Catering equipment management system and method based on data analysis

Abstract

The invention discloses a catering equipment management system and method based on data analysis, and belongs to the field of catering equipment management, and the system comprises a data collection module, a data storage and processing module, an equipment management module, a data analysis module, a remote upgrading module, a user management module, a platform service module, and a platform sharing application module. According to the invention, the data acquisition module acquires the operation data of the catering equipment in real time, and the equipment management module realizes remote monitoring through a universal remote controller, so that the workload of manual inspection is reduced, and managers can master the operation state of the equipment more conveniently. Based on the energy consumption efficiency index in the equipment performance evaluation algorithm, the system is promoted to pursue a more efficient energy use mode, the abnormal change of the equipment performance can be found in time, a reference is provided for equipment type selection and updating, and more energy-saving equipment with better performance can be selected, so that the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of catering equipment management, and particularly to a catering equipment management system and method based on data analysis. Background Art

[0002] With the continuous development of the catering industry and the advancement of the intelligentization trend, the types and quantities of catering equipment are increasing continuously. The traditional catering equipment management method relies on manual records and empirical judgments, and has problems such as low efficiency, difficulty in timely discovering faults, and untimely maintenance. At the same time, with the development of Internet of Things technology and the maturity of big data analysis means, it provides technical support for realizing the intelligent management and efficient operation of catering equipment.

[0003] Therefore, there is a need for a catering equipment management system based on data analysis, which uses advanced data analysis technology and Internet of Things means to improve the efficiency and reliability of catering equipment management, reduce costs, and improve service quality. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a catering equipment management system and method based on data analysis, which solves the problems put forward in the above background art.

[0005] Technical Solution: To solve the above technical problems, according to one aspect of the present invention, more specifically, a catering equipment management system based on data analysis includes a data acquisition module, a data storage and processing module, an equipment management module, a data analysis module, a remote upgrade module, a user management module, a platform service module, and a platform sharing application module. The data acquisition module real-time collects the operation data of catering equipment, including information such as temperature, pressure, current, voltage, energy consumption, and equipment status.

[0006] Data Storage and Processing Module: Establish a high-performance data storage system, adopt distributed database and data warehouse technologies to store a large amount of equipment operation data and historical records.

[0007] Use big data processing technology to clean, transform, and analyze the collected data, and extract valuable information and knowledge.

[0008] The equipment management module realizes equipment status monitoring, and real-time displays the operation status, parameter changes, and fault alarm information of the equipment; through the universal remote control, the management personnel can remotely monitor the operation status of various equipment in the restaurant, discover problems in time and take measures.

[0009] The data analysis module establishes an equipment performance evaluation model to evaluate the operation efficiency, reliability, and stability of the equipment, develops a fault prediction model to predict in advance the possible faults of the equipment, so as to take preventive measures in time, conducts energy consumption analysis, optimizes the operation parameters of the equipment, and reduces energy consumption.

[0010] The remote upgrade module pushes a new firmware version to the device through a secure communication channel to implement remote upgrade operations;

[0011] The user management module assigns different operation permissions and access scopes according to the roles and permissions of users, records the operation history of users and the usage of devices, and provides personalized services and suggestions for users;

[0012] The platform service module: provides comprehensive device management functions, including device access, status monitoring, fault alarm, and maintenance plan formulation.

[0013] Furthermore, the data acquisition module includes a temperature sensor, a pressure sensor, a current sensor, a voltage sensor, an energy consumption sensor, a device status sensor, a data acquisition card, a wireless sensor node, an intelligent meter, and a universal remote control for catering equipment, and real-time collects the operation data of catering equipment, including information such as temperature, pressure, current, voltage, energy consumption, and device status.

[0014] Furthermore, the temperature sensor: is used to measure the temperature of catering equipment, such as the surface temperature of a stove, the internal temperature of an oven, and the refrigeration and freezing temperatures of a refrigerator;

[0015] The pressure sensor: measures the pressure in catering equipment, such as the gas pressure of a stove, the steam pressure of a steam engine, and the water pressure of a beverage machine;

[0016] The current sensor: monitors the magnitude of the current in catering equipment, such as the operating current of devices such as refrigerators, ovens, and dishwashers;

[0017] The voltage sensor: detects the voltage value of catering equipment to ensure that the equipment operates within the normal voltage range;

[0018] The energy consumption sensor: measures the energy consumption of catering equipment, such as the consumption of electric energy, gas, and water; it is an electric energy meter, a gas meter, and a water meter;

[0019] The device status sensor: is used to detect the operating status of catering equipment, such as the on / off status, operating mode, and fault status of the equipment.

[0020] Furthermore, the device performance evaluation algorithm formula is expressed as:

[0021] Index calculation: Stove thermal efficiency index : , where represents the actual heat output of the stove, represents the gas input of the stove;

[0022] Refrigeration coefficient of refrigeration equipment : , where represents the refrigerating capacity, represents the power consumption of the refrigeration equipment;

[0023] Equipment energy consumption efficiency index : , where represents the amount of specific tasks completed by the equipment per unit time, represents the energy consumed by the equipment;

[0024] Calculation of performance evaluation score:

[0025] Suppose there are performance indicators, and the score of indicator is recorded as , and the weight is , then the equipment performance evaluation score .

[0026] According to another aspect of the present invention, more specifically, a catering equipment management method based on data analysis, including the catering equipment management system based on data analysis:

[0027] S1. Data collection and processing:

[0028] a. Regularly collect the operation data of catering equipment, and perform real-time processing and analysis on the data;

[0029] b. The data collection frequency can be adjusted according to the importance of the equipment and the speed of data change to ensure the timeliness and accuracy of the data;

[0030] c. Use data cleaning and conversion technologies to remove noise and abnormal data and improve the data quality;

[0031] S2. Equipment management and maintenance:

[0032] a. According to the equipment status monitoring and fault alarm information, perform equipment repair and maintenance in a timely manner;

[0033] b. Formulate an equipment maintenance plan, regularly inspect and maintain the equipment to ensure the normal operation of the equipment;

[0034] c. Utilize the data analysis results to optimize the operation parameters of the equipment and improve the performance and efficiency of the equipment;

[0035] S3. Data analysis and decision-making:

[0036] a. Use data analysis technologies to deeply analyze the equipment operation data and provide decision-making support for restaurant operations;

[0037] b. Establish a data analysis model to predict equipment failures and energy consumption change trends and take preventive measures in advance;

[0038] c. Adjust the equipment management strategy and operation mode according to the data analysis results to improve the economic benefits and competitiveness of the restaurant;

[0039] S4. Platform Services and Shared Applications:

[0040] a. Make full use of the platform service module to provide services such as equipment management, data analysis, remote upgrade, and user management;

[0041] b. Actively expand the platform shared applications to achieve functions such as cross-device linkage, open API interfaces, and ecological cooperation, and improve the intelligent level and application value of the system;

[0042] c. Continuously optimize the platform services and shared applications to meet the diverse needs of users and promote the intelligent upgrade and development of the catering industry.

[0043] The beneficial effects of the catering equipment management system and method based on data analysis of the present invention are as follows:

[0044] The present invention collects multi-dimensional equipment operation data in real time through the data acquisition module, and the equipment management module realizes remote monitoring through the universal remote control, reducing the workload of manual inspection and enabling managers to more conveniently master the equipment operation status.

[0045] The data analysis module conducts energy consumption analysis, optimizes the equipment operation parameters, improves the energy utilization efficiency, reduces the energy consumption cost, by adjusting the gas volume of the stove, the temperature setting of the refrigeration equipment, etc.; and based on the energy consumption efficiency index in the equipment performance evaluation algorithm, the system is urged to pursue a more efficient energy usage method. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The following further describes the present invention in detail with reference to the drawings and specific implementation methods.

[0047] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] The present invention will be described in detail below with reference to the drawings and embodiments. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0049] To make the technical solution of the present invention clearer, the following further describes the present invention in detail with reference to the drawings and specific embodiments.

[0050] Refer to Figure 1, A catering equipment management system based on data analysis, including a data acquisition module, a data storage and processing module, an equipment management module, a data analysis module, a remote upgrade module, a user management module, a platform service module, and a platform sharing application module, characterized in that: The data acquisition module collects the operation data of catering equipment in real time, including information such as temperature, pressure, current, voltage, energy consumption, and equipment status;

[0051] Data storage and processing module: Establish a high-performance data storage system, adopt distributed database and data warehouse technologies to store a large amount of equipment operation data and historical records;

[0052] Use big data processing technology to clean, transform, and analyze the collected data, and extract valuable information and knowledge;

[0053] The equipment management module realizes equipment status monitoring, and displays the operation status, parameter changes, and fault alarm information of the equipment in real time; Through the universal remote control, managers can remotely monitor the operation status of various equipment in the restaurant, discover problems in time and take measures;

[0054] Data analysis module, establish an equipment performance evaluation model to evaluate the operation efficiency, reliability, and stability of the equipment, develop a fault prediction model to predict possible equipment failures in advance, so as to take preventive measures in time, conduct energy consumption analysis, optimize the operation parameters of the equipment, and reduce energy consumption;

[0055] Remote upgrade module, through a secure communication channel, push new firmware versions to the equipment to achieve remote upgrade operations;

[0056] User management module, according to the roles and permissions of users, assign different operation permissions and access scopes, record the operation history and equipment usage of users, and provide personalized services and suggestions for users;

[0057] Platform service module: Provide comprehensive equipment management functions, including equipment access, status monitoring, fault alarm, and maintenance plan formulation.

[0058] The data acquisition module includes a temperature sensor, a pressure sensor, a current sensor, a voltage sensor, an energy consumption sensor, an equipment status sensor, a data acquisition card, a wireless sensor node, an intelligent meter, and a universal remote control for catering equipment, and collects the operation data of catering equipment in real time, including information such as temperature, pressure, current, voltage, energy consumption, and equipment status.

[0059] Temperature sensor: Used to measure the temperature of catering equipment, such as the surface temperature of the stove, the internal temperature of the oven, and the refrigeration and freezing temperatures of the refrigerator;

[0060] Pressure sensor: Measures the pressure in catering equipment, such as the gas pressure of a stove, the steam pressure of a steam engine, and the water pressure of a beverage machine;

[0061] Current sensor: Monitors the magnitude of the current in catering equipment, such as the operating current of equipment like refrigerators, ovens, and dishwashers;

[0062] Voltage sensor: Detects the voltage value of catering equipment to ensure that the equipment operates within the normal voltage range;

[0063] Energy consumption sensor: Measures the energy consumption of catering equipment, such as the consumption of electric energy, gas, and water; It is an electric energy meter, a gas meter, and a water meter;

[0064] Equipment status sensor: Used to detect the operating status of catering equipment, such as the on / off status, operating mode, and fault status of the equipment.

[0065] Expression of the equipment performance evaluation algorithm formula:

[0066] Index calculation: Stove thermal efficiency index : , where represents the actual heat output of the stove, represents the gas input of the stove;

[0067] Refrigeration coefficient of refrigeration equipment : , where represents the refrigerating capacity, represents the power consumption of the refrigeration equipment;

[0068] Equipment energy consumption efficiency index : , where represents the amount of specific tasks completed by the equipment per unit time, represents the energy consumed by the equipment;

[0069] Performance evaluation score calculation:

[0070] Suppose there are performance indicators, and the score of indicator is recorded as , and the weight is , then the equipment performance evaluation score .

[0071] For the calculation of the stove equipment thermal efficiency index, it can accurately reflect the energy utilization efficiency of the stove during use; By comparing the actual generated heat with the input gas volume, the working performance of the stove can be intuitively understood; If the thermal efficiency is low, it may mean serious gas waste and equipment maintenance or adjustment of the usage method is required.

[0072] The calculation of the coefficient of performance of refrigeration equipment helps to evaluate the performance of refrigeration equipment such as refrigerators. The higher the coefficient of performance, it indicates that under the condition of consuming the same amount of electricity, the refrigeration equipment can generate more cooling capacity, thereby improving the operating efficiency and energy-saving effect of the equipment.

[0073] The calculation of the equipment energy consumption efficiency index can measure the energy consumption of different equipment when completing specific tasks; more energy-efficient equipment can be selected according to the energy consumption efficiency, or the existing equipment can be optimized and adjusted to reduce the energy cost.

[0074] And it can assist in equipment fault diagnosis and maintenance decision-making

[0075] Continuously monitoring these indicators can timely detect abnormal changes in equipment performance; if the thermal efficiency of a stove suddenly drops, it may be a sign of burner blockage, gas supply problems or other faults; through the analysis of these indicators, the problem can be quickly located and corresponding maintenance measures can be taken to avoid the impact of equipment failures on the catering business.

[0076] For refrigeration equipment, if the coefficient of performance drops significantly, it may mean that there are faults in the refrigeration system, such as refrigerant leakage, compressor failure; timely detection of these problems can be repaired in advance to prevent food spoilage and loss.

[0077] Provide reference for equipment selection and update. When new equipment needs to be purchased or existing equipment needs to be updated, these indicators can be used as important reference bases; by comparing the thermal efficiency, coefficient of performance and energy consumption efficiency of different brands and models of equipment, equipment with better performance and higher energy efficiency can be selected to improve the economic benefits and sustainable development ability of the enterprise;

[0078] Refer to Figure 1 , a catering equipment management method based on data analysis, including a catering equipment management system based on data analysis:

[0079] S1. Data collection and processing:

[0080] a. Regularly collect the operation data of catering equipment, and perform real-time processing and analysis on the data;

[0081] b. The data collection frequency can be adjusted according to the importance of the equipment and the speed of data change to ensure the timeliness and accuracy of the data;

[0082] c. Use data cleaning and conversion technologies to remove noise and abnormal data and improve data quality;

[0083] S2. Equipment management and maintenance:

[0084] a. According to the equipment status monitoring and fault alarm information, carry out equipment repair and maintenance in a timely manner;

[0085] b. Formulate an equipment maintenance plan, regularly inspect and maintain the equipment to ensure its normal operation;

[0086] c. Utilize the data analysis results to optimize the operating parameters of the equipment and improve its performance and efficiency;

[0087] S3. Data Analysis and Decision-Making:

[0088] a. Apply data analysis techniques to deeply analyze the equipment operation data and provide decision-making support for the restaurant operation;

[0089] b. Establish a data analysis model to predict the trends of equipment failures and energy consumption changes, and take preventive measures in advance;

[0090] c. Adjust the equipment management strategy and operation mode according to the data analysis results to improve the economic benefits and competitiveness of the restaurant;

[0091] S4. Platform Services and Shared Applications:

[0092] a. Make full use of the platform service module to provide services such as equipment management, data analysis, remote upgrade, and user management;

[0093] b. Actively expand the platform shared applications to achieve functions such as cross-device linkage, open API interfaces, and ecological cooperation, and improve the intelligent level and application value of the system;

[0094] c. Continuously optimize the platform services and shared applications to meet the diverse needs of users and promote the intelligent upgrade and development of the catering industry.

[0095] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

Claims

1. A catering equipment management system based on data analysis, comprising a data acquisition module, a data storage and processing module, an equipment management module, a data analysis module, a remote upgrade module, a user management module, a platform service module, and a platform sharing application module, characterized in that: The data acquisition module collects the operation data of catering equipment in real time, including information such as temperature, pressure, current, voltage, energy consumption, and equipment status.

2. The food service equipment management system based on data analysis according to claim 1, wherein: Data storage and processing module: Establish a high-performance data storage system, adopt distributed database and data warehouse technologies to store a large amount of equipment operation data and historical records; Use big data processing technology to clean, transform, and analyze the collected data, and extract valuable information and knowledge.

3. The catering equipment management system based on data analysis according to claim 2, wherein: The equipment management module realizes equipment status monitoring, and displays the operation status, parameter changes, and fault alarm information of the equipment in real time; through the universal remote control, managers can remotely monitor the operation status of various equipment in the restaurant, discover problems in time and take measures.

4. The food and beverage equipment management system based on data analysis according to claim 3, characterized in that: The data analysis module establishes an equipment performance evaluation model to evaluate the operation efficiency, reliability, and stability of the equipment, develops a fault prediction model to predict possible equipment failures in advance, so as to take preventive measures in time, conducts energy consumption analysis, optimizes the operation parameters of the equipment, and reduces energy consumption; The remote upgrade module pushes new firmware versions to the equipment through a secure communication channel to achieve remote upgrade operations; The user management module assigns different operation permissions and access scopes according to the roles and permissions of users, records the operation history of users and the usage of equipment, and provides personalized services and suggestions for users; The platform service module: provides comprehensive equipment management functions, including equipment access, status monitoring, fault alarm, and maintenance plan formulation.

5. The food service equipment management system based on data analysis according to claim 4, wherein: The data acquisition module includes a temperature sensor, a pressure sensor, a current sensor, a voltage sensor, an energy consumption sensor, an equipment status sensor, a data acquisition card, a wireless sensor node, an intelligent meter, and a universal remote control for catering equipment, and collects the operation data of catering equipment in real time, including information such as temperature, pressure, current, voltage, energy consumption, and equipment status.

6. The catering equipment management system based on data analysis according to claim 5, characterized in that: Temperature sensor: used to measure the temperature of catering equipment, such as the surface temperature of the stove, the internal temperature of the oven, and the refrigeration and freezing temperatures of the refrigerator; Pressure sensor: measures the pressure in catering equipment, such as the gas pressure of the stove, the steam pressure of the steam engine, and the water pressure of the beverage machine; Current sensor: monitors the magnitude of the current of catering equipment, such as the operating current of equipment such as refrigerators, ovens, and dishwashers; Voltage sensor: detects the voltage value of catering equipment to ensure that the equipment operates within the normal voltage range; Energy consumption sensor: measures the energy consumption of catering equipment, such as the consumption of electric energy, gas, and water; for electric energy meters, gas meters, and water meters; Equipment status sensor: used to detect the operation status of catering equipment, such as the switch status, operation mode, and fault status of the equipment.

7. The food service equipment management system based on data analysis according to claim 6, wherein: The formula of the equipment performance evaluation algorithm is expressed as: Indicator calculation: Stove thermal efficiency indicator : , where represents the actual heat output of the stove, represents the gas input volume of the stove; Coefficient of performance of refrigeration equipment : , where represents the refrigerating capacity, represents the power consumption of the refrigeration equipment; Device energy consumption efficiency index : , where represents the specific task volume completed by the device per unit time, represents the energy consumed by the device; Calculation of performance evaluation score: Suppose there are performance indicators, and the score of indicator is recorded as , with a weight of . Then the device performance evaluation score .

8. A method for managing catering equipment based on data analysis, including the system for managing catering equipment based on data analysis described in claim 7, characterized in that: S1. Data acquisition and processing: a. Regularly collect the operation data of catering equipment, and perform real-time processing and analysis on the data; b. The data acquisition frequency can be adjusted according to the importance of the equipment and the speed of data change to ensure the timeliness and accuracy of the data; c. Apply data cleaning and transformation techniques to remove noise and abnormal data and improve data quality; S2. Equipment Management and Maintenance: a. Conduct equipment repair and maintenance in a timely manner based on equipment status monitoring and fault alarm information; b. Develop an equipment maintenance plan, regularly inspect and maintain the equipment to ensure its normal operation; c. Utilize the data analysis results to optimize the operating parameters of the equipment and improve its performance and efficiency; S3. Data Analysis and Decision Making: a. Apply data analysis techniques to deeply analyze the equipment operation data and provide decision-making support for restaurant operations; b. Establish a data analysis model to predict equipment faults and energy consumption change trends and take preventive measures in advance; c. Adjust the equipment management strategy and operation mode according to the data analysis results to improve the economic benefits and competitiveness of the restaurant; S4. Platform Services and Shared Applications: a. Make full use of the platform service module to provide services such as equipment management, data analysis, remote upgrade, and user management; b. Actively expand the platform shared applications to achieve functions such as cross-device linkage, open API interfaces, and ecological cooperation, and improve the intelligent level and application value of the system; c. Continuously optimize the platform services and shared applications to meet the diverse needs of users and promote the intelligent upgrade and development of the catering industry.

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