, filtering out projection equipment with performance indicators lower than the corresponding user demand indicators, obtaining the performance index set corresponding to the remaining random projection equipment as S = {S1, S2, ..., Sn}, where n represents the number of performance indicators of the projection equipment, and collecting key performance data of the projection equipment that different users value; In step Z2: the difference Wj between a random user's demand index for different performances of a projection device and a random projection device's corresponding performance index is calculated according to the following formula: Among them, Ri represents a random user's demand index for a random performance of a projection device, and Si represents a random performance index of the remaining random projection devices corresponding to the demand index; In step Z3: a total of m key performance indicators of a random projection device that a user cares about are screened out, and the key performance indicator set corresponding to the random projection device is s = {s1, s2, ..., s m }, S represents the performance indicator set corresponding to the remaining random projection device; In step Z4: normalize the key performance indicators to obtain a set of key performance indicators after normalization: X = {X1, X2, ..., X i , …, X m },in, s i Indicates a random key performance indicator of the corresponding projection device that users value, s min and max Respectively represent the minimum and maximum values ​​in the set s, and the stability of the key performance of the corresponding projection equipment Cj is analyzed according to the following formula: Among them, X i Represents a random key performance indicator after normalization; In step Z5: Set the weight base of the degree of difference as k and the weight base of the degree of stability as 1 - k, where 0 < k < 1 and k > 1 - k. According to the formula Calculate the matching degree Fj between a randomly selected projection device and the corresponding user requirements. By the same method, the set of matching degrees between the projection devices and the corresponding user requirements is obtained as F = {F1, F2,..., Fj,..., Fz}, where Wj ≠ 0, z represents the number of projection devices. Compare the matching degrees and select the projection device with the highest matching degree with the corresponding user requirements. Transmit the performance information of the selected projection device to the corresponding user terminal for reference.

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