Intelligent laboratory management platform and control method thereof

Abstract

The invention relates to an intelligent laboratory management platform and a control method thereof, the intelligent laboratory management platform comprises a server and a management system, and the server is composed of a remote monitoring terminal and a database; the remote monitoring terminal is used for performing remote monitoring on the laboratory and performing video acquisition through a camera installed in the laboratory; the database is used for storing data generated by the laboratory management platform, reasonable storage algorithms are matched according to different structures of the data, and the data storage algorithms to be selected comprise sequential storage, link storage, index storage and hash storage. According to the method, data with different requirements are stored and processed by adopting different types of storage algorithms, different storage algorithms are applied according to data use requirements, data can be stored and called more quickly, the data can be updated in a low-delay manner in a laboratory management process, data changes of the laboratory can be monitored accurately at any time, and the laboratory management efficiency is improved. And the safety of the laboratory is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart laboratories, and in particular to a smart laboratory management platform and a control method thereof. Background Art

[0002] Smart laboratories are modern laboratories built using advanced technologies such as the Internet of Things, big data, cloud computing, artificial intelligence, and digital twins. They are innovative laboratories that are based on the idea of ​​distributed collaboration and centralized overall planning, use modern information technology, combine laboratory systems, experimental data, and Internet technology, and use cloud computing, the Internet of Things, artificial intelligence, and other technical means to achieve digitalization, automation, and intelligence in the laboratory experimental process.

[0003] For example, a smart laboratory management platform and its control method proposed in 202311694478.4, when the experimenter conducts an independent experiment, he must first pass a simulation experiment. After the simulation experiment, only the equipment used in the simulation experiment is opened. The experimenter simulates the selection of medicines, and can analyze whether the type and dosage of medicines meet the standards, and through prompts, the experimenter can quickly find the required medicines.

[0004] However, data redundancy may occur during the data storage process, resulting in slow data storage and call speed, which directly affects the operation speed of the laboratory management platform. When the data update lags behind, it will have a great impact and reduce the user experience. Therefore, a new smart laboratory management platform and its control method are proposed to solve the above problems. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a smart laboratory management platform and a control method thereof, which have the advantages of combining multiple data storage algorithms to improve storage call speed and enhance user experience, and solve the problem of data redundancy in the data storage process, resulting in slow data storage and call speed, which directly affects the operation speed of the laboratory management platform. When data updates lag behind, it will have a great impact and reduce the user experience.

[0006] To achieve the above object, the present invention provides the following technical solutions: a smart laboratory management platform, including a server and a management system, wherein the server consists of a remote monitoring terminal and a database;

[0007] The remote monitoring terminal is used to remotely monitor the laboratory and collect video through the camera installed in the laboratory;

[0008] The database is used to store the data generated by the laboratory management platform, and a reasonable storage algorithm is matched according to the different structures of the data. The data storage algorithm to be selected includes sequential storage, link storage, index storage and hash storage;

[0009] The management system includes a management terminal, an environmental anomaly monitoring module, a personnel access module, an electricity safety monitoring module, a consumables monitoring module and an Internet of Things gateway;

[0010] The management terminal manages the laboratory management platform through the web front end and the mobile terminal, and uses telephone alarm and SMS alarm to provide remote early warning;

[0011] The environmental anomaly monitoring module collects data from sensors in the laboratory through a data collector, and installs particle monitoring sensors, fire monitoring sensors, combustible gas monitoring sensors, temperature and humidity sensors, smoke detection sensors and infrared human body sensors in the laboratory;

[0012] The personnel access module is used to control the personnel entering the laboratory;

[0013] The power safety monitoring module is used to monitor the safety of electrical appliances in the laboratory;

[0014] The consumables monitoring module is used to monitor consumable materials in the laboratory;

[0015] The Internet of Things gateway is used to connect the management terminal to the server to achieve data input and output.

[0016] Preferably, the remote monitoring terminal is specifically four cameras installed inside the laboratory, namely camera No. 1 for monitoring the laboratory bench area, camera No. 2 for monitoring experimental consumables, camera No. 3 for monitoring people entering the laboratory, and camera No. 4 for monitoring the aisle.

[0017] Preferably, the database uses a mixture of sequential storage, linked storage, index storage and hash storage algorithms for data storage, wherein the sequential storage algorithm is suitable for data that requires fast access to large amounts of continuous data, the linked storage algorithm is suitable for data that requires frequent insertion and deletion operations, the index storage algorithm is suitable for data structures that require efficient retrieval, and the hash storage algorithm is suitable for data that requires fast search and update.

[0018] Preferably, the management terminal generates a management front end and a management APP through web front end compilation, feeds back the internal situation data of the laboratory to the user, and issues abnormal warnings through telephone alarms and SMS alarms after data abnormalities occur.

[0019] Preferably, the environmental anomaly monitoring module uses a 485 bus to connect the particle monitoring sensor, fire monitoring sensor, combustible gas monitoring sensor, temperature and humidity sensor, smoke detection sensor and infrared human body sensor to the data collector, and the data collector transmits the data to the database through the Internet of Things gateway. Each sensor is designed with a threshold value, and a warning signal is issued when the threshold value is reached.

[0020] Preferably, the personnel access module manages the incoming and outgoing personnel through the access control system, performs personnel access identification through the face recognition system, and performs intelligent scheduling of laboratory users through electronic shift signs.

[0021] Preferably, the electricity safety monitoring module monitors the electricity consumption of air switches, smart sockets and smart sockets inside the laboratory through an Internet of Things gateway, and sends out a warning signal when abnormal electricity consumption occurs.

[0022] Preferably, the consumables monitoring module stores data by means of data entry, enters the total amount of consumables entering the laboratory, and enters the usage amount after the consumables are used. The system automatically updates the consumables inventory and issues a warning signal when the consumables are insufficient.

[0023] A control method for a smart laboratory management platform, including the control method for the smart laboratory management platform, the control method is specifically as follows:

[0024] Step 1: Data Collection

[0025] The data generated by the environment anomaly monitoring module, personnel access module, power safety monitoring module and consumables monitoring module are collected through the Internet of Things gateway;

[0026] Step 2: Data processing

[0027] Convert the collected data into binary data for system recognition, and store the data in the database after classification;

[0028] Step 3: Data call

[0029] Transmit the data in the database to the management terminal, update the data in the management terminal, and display the data in the database on the web front end and mobile terminal for laboratory managers to supervise;

[0030] Step 4: Abnormal warning

[0031] When the collected data reaches the preset threshold, an alarm signal will be issued, which will be directly responded to the laboratory manager by phone call and text message.

[0032] Compared with the prior art, the technical solution of this application has the following beneficial effects:

[0033] 1. In the data storage stage, the present invention classifies the data collected by the Internet of Things gateway through sequential storage, link storage, index storage and hash storage algorithms, and uses different types of storage algorithms to store and process data with different requirements. Different storage algorithms are applied according to data usage requirements, which can store and call data more quickly. In the process of managing the laboratory, data can be updated with low latency, and the data changes in the laboratory can be accurately monitored at all times, further improving the safety of the laboratory.

[0034] 2. The present invention conducts real-time monitoring of the laboratory's environmental conditions, on-site images, electricity safety, consumables usage, and personnel entry and exit during laboratory management to ensure that the laboratory is always in the best experimental state. When abnormal situations occur, remote warnings are issued in a timely manner to remind laboratory managers to take emergency measures, ensure the safety of the laboratory, and ensure the smooth progress of the experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a schematic diagram of the structure of a smart laboratory management platform of the present invention;

[0036] Figure 2 This is a flow chart of a control method of a smart laboratory management platform of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1

[0039] See also Figure 1 ,A smart laboratory management platform in this embodiment includes a server and a management system, wherein the server consists of a remote monitoring terminal and a database;

[0040] The remote monitoring terminal is used to remotely monitor the laboratory and collect video through the cameras installed in the laboratory;

[0041] The database is used to store the data generated by the laboratory management platform. A reasonable storage algorithm is matched according to the different structures of the data. The data storage algorithms to be selected include sequential storage, link storage, index storage and hash storage.

[0042] The management system includes a management terminal, an environmental anomaly monitoring module, a personnel access module, an electricity safety monitoring module, a consumables monitoring module and an IoT gateway;

[0043] The management terminal manages the laboratory management platform through the web front end and mobile terminal, and uses telephone alarm and SMS alarm to provide remote early warning;

[0044] The environmental anomaly monitoring module collects data from sensors in the laboratory through a data collector, and installs particle monitoring sensors, fire monitoring sensors, combustible gas monitoring sensors, temperature and humidity sensors, smoke detection sensors, and infrared human body sensors in the laboratory;

[0045] The personnel access module is used to control the personnel entering the laboratory;

[0046] The power safety monitoring module is used to monitor the safety of electrical appliances in the laboratory;

[0047] The consumables monitoring module is used to monitor consumable materials in the laboratory;

[0048] The IoT gateway is used to connect the management terminal to the server to achieve data input and output.

[0049] In this embodiment, four cameras are designed inside the laboratory to monitor the laboratory bench area, laboratory consumables, personnel entering the laboratory, and aisles respectively. The staff can monitor or retrieve the images captured by the cameras through the management terminal.

[0050] In this embodiment, the database uses a combination of sequential storage, linked storage, index storage and hash storage algorithms for data storage, wherein the sequential storage algorithm is suitable for data that requires fast access to a large amount of continuous data, sequential storage is to store logically adjacent data elements in storage units that are also physically adjacent, and the logical relationship between nodes is reflected by the adjacency relationship of the storage units, the linked storage algorithm is suitable for data that requires frequent insertion and deletion operations, linked storage does not require logically adjacent nodes to be physically adjacent, and the logical relationship between nodes is represented by an additional pointer field, the index storage algorithm is suitable for data structures that require efficient retrieval, and in addition to storing node information, the index storage also establishes an additional index table. The index table consists of several index items, and each node has an index item in the index table, the hash storage algorithm is suitable for data that requires fast search and update, and the hash storage directly calculates the storage address of the node through the hash function using the keyword, and is suitable for the situation of fast retrieval of data through the keyword.

[0051] In this embodiment, the management terminal generates a management front end and a management APP through web front end compilation, feeds back the internal situation data of the laboratory to the user, and issues abnormal warnings through telephone alarms and SMS alarms when data abnormalities occur.

[0052] In this embodiment, the particle monitoring sensor, fire monitoring sensor, combustible gas monitoring sensor, temperature and humidity sensor, smoke detection sensor and infrared human body sensor are connected to the data collector through the 485 bus for data collection. The particle monitoring sensor monitors the dust content inside the laboratory, and its threshold value is ≤10mg / m 3 The fire monitoring sensor sends out an alarm signal after smoke appears in the laboratory. The smoke concentration threshold is 0.01% to 0.03%. The combustible gas monitoring sensor monitors the gas inside the laboratory and issues an early warning when the combustible gas concentration is too high. The temperature and humidity sensor monitors the temperature and humidity of the laboratory. The smoke detection sensor monitors the smoke concentration in the laboratory and issues an early warning when there is a lot of smoke in the center of the experiment. The infrared human body sensor performs infrared identification on people entering the laboratory.

[0053] In this embodiment, the personnel access module manages the coming and going of personnel through the access control system, performs personnel access identification through the face recognition system, and performs intelligent scheduling of laboratory users through electronic shift signs. The electricity safety monitoring module monitors the electricity consumption of air switches, smart strips and smart sockets inside the laboratory through the Internet of Things gateway, and issues a warning signal after abnormal electricity consumption occurs. The consumables monitoring module stores data through data entry, enters the total amount of consumables entering the laboratory, and enters the usage amount after the consumables are used. The system automatically updates the inventory of consumables and issues a warning signal when the consumables are insufficient.

[0054] Embodiment 2

[0055] See also Figure 2 , a control method of a smart laboratory management platform, including a control method of a smart laboratory management platform, the control method is as follows:

[0056] Step 1: Data Collection

[0057] The data generated by the environment anomaly monitoring module, personnel access module, power safety monitoring module and consumables monitoring module are collected through the Internet of Things gateway;

[0058] Step 2: Data processing

[0059] Convert the collected data into binary data for system recognition, and store the data in the database after classification;

[0060] Step 3: Data call

[0061] Transmit the data in the database to the management terminal, update the data in the management terminal, and display the data in the database on the web front end and mobile terminal for laboratory managers to supervise;

[0062] Step 4: Abnormal warning

[0063] When the collected data reaches the preset threshold, an alarm signal will be issued, which will be directly responded to the laboratory manager by phone call and text message.

[0064] By adopting the above technical scheme, the present invention, in the data storage stage, stores the data collected by the Internet of Things gateway by sequential storage, link storage, index storage and hash storage algorithms, stores and processes data with different requirements by using different types of storage algorithms, and applies different storage algorithms according to data usage requirements, which can store and call data more quickly, update data with low latency in the process of managing the laboratory, and accurately monitor the data changes in the laboratory at all times, further improving the safety of the laboratory. In the process of laboratory management, the laboratory's environmental conditions, on-site images, electricity safety, consumables usage and personnel access are monitored in real time to ensure that the laboratory is always in the best experimental state, and remote warning is carried out in time when abnormal conditions occur, reminding laboratory managers to carry out emergency treatment, ensuring the safety of the laboratory, ensuring the smooth progress of the experiment, and solving the problem of data redundancy in the data storage process, resulting in slow data storage and call speed, which directly affects the running speed of the laboratory management platform, and will cause great impact when data updates lag behind, and reduce the user experience.

[0065] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0066] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart laboratory management platform, including a server and a management system, characterized in that: The server consists of a remote monitoring terminal and a database; The remote monitoring terminal is used to remotely monitor the laboratory and collect video through the camera installed in the laboratory; The database is used to store the data generated by the laboratory management platform, and a reasonable storage algorithm is matched according to the different structures of the data. The data storage algorithm to be selected includes sequential storage, link storage, index storage and hash storage; The management system includes a management terminal, an environmental anomaly monitoring module, a personnel access module, an electricity safety monitoring module, a consumables monitoring module and an Internet of Things gateway; The management terminal manages the laboratory management platform through the web front end and the mobile terminal, and uses telephone alarm and SMS alarm to provide remote early warning; The environmental anomaly monitoring module collects data from sensors in the laboratory through a data collector, and installs particle monitoring sensors, fire monitoring sensors, combustible gas monitoring sensors, temperature and humidity sensors, smoke detection sensors and infrared human body sensors in the laboratory; The personnel access module is used to control the personnel entering the laboratory; The power safety monitoring module is used to monitor the safety of electrical appliances in the laboratory; The consumables monitoring module is used to monitor consumable materials in the laboratory; The Internet of Things gateway is used to connect the management terminal to the server to achieve data input and output.

2. The intelligent laboratory management platform according to claim 1, characterized in that: The remote monitoring terminal is specifically four cameras installed inside the laboratory, namely camera No. 1 for monitoring the laboratory bench area, camera No. 2 for monitoring experimental consumables, camera No. 3 for monitoring people entering the laboratory, and camera No. 4 for monitoring the aisle.

3. The intelligent laboratory management platform according to claim 1, characterized in that: The database uses a mixture of sequential storage, linked storage, index storage and hash storage algorithms for data storage, wherein the sequential storage algorithm is suitable for fast access to a large amount of continuous data, the linked storage algorithm is suitable for data that requires frequent insertion and deletion operations, the index storage algorithm is suitable for data structures that require efficient retrieval, and the hash storage algorithm is suitable for data that requires fast search and update.

4. The intelligent laboratory management platform according to claim 1, characterized in that: The management terminal generates a management front end and a management APP through web front end compilation, feeds back the internal laboratory situation data to the user, and issues abnormal warnings through telephone alarms and SMS alarms when data abnormalities occur.

5. The smart laboratory management platform according to claim 1, characterized in that: The environmental anomaly monitoring module uses a 485 bus to connect the particle monitoring sensor, fire monitoring sensor, combustible gas monitoring sensor, temperature and humidity sensor, smoke detection sensor and infrared human body sensor to the data collector. The data collector transmits data to the database through the Internet of Things gateway. Each sensor is designed with a threshold value, and a warning signal is issued when the threshold is reached.

6. The intelligent laboratory management platform according to claim 1, characterized in that: The personnel access module manages the incoming and outgoing personnel through the access control system, performs personnel access identification through the face recognition system, and performs intelligent scheduling of laboratory users through electronic shift signs.

7. The intelligent laboratory management platform according to claim 1, characterized in that: The electricity safety monitoring module monitors the power consumption of air switches, smart sockets and smart sockets inside the laboratory through the Internet of Things gateway, and sends out early warning signals when abnormal power consumption occurs.

8. The smart laboratory management platform according to claim 1, characterized in that: The consumables monitoring module stores data by means of data entry, enters the total amount of consumables entering the laboratory, and enters the usage amount after the consumables are used. The system automatically updates the inventory of consumables and issues a warning signal when the consumables are insufficient.

9. A control method for a smart laboratory management platform, comprising the control method for a smart laboratory management platform according to any one of claims 1 to 8, characterized in that: The control method is specifically as follows: Step 1: Data Collection The data generated by the environment anomaly monitoring module, personnel access module, power safety monitoring module and consumables monitoring module are collected through the Internet of Things gateway; Step 2: Data processing Convert the collected data into binary data for system recognition, and store the data in the database after classification; Step 3: Data call Transmit the data in the database to the management terminal, update the data in the management terminal, and display the data in the database on the web front end and mobile terminal for laboratory managers to supervise; Step 4: Abnormal warning When the collected data reaches the preset threshold, an alarm signal will be issued, which will be directly responded to the laboratory manager by phone call and text message.

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