Intelligent warehouse dividing and adjusting system and method based on big data
Through the intelligent warehouse division and warehousing adjustment system based on big data, and the automatic adjustment of the prison room, the problems of cumbersome and errors in the prison center are solved, the fairness and safety of the prison room are realized, and the overall efficiency and Corruption risk management.
Patent Information
- Application Number
- CN202411033650.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-30
- Publication Date
- 2024-12-10
AI Technical Summary
The adjustment of the existing prison rooms mainly relies on manual labor, which has problems such as cumbersome manual entry, easy to cause work errors, inability to consider capacity and risk factors in a coordinated manner, and leaving hidden dangers of corruption.
Design an intelligent warehouse division and warehousing system based on big data. Through database units, screening units, front warehouse division units, warehouse division units and warehousing units, combined with screening calculation model and case exclusion module, the detainees can be realized. Automatic allocation and allocation to ensure that the proportion of prisons meets the requirements, avoiding the allocation of co-camps to the same prison room, and performing permission grading and data backup through the login unit.
It improves the efficiency of warehouse division and placing adjustment in the prison, avoids manual mistakes and corruption risks, ensures that each allocation is fair and reasonable, and enhances the security of the system and data accuracy.
Smart Images
Figure CN119106840A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of big data warehouse division and adjustment, and in particular to an intelligent warehouse division and adjustment system and method based on big data. Background Art
[0002] Cell allocation is an important task in the daily management of prisons. With the advancement of the litigation process and the need for security management, prisons need to make timely adjustments to the cells of detainees, including separation and transfer of cells. Reasonable allocation and adjustment of cells can avoid security loopholes and potential risks that should not occur.
[0003] At present, prisons mainly rely on manual work to adjust cell rooms.
[0004] However, there are many disadvantages in manual cell adjustment: first, manual data entry is cumbersome, time-consuming and occupies police force; second, manual allocation of cells is prone to work errors, such as mistakenly assigning people involved in the same case to the same cell, resulting in tip-offs; third, manual allocation of cells cannot take into account risk factors such as capacity, case, place of origin, age, etc., resulting in uneven personnel distribution, which leads to cells being overcrowded, understaffed, safe and stable, or having great safety risks; fourth, human decision-making in cell allocation provides space for taking care of prisoners with personal connections and relationships, leaving hidden risks of corruption. Summary of the invention
[0005] The purpose of the present invention is to provide an intelligent warehouse division and adjustment system and method based on big data to solve the problems raised in the above background technology.
[0006] The purpose of the present invention can be achieved through the following technical solutions:
[0007] An intelligent warehouse division and adjustment system based on big data includes: a database unit: establishing a database on detainees, wherein the database information includes: identity information of detainees, case category, and prison number; an input unit: establishing a database on detainees to be detained, wherein the database information includes: identity information of detainees to be detained, case category, and the detainees to be detained are divided into immediate detainees and detainees to be confirmed; a screening unit: establishing a screening calculation model based on the prison's requirements for the proportion of eight major violent cases, theft cases, sensitive cases, the number of seriously ill patients, the number of people over 60 years old, and the number of people with the same place of origin, so that in the process of warehouse division and adjustment, the actual proportion of the prison is always kept below the prescribed proportion requirement; a pre-warehouse division unit: randomly assigning the detainees to be confirmed who have been entered by the input unit to the prison after passing through the screening unit in the order of entry time, reserving prison beds for the detainees to be detained, and A retention period is set according to the judicial procedure time required for the detainee and the saturation level of all prisons. If the retention period is exceeded, the pre-placement of the detainee will be invalid. If the detainee enters the prison normally within the retention period, the identity information, case category, and prison number of the detainee to be confirmed will be synchronized to the database unit; Division unit: the immediate detainees entered by the input unit will be randomly assigned to prisons in the order of entry time after passing through the screening unit, and the identity information, case category, and prison number of the immediate detainees will be synchronized to the database unit; Transfer unit: the detainees who need to be transferred will be randomly assigned to prisons other than the original prison after passing through the screening unit in the order of time when they leave the original prison, and the identity information, case category, and prison number of the detainee will be synchronized to the database unit; Login unit: three login categories are set up, including: entry and transfer login, database access query login, and administrator login.
[0008] Preferably, the identity information includes: name, gender, ID number, place of origin, address, health status, and the case categories include: eight major violent cases, theft cases, and sensitive cases.
[0009] Preferably, the screening calculation model is: y is not greater than Y, where n is the number of inmates in the prison who meet one of the eight characteristics of violent cases, theft cases, sensitive cases, seriously ill patients, over 60 years old, and the same place of origin; N is the number of all inmates in the prison, including those who are waiting to be confirmed and detained within the retention period; Y is the required proportion of the prison; and y is the actual proportion of the prison.
[0010] Preferably, the screening unit further includes a same case exclusion module, and the same case exclusion module includes the following algorithm steps:
[0011] The first step is that when entering the identity information and case category of the detainees, the entry unit will automatically number the case category; the second step is that when pre-separating and dividing the detainees into different cells, the screening unit will exclude the cells where the detainees with the same case category number are already located; the third step is that when transferring the detainees into different cells, the screening unit will exclude the cells where the detainees with the same case category number are already located.
[0012] Preferably, the authority of the person who logs in for recording, dividing and adjusting includes: entering the identity information and case category of the detained persons, running the pre-dividing warehouse unit, running the dividing warehouse unit, and running the adjusting warehouse unit. The person who logs in for recording, dividing and adjusting has no authority to know the prison to which the detained persons are randomly assigned after passing through the pre-dividing warehouse unit and the dividing warehouse unit, and the person who logs in for recording, dividing and adjusting has no authority to know the prison to which the detained persons are randomly assigned after passing through the adjusting warehouse unit.
[0013] Preferably, the permissions of the person who logs in to access and query the database include: querying the information and the prison where the detainees are and the prisoners are located, directly contacting and managing the detainees and the prisoners, and feeding back information entry errors to the person who logs in to make corrections. Each query and feedback of entry errors by the person who accesses and queries the database is backed up with a timestamp and information summary in this system.
[0014] Preferably, the permissions of the person logged in as the administrator include: modifying the specified ratio in the screening unit, modifying the retention period in the pre-storage unit, and viewing the timestamp and information summary backed up in the system by the person accessing the database and querying the login.
[0015] A method for using an intelligent warehouse division and adjustment system based on big data comprises the following steps: a first step, a person who logs in for recording, dividing and adjusting logs in to the system, enters the identity information and case category of a person to be detained and runs a front warehouse division unit, a warehouse division unit or directly runs a warehouse adjustment unit for a person in custody; a second step, a person who logs in for database access and query logs in to the system to obtain information on a person to be detained or a person in custody and the prison where the person is located; a third step, if the person who logs in for database access and query finds that there are errors in the entry of the identity information and case category of a person to be detained, the person can feedback to the person who logs in for recording, dividing and adjusting for modification; a fourth step, the person who logs in as an administrator can modify the prescribed proportion in the screening unit and the retention period in the front warehouse division unit according to the authority scale of the prison or new regulations, and can view the timestamp and information summary backed up in the system by the person who logs in for database access and query for supervision and tracing.
[0016] Beneficial effects of the present invention:
[0017] 1. Through the setting of database unit, screening unit, pre-dividing warehouse unit, dividing warehouse unit and adjusting warehouse unit, the tedious manual data entry is avoided, the data entry efficiency is improved, and the mistakes caused by manual allocation are avoided, so that each prison is used in a standardized manner. The random allocation of the system avoids the hidden risks of corruption, making each allocation fair and reasonable, which greatly improves the efficiency of dividing and adjusting warehouses in prisons.
[0018] 2. Through the setting of the same case exclusion module, people involved in the same case will not be assigned to the same prison. It is automatically applied when the screening unit is running. Compared with manual screening, the efficiency has been greatly improved.
[0019] 3. Through the setting of the login unit, the control and use authority of this system is graded. The personnel who log in for recording and adjusting are unaware of the prison to which the detainees or detainees are assigned, which reduces their corruption risk. The timestamps and information summaries backed up in the system by the personnel who log in for database access and query can not only check the errors in the database unit and improve the accuracy of the data, but also leave traces to provide clues for possible subsequent accountability, thereby improving the security of this system. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] The present invention will be further described below in conjunction with the accompanying drawings.
[0021] Figure 1 It is a system block diagram of the present invention.
[0022] Figure 2 It is a system block diagram of the screening unit in the present invention.
[0023] Figure 3 It is a schematic diagram of the steps of using the system of the present invention. DETAILED DESCRIPTION
[0024] 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.
[0025] Reference Figure 1-3As shown, the present invention is an intelligent warehouse division and adjustment system based on big data, including: a database unit: establishing a database about detainees, the database information includes: identity information of detainees, case category, and prison number; an input unit: establishing a database about detainees, the database information includes: identity information of detainees, case category, and detainees are divided into immediate detainees and detainees to be confirmed; a screening unit: based on the prison's requirements for the proportion of eight major violent cases, theft cases, sensitive cases, the number of seriously ill patients, the number of people over 60 years old, and the number of people with the same place of origin, a screening calculation model is established, and in the process of warehouse division and adjustment, the actual proportion of the prison is always kept below the prescribed proportion requirement; a pre-warehouse division unit: after the detainees to be confirmed who have been entered by the entry unit pass through the screening unit in the order of entry time, they are randomly assigned to the prison, and a prison bed is reserved for the detainee to be confirmed, which can be based on A retention period is set according to the judicial procedure time required for the detainee and the saturation level of all prisons. If the retention period is exceeded, the pre-placement of the detainee will be invalid. If the detainee enters the prison normally within the retention period, the identity information, case category, and prison number of the detainee to be confirmed will be synchronized to the database unit; Division unit: the immediate detainees entered by the input unit will be randomly assigned to a prison after passing through the screening unit in the order of entry time, and the identity information, case category, and prison number of the immediate detainees will be synchronized to the database unit; Transfer unit: the detainees who need to be transferred will be randomly assigned to a prison other than the original prison after passing through the screening unit in the order of their exit from the original prison, and the identity information, case category, and prison number of the detainee will be synchronized to the database unit; Login unit: three login categories are set up, including: entry and transfer login, database access query login, and administrator login.
[0026] Through the setting of database units, screening units, pre-dividing warehouse units, dividing warehouse units and adjusting warehouse units, the tedious manual data entry is avoided, the data entry efficiency is improved, and the errors caused by manual allocation are avoided, so that each prison is used in a standardized manner. The random allocation of the system avoids the hidden risks of corruption, making each allocation fair and reasonable, which greatly improves the efficiency of dividing and adjusting warehouses in prisons.
[0027] Among them, it needs to be supplemented that identity information includes: name, gender, ID number, place of origin, address, and health status; and case categories include: eight major violent cases, theft cases, and sensitive cases.
[0028] Among them, the screening calculation model is: y is not greater than Y, where n is the number of inmates in the prison who meet one of the eight characteristics of violent cases, theft cases, sensitive cases, seriously ill patients, over 60 years old, and the same place of origin; N is the number of all inmates in the prison, including those who are waiting to be confirmed and detained within the retention period; Y is the required proportion of the prison; and y is the actual proportion of the prison.
[0029] It should be noted that the screening unit also includes a same-case exclusion module, which includes the following algorithmic steps: the first step is that when entering the identity information and case category of the detainees, the entry unit will automatically number the case category; the second step is that when pre-separating and dividing the detainees into different cells, the screening unit will exclude the detention centers where the detainees have the same case category number; the third step is that when transferring the detainees into different cells, the screening unit will exclude the detention centers where the detainees have the same case category number.
[0030] By setting up the same-case exclusion module, people involved in the same case will not be assigned to the same prison. This is automatically applied when the screening unit is running. Compared with manual screening, the efficiency has been greatly improved.
[0031] It is necessary to explain in detail the operations that can be performed by users who log in for recording and transferring, database access and query, and administrator login:
[0032] The rights of the person logging in for recording, dividing and transferring include: entering the identity information and case category of the persons to be detained, running the pre-dividing warehouse unit, running the dividing warehouse unit and running the dividing warehouse unit. The person logging in for recording, dividing and transferring has no right to know the detention center to which the entered persons to be detained are randomly assigned after passing through the pre-dividing warehouse unit and the dividing warehouse unit. The person logging in for recording, dividing and transferring has no right to know the detention center to which the detainees are randomly assigned after passing through the dividing warehouse unit.
[0033] The rights of the personnel who log in to access and query the database include: querying the information and prisons of detainees and prisoners, directly contacting and managing detainees and reporting information entry errors to the personnel who log in to make corrections. Each query and feedback of entry errors by the personnel who access and query the database will be backed up with a timestamp and information summary in this system. It should be noted that the information summary mainly refers to the evidence of feedback of entry errors and the purpose of each access query.
[0034] The permissions of the person logged in as an administrator include: modifying the specified ratio in the screening unit, modifying the retention period in the pre-storage unit, and viewing the timestamp and information summary backed up in the system by the person who accesses the database query.
[0035] Through the setting of the login unit, the control and use permissions of this system are graded. The personnel who log in for recording and adjusting are unaware of the prison to which the detainees or detainees are assigned, thus reducing their corruption risks. The timestamps and information summaries backed up in the system by the personnel who log in for database access and query can not only check the errors in the database unit and improve the accuracy of the data, but also leave traces to provide clues for possible subsequent accountability, thus improving the security of this system.
[0036] Among them, it should be noted that the login unit also includes a security module, wherein the security module prevents the password from being stolen by setting a password mutation algorithm, and the password mutation algorithm includes the following steps: Step 1: An additional password book query login is added, which is only used to query the login passwords of three login categories; Step 2: After each login, the three login categories automatically and randomly change the passwords and upload them to the password book query login system. The last password record is not deleted, and the update time is left; Step 3: The account usage authority of the password book query login is regularly and randomly changed.
[0037] Among them, it is also necessary to note that the login password for password book query login is set by the owner of the login category usage permission. If you have the permission to use this login category, you will lose the permission to use three login categories.
[0038] Through the setting of security modules and password mutation algorithms, each time a user logs into the system, a trace will be left. At the same time, the next time the user logs in, the password book will be used to query the account usage permission owner to know the information, thus avoiding private query and change of information in the system. While protecting the security of the login unit, it further supervises the behavior of staff and reduces the space for staff to violate corruption risks.
[0039] A method for using an intelligent warehouse division and adjustment system based on big data comprises the following steps: a first step, a person who logs in for recording, dividing and adjusting logs in to the system, enters the identity information and case category of the person to be detained and runs the front warehouse division unit, the warehouse division unit or directly runs the warehouse adjustment unit for the detained person; a second step, a person who logs in for database access and query logs in to the system to obtain the information of the person to be detained or the detained person and the prison where the person is located; a third step, if the person who logs in for database access and query finds that the input errors of the identity information and case category of the person to be detained are found, the person who logs in for recording, dividing and adjusting can feedback to the person who logs in for modification; a fourth step, the person who logs in as an administrator can modify the prescribed proportion in the screening unit and the retention period in the front warehouse division unit according to the authority scale of the prison or the new regulations, and can view the timestamp and information summary backed up in the system by the person who logs in for database access and query to supervise and trace. In summary, the method for using the system is concise, efficient, and easy to operate and execute.
[0040] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.
Claims
1. An intelligent warehouse division and adjustment system based on big data, It is characterized in that include: Database unit: Establish a database on detainees. The database information includes: detainee identity information, case category, and prison number. Input unit: establish a database about detained persons, the database information includes: identity information of detained persons, case category, and the detained persons are divided into immediate detained persons and detained persons to be confirmed. Screening unit: Based on the prison's requirements for the proportion of eight violent cases, theft cases, sensitive cases, the number of seriously ill patients, the number of people over 60 years old, and the number of people with the same place of origin, a screening calculation model is established to ensure that the actual proportion of the prison is always kept below the prescribed proportion requirement during the process of warehouse division and adjustment. Pre-placement unit: The detainees to be confirmed who have been entered into the entry unit will be randomly assigned to a prison after passing through the screening unit in the order of entry time, and a prison bed will be reserved for the detainees. A retention period can be set according to the judicial procedure time required for the detainees and the saturation level of all prisons. If the retention period is exceeded, the pre-placement unit of the detainee will be invalid. If the detainee is admitted to the prison normally within the retention period, the identity information, case category, and prison number of the detainee to be confirmed will be synchronized to the database unit. Cell division unit: The persons on-call who have been entered into the entry unit will be randomly assigned to a cell after passing through the screening unit in the order of entry time, and the identity information, case category, and cell number of the persons on-call will be synchronized to the database unit. Transfer unit: The detainees who need to be transferred will be randomly assigned to a prison other than the original prison after passing through the screening unit in the order of their exit from the original prison. The identity information, case type, and prison number of the detainee will be synchronized to the database unit. Login unit: Set up three login categories, including: recording and transfer login, database access and query login, and administrator login.
2. According to the big data-based intelligent warehouse division and adjustment system of claim 1, It is characterized in that The identity information includes: name, gender, ID number, place of origin, address, and health status; the case categories include: eight major violent cases, theft cases, and sensitive cases.
3. According to the big data-based intelligent warehouse division and adjustment system of claim 2, It is characterized in that The screening calculation model is: y is not greater than Y, where n is the number of inmates in the prison who meet one of the eight characteristics of violent cases, theft cases, sensitive cases, seriously ill patients, over 60 years old, and the same place of origin; N is the number of all inmates in the prison, including those who are waiting to be confirmed and detained within the retention period; Y is the prescribed ratio requirement of the prison; and y is the actual ratio of the prison.
4. According to the big data-based intelligent warehouse division and adjustment system and method according to claim 1, It is characterized in that The screening unit also includes a same case exclusion module, which includes the following algorithm steps: S1: When entering the identity information and case category of the detainee, the entry unit will automatically number the case category. S2: When pre-dividing and dividing detainees, the screening unit will exclude detention centers where detainees with the same case category number are already located. S3: When transferring detainees, the screening unit will exclude detention centers where detainees with the same case category number are already in custody.
5. According to the big data-based intelligent warehouse division and adjustment system of claim 1, It is characterized in that The authority of the person who logs in for recording, dividing and adjusting includes: entering the identity information and case category of the detained persons, running the pre-dividing warehouse unit, running the dividing warehouse unit, and running the adjusting warehouse unit. The person who logs in for recording, dividing and adjusting has no authority to know the prison to which the detained persons are randomly assigned after passing through the pre-dividing warehouse unit and the dividing warehouse unit, and the person who logs in for recording, dividing and adjusting has no authority to know the prison to which the detained persons are randomly assigned after passing through the adjusting warehouse unit.
6. According to the big data-based intelligent warehouse division and adjustment system of claim 5, It is characterized in that The permissions of the person who logs in to access and query the database include: querying the information and prisons of persons awaiting detention and detainees, directly contacting and managing persons awaiting detention and detainees, and reporting information entry errors to the person who logs in to make corrections. Each query and feedback of entry errors by the person who accesses and queries the database will be backed up with a timestamp and information summary in this system.
7. According to claim 6, an intelligent warehouse division and adjustment system based on big data, It is characterized in that The permissions of the person logged in as the administrator include: modifying the specified ratio in the screening unit, modifying the retention period in the pre-storage unit, and viewing the timestamp and information summary backed up in the system by the person who accesses the database query.
8. A method for using the intelligent warehouse division and adjustment system based on big data according to claim 1, It is characterized in that The following steps are involved: S1: The person who logs in for division and transfer logs in to the system, enters the identity information and case category of the person to be detained, and runs the pre-division unit, division unit, or directly runs the transfer unit for the detainee; S2: Database access query The logged-in personnel log into this system and obtain the information of the persons to be detained or detained and the prison where they are located; S3: If the personnel who log in to access the database find errors in the identity information and case categories of the detained persons, they can feedback to the personnel who log in to the database for correction; S4: The person logged in as an administrator can modify the prescribed proportion in the screening unit and the retention period in the pre-storage unit according to the prison authority scale or new regulations, and can view the timestamps and information summaries backed up in the system by the person who has logged in to the database for monitoring and tracing.