Novel scientific research project intelligent management and control platform

Abstract

The invention discloses a novel intelligent management and control platform for scientific research projects, which comprises a project approval analysis module, a project progress tracking analysis module, a project achievement management module and an intellectual property protection module, relates to the technical field of intelligent management and control, and solves the problem that whole-process information coherence is difficult to realize when scientific research project information is analyzed. In order to solve the technical problems that technical feasibility analysis mostly stays in subjective qualitative judgment, system analysis is lacked and evaluation accuracy is reduced, a quantitative evaluation system is constructed, scientific research values are comprehensively measured and calculated from the technical dimension and the market dimension, project feasibility is accurately balanced, project establishment blindness is reduced, the high-quality project screening success rate is increased, and the evaluation accuracy is improved. Scientific research resources are reasonably configured, through periodic monitoring and intelligent comparison of real-time and benchmarking progress, rationality is accurately judged according to a self-adaptive threshold value, abnormity is timely pulled out, reasons are deeply analyzed, a strategy is pushed, it is ensured that a project is stably propelled according to a plan, and the delay risk is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management and control technology, and in particular to a novel intelligent management and control platform for scientific research projects. Background Art

[0002] In today's scientific research field, the complexity and scale of scientific research projects continue to increase, and traditional scientific research management models are increasingly unable to meet the needs of efficient and precise control.

[0003] On the one hand, the information in all links of scientific research projects, from project preparation to output of results, is complicated and scattered, and the collection of basic information relies on manual sorting, which is prone to omissions and errors, and it is difficult to achieve coherent traceability of information throughout the process; when evaluating the feasibility of projects, the analysis of technical feasibility often remains at the level of subjective qualitative judgment, and there is a lack of systematic quantitative means to measure the maturity of required technologies and the difficulty of resource acquisition. Market demand analysis is often due to sample limitations and outdated data, resulting in inaccurate grasp of the target group and large deviations in the estimation of market potential.

[0004] On the other hand, project progress tracking mostly relies on regular reporting, which makes it difficult to detect subtle deviations and deep-seated problems in a timely manner. When the progress is abnormal, the cause analysis is time-consuming and inaccurate, and it is impossible to respond quickly and effectively. In the achievement management link, scientific research records and achievement storage are scattered and disordered, knowledge is not effectively integrated and mined, achievement transformation lacks professional evaluation and resource docking, intellectual property protection is passive and lagging, and often faces infringement risks and rights protection difficulties. The overall scientific research management efficiency, quality and value realization need to be improved urgently. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a new intelligent management and control platform for scientific research projects, which solves the problems of difficulty in achieving full information coherence when analyzing scientific research project information, and the fact that technical feasibility analysis mostly remains at the level of subjective qualitative judgment and lacks systematic analysis, thereby reducing the accuracy of evaluation.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a new type of scientific research project intelligent management and control platform, including:

[0007] The project establishment analysis module is used to analyze the scientific research feasibility of scientific research projects based on the basic project information transmitted by the project information collection module, and to comprehensively calculate the scientific research feasibility value from the two aspects of technical feasibility and market demand feasibility. At the same time, the scientific research projects are judged based on the scientific research feasibility value, and the project establishment results and non-project establishment results are generated. The project establishment results are transmitted to the project progress tracking and analysis module, and the non-project establishment results are transmitted to the project management information output module;

[0008] The project progress tracking and analysis module is used to analyze the obtained project establishment results, and to judge the rationality of the project progress by analyzing the project progress of the scientific research project to generate reasonable results or unreasonable results, and transmit the reasonable results to the project achievement management module. At the same time, the unreasonable results are analyzed, and the abnormal reasons are determined in combination with the project progress, and the abnormal reasons are transmitted to the project management information output module;

[0009] The project achievement management module is used to analyze the scientific research projects corresponding to the reasonable results obtained, store the scientific research records and research results of the scientific research projects, and conduct corresponding transformation analysis based on the scientific and technological achievements to obtain the transformation analysis results, and at the same time transmit the transformation analysis results to the intellectual property protection module;

[0010] The intellectual property protection module is used to process the obtained conversion analysis results. It is also used to manage the project's patent applications, copyright registrations and other intellectual property matters, and transmit management information to the project management information output module.

[0011] As a further solution of the present invention, it also includes a project information collection module and a project management information output module;

[0012] The project information collection module is used to obtain the basic information of scientific research projects and transmit the obtained basic information to the project establishment analysis module. The basic information obtained includes the basic content of the project, the content and method of the project research, and the project schedule.

[0013] The project management information output module is used to display the acquired abnormal reasons and management information to the corresponding management personnel.

[0014] As a further solution of the present invention, the project establishment analysis module analyzes the technical feasibility of the scientific research project in the following manner:

[0015] The required technologies of the scientific research project are obtained and labeled as i, where i=1, 2, ..., j, where j represents the number of required technologies. At the same time, the maturity of the required technology i is quantified, and the quantified maturity is assigned a value and recorded as F i. Similarly, the maturity values ​​of all required technologies i are obtained, and the average value of the maturity values ​​of the required technologies is calculated and recorded as the technology value Fp;

[0016] At the same time, the technical resources of the scientific research project are obtained and labeled as n, where n = 1, 2, ..., m, where m represents the number of technical resources, and the difficulty of obtaining technical resource n is quantified, and the quantified difficulty of obtaining is assigned a value and recorded as Gn, and then the mean of the assigned technical resource values ​​is calculated as the resource value Gp;

[0017] At the same time, the technical value Fp and the resource value Gp are summed to obtain the technical feasibility value L1 of the scientific research project.

[0018] As a further solution of the present invention, the project establishment analysis module analyzes the feasibility of market demand for scientific research projects in the following manner:

[0019] Obtain the target group of the scientific research project, obtain the number of people in the target group, and calculate the proportion of the number of people. Then, rate the proportion of the number of people obtained, and assign values ​​to the different levels obtained as the group demand value.

[0020] Then, randomly obtain h users, conduct questionnaire tests on h users, and count the questionnaires of users to obtain the corresponding survey values ​​on the questionnaires. Similarly, obtain the survey values ​​of h users, and calculate the mean of all survey values ​​as the expected value Kh. At the same time, estimate the overall users based on the expected value Kh.

[0021] Then, the calculated group demand value and expected value are summed to obtain the market demand value L2.

[0022] As a further solution of the present invention, the specific method in which the project establishment analysis module judges the scientific research project according to the scientific research feasibility value is:

[0023] The scientific research value is calculated by calculating the sum of the technical feasibility value L1 and the market demand value L2, and the scientific research value is compared with the preset value. If the scientific research value is greater than the preset value, it means that the scientific research project is feasible and a project establishment result is generated. Otherwise, if the scientific research value is less than the preset value, it means that the scientific research project is not feasible and a non-project establishment result is generated. Then the project establishment result is transmitted to the project progress tracking and analysis module, and the non-project establishment result is transmitted to the project management information output module.

[0024] As a further solution of the present invention, the specific method in which the project progress tracking and analysis module analyzes the project establishment results is as follows:

[0025] Analyze the project establishment results, monitor the progress of the scientific research project periodically, obtain the real-time project progress, and obtain the corresponding time period, obtain the corresponding benchmark progress based on the time period, and then calculate the difference between the real-time project progress and the benchmark progress and record it as the progress difference;

[0026] If the progress difference is greater than the preset progress value, it means that the real-time progress project deviates greatly, which means that the project progress in the current time period is unreasonable, and unreasonable results are generated. On the contrary, if the progress difference is less than the preset progress value, it means that the real-time progress project deviates slightly, which means that the project progress in the current time period is reasonable, and reasonable results are generated, and unreasonable results are analyzed.

[0027] As a further solution of the present invention, the specific method in which the project progress tracking and analysis module analyzes unreasonable results is as follows:

[0028] Then, the unreasonable results are analyzed, the project progress corresponding to the current cycle is obtained, and the project progress is segmented. The real-time project progress after segmentation is compared with the benchmark progress to determine the cause of the abnormality, and then the cause of the abnormality is transmitted to the project management information output module.

[0029] As a further solution of the present invention, the specific method for the project achievement management module to obtain the conversion analysis result is:

[0030] Use blockchain distributed ledger technology and cloud storage to build a dedicated archive for scientific research projects. Scientific research records are subdivided into experimental raw data, research logs, and project documents. Research results are accurately classified and stored by academic, technical, and physical objects. Each data is associated according to the project level.

[0031] Artificial intelligence and machine learning algorithms are introduced to explore the value of stored data, extract key content of papers, identify patent innovations and draw up a technology roadmap, explore the patterns of experimental data to build a "scientific research knowledge graph", and form an interdisciplinary "technology industrialization review group". After market and technical evaluation, conversion analysis results are generated and transmitted to the intellectual property protection module.

[0032] The present invention provides a new type of intelligent management and control platform for scientific research projects. Compared with the prior art, it has the following beneficial effects:

[0033] The present invention constructs a quantitative evaluation system, comprehensively measures the scientific research value from the dual dimensions of technology and market, accurately weighs the feasibility of the project, and analyzes the required technology, resources and target groups in detail based on examples, reduces the blindness of project establishment, improves the success rate of high-quality project screening, and rationally allocates scientific research resources. Through periodic monitoring and intelligent comparison of real-time and benchmark progress, the invention accurately judges rationality based on adaptive thresholds, finds out anomalies in time, deeply analyzes the causes and pushes strategies, ensuring that the project is steadily advanced as planned and reducing the risk of delays.

[0034] Relying on advanced storage and algorithms, integrating scientific research knowledge graphs, and exploring the potential value of research results, the "Technology Industrialization Review Group" professionally evaluates market technology adaptation, clears transformation bottlenecks, and coordinates the pre-positioning and precise layout of intellectual property protection, accelerating the transition of research results from the laboratory to the market, and improving the economic and social benefits of scientific research;

[0035] The unified archive uses blockchain and cloud storage to ensure data reliability, subdivides scientific research records and results categories, and hierarchical associations, breaking down information silos and leaving traces throughout the process, laying a solid data foundation for full-process project management and improving management transparency and standardization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a system block diagram of the intelligent management and control platform of the present invention;

[0037] Figure 2 This is the process management diagram of the scientific research project of the present invention;

[0038] Figure 3 This is a flow chart of the intellectual property management of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] For example, see Figures 1 to 3 This application provides a new type of scientific research project intelligent management and control platform, including project information collection module, project establishment analysis module, project progress tracking and analysis module, project achievement management module, intellectual property protection module and project management information output module, and at the same time combines the attached Figure 1 As shown, the above functional modules are electrically connected in a unidirectional manner.

[0041] Project information collection module, this module is used to obtain the basic information of scientific research projects, and transmit the obtained basic information to the project establishment analysis module. The basic information obtained includes the basic content of the project, the project research content and methods, and the project schedule. The specific basic content of the project includes the project name, project number, project start and end time, as well as the project leader and team information. The project research content and methods include the core problem description and content module division, and the research methods include theoretical methods, experimental methods, and data collection and analysis methods. The project schedule includes stage division and key nodes as well as progress plan charts.

[0042] Project establishment analysis module, this module is used to analyze the scientific research feasibility of scientific research projects based on the acquired basic project information, and comprehensively calculate the scientific research feasibility value from two aspects: technical feasibility and market demand feasibility. At the same time, the scientific research projects are judged based on the scientific research feasibility value, and the judgment results are generated and then transmitted.

[0043] Obtain basic information on scientific research projects, and analyze them from two aspects: technical feasibility and market demand feasibility;

[0044] The analysis of the technical feasibility of scientific research projects is as follows: the required technologies of scientific research projects are obtained and labeled as i, and i = 1, 2, ..., j, where j represents the number of required technologies, and the maturity of required technology i is quantified. The specific maturity quantification is expressed as the division of maturity, such as qualitative intervals of maturity at different levels such as budding, preliminary exploration, moderate development, relative maturity, and high maturity, and the quantified maturity is assigned a value and recorded as F i. For example, the values ​​are 1, 2, 3, 4 and 5 respectively, where the values ​​correspond to the above maturity levels, and the specific budding corresponds to 1, and the high maturity corresponds to 5. Similarly, the maturity values ​​of all required technologies i are obtained, and the average value of the maturity values ​​of the required technologies is calculated and recorded as the technical value Fp;

[0045] Assume that there is a research project on a new intelligent medical imaging diagnosis system, Technology 1 (i = 1): Image deep learning algorithm optimization technology, used to improve the accuracy of image recognition. At present, this technology has many research results in the field of medical imaging and is in a relatively mature stage, corresponding to a maturity level of 4, so F1 = 4;

[0046] Technology 2 (i=2): Edge computing data processing technology for medical imaging, which can realize local rapid processing of imaging data and reduce transmission delays, but is still in the medium development stage. The scientific research team has a good grasp of its theory and has some preliminary application cases. The corresponding maturity level is 3, so F2=3;

[0047] Technology 3 (i=3): Multimodal image data fusion technology, which attempts to integrate different modality image information such as CT and MRI. It is still in the initial exploration stage. The research team has just built the basic framework and is still testing and adjusting it. The corresponding maturity level is 2, that is, F3=2;

[0048] Technology 4 (i=4): Human-computer interaction interface design technology for medical equipment, which aims to design an image diagnosis system interface that is convenient for doctors to operate. This technology is mature in the field of consumer electronics, but its adaptation to medical scenarios is still in its infancy, and the integration of relevant medical standards has just begun. The maturity level is 1, so F4=1;

[0049] Further calculation of the assigned values ​​of all technical requirements yields Fp=2.5.

[0050] At the same time, the technical resources of the scientific research project are obtained and labeled as n, and n = 1, 2, ..., m, where m represents the number of technical resources. Specific technical resources include technical equipment, software tools, and experimental facilities required for the project, and the difficulty of obtaining technical resources n is quantified. The specific quantification of the difficulty of obtaining is expressed as dividing the difficulty of obtaining, for example, dividing it into three levels: simple, general, and difficult. At the same time, the quantified difficulty of obtaining is assigned a value and recorded as Gn. Specifically, different division levels are assigned values ​​of 1, 2, and 3, and the values ​​correspond to the above levels respectively. Then, the mean of the assigned technical resources is calculated as the resource value Gp. At the same time, the technical value Fp and the resource value Gp are summed to obtain the technical feasibility value L1 of the scientific research project.

[0051] For example, the research project identified the following main technical resources and numbered them in sequence:

[0052] Resource 1 (n = 1): A high-performance graphics processing server used to run deep learning algorithm training and image data processing. There are many suppliers on the market that provide similar configuration products. The procurement process is relatively standardized and simple. The acquisition difficulty level is simple, and the value G1 = 1;

[0053] Resource 2 (n = 2): Professional medical image annotation software, which must comply with medical data privacy regulations and customize annotation rules for the special image features of this project. The acquisition channels are limited and the operation is relatively complex. The acquisition difficulty level is medium, and the value is G2 = 2;

[0054] Resource 3 (n = 3): Medical imaging physical simulation experimental facilities that simulate various disease states. They are produced by only a few professional manufacturers in the world. They are highly customized and expensive. They also have to go through a cumbersome medical equipment access approval process. The difficulty level of obtaining them is difficult, and the value is G3 = 3.

[0055] At the same time, the mean value Gp=2 is assigned to the obtained technical resources.

[0056] The feasibility analysis of the market demand for scientific research projects is as follows: obtain the target group of the scientific research project, obtain the number of people corresponding to the target group, and calculate the proportion of the number of people. The target group here is represented by the corresponding age range of the group. At the same time, the number of people in the corresponding age range is obtained based on big data. Then the proportion of the obtained number of people is rated. The rating processing here means that different levels are divided according to the numerical value of the proportion of the number of people. The number of target groups collected is summarized and strictly compared with the number of the same type of overall population in the corresponding region (in this case, the entire permanent population of the first-tier city). Using statistical precision algorithms, the proportion of the target group in the overall population is calculated, and the rating is set as "niche focus type (A level)", "moderate mainstream type (B level)", "widespread popularization type (C level)" "There are four levels of "super-large-scale (Grade D)", which are specifically defined as: the proportion of people in the range of 0-5% belongs to Grade A, which means that the project targets a relatively niche and specific segmented group, with precise needs but limited scale; the proportion of 5%-15% corresponds to Grade B, reflecting that the project audience has a certain scale and has moderate influence and coverage in the market; the proportion of 15%-30% fits Grade C, highlighting that the project is aimed at a wide range of mass groups and has considerable market potential and prospects for popularization; the proportion of more than 30% is classified as Grade D, indicating that the project targets a super-large audience, is expected to lead the mainstream trend of the industry and give birth to a grand market map, and at the same time, the different levels are assigned values ​​​​and recorded as group demand values, such as assigning 1, 2, 3 and 4 to A, B, C and D respectively, and the assigned values ​​​​are recorded as group demand values;

[0057] Then, randomly obtain h users, and conduct questionnaire tests on h users at the same time. The user questionnaires are counted to obtain the corresponding survey values ​​on the questionnaire, and the expected value here is calculated based on the questionnaire. For example, there are ten questions on the questionnaire, each question has four options, and the scores corresponding to the options are 1, 2, 3 and 4 respectively. The scores of the user questionnaires are counted, and the obtained scores are summed to obtain the user's survey value. Similarly, the survey values ​​of h users are obtained, and the mean of all survey values ​​is calculated as the expected value Kh. At the same time, the overall user is estimated based on the obtained expected value Kh;

[0058] Then, the calculated group demand value and expected value are summed to obtain the market demand value L2;

[0059] The scientific research value is calculated by calculating the sum of the technical feasibility value L1 and the market demand value L2, and the scientific research value is compared with the preset value. The specific value of the preset value here is set by the operator based on experience. If the scientific research value is greater than the preset value, it means that the scientific research project is feasible and a project establishment result is generated. Otherwise, if the scientific research value is less than the preset value, it means that the scientific research project is not feasible and a non-project establishment result is generated. Then the project establishment result is transmitted to the project progress tracking and analysis module, and the non-project establishment result is transmitted to the project management information output module.

[0060] The project progress tracking and analysis module is used to analyze the obtained project establishment results. By analyzing the project progress of the scientific research project, the rationality of the project progress is judged to generate reasonable results or unreasonable results, and the reasonable results are transmitted to the project achievement management module. At the same time, the unreasonable results are analyzed, and the abnormal reasons are determined in combination with the project progress, and the abnormal reasons are transmitted to the project management information output module.

[0061] Analyze the obtained project establishment results, and monitor the progress of the scientific research project periodically to obtain the real-time project progress and the corresponding time period. Based on the time period, obtain the corresponding benchmark progress, and the benchmark progress here represents the schedule of the initial scientific research project. Then calculate the difference between the real-time project progress and the benchmark progress and record it as the progress difference. If the progress difference is greater than the preset progress value, it means that the real-time progress project deviates greatly, which means that the project progress of the current time period is unreasonable, and an unreasonable result is generated. On the contrary, if the progress difference is less than the preset progress value, it means that the real-time progress project deviates less, which means that the project progress of the current time period is reasonable, and a reasonable result is generated.

[0062] Then, the unreasonable results are analyzed, the project progress corresponding to the current cycle is obtained, and the project progress is segmented. The real-time project progress after segmentation is compared with the benchmark progress to determine the cause of the abnormality, and then the cause of the abnormality is transmitted to the project management information output module.

[0063] For example, in the second and a half month of the project, the intelligent monitoring platform showed that it had signed data sharing agreements with five grassroots hospitals (two more than planned), and the construction of the imaging data set had been completed by 65% ​​(ahead of schedule). The algorithm team not only determined the basic selection, but also preliminarily optimized the super-resolution structure adapted to medical low-dose imaging. The progress difference was less than the adaptive preset value, and a reasonable result report was generated, detailing how data cooperation helped model generalization beyond expectations and structural optimization unlocked the advantages of image detail enhancement in advance. It was recommended to strike while the iron is hot to expand the data annotation categories and fine-tune the model architecture, and enter the clinical verification preparation period (benchmarking progress in the 9th to 12th months). According to the plan, the model should be tested internally in the imaging department of the cooperative hospital, ethical approval and medical staff operation training should be completed in the 10th month. However, due to the new national medical data security regulations, the cooperative hospitals urgently adjusted the data interface and strengthened privacy audits, resulting in a two-week data transmission interruption, and only 40% of the internal model testing was completed; the ethical approval process lagged behind by 60% due to the need to redraft the application materials and wait for review by superiors due to the update of regulations; the training was delayed by less than 30% due to the withdrawal of medical staff for anti-epidemic work, and the progress difference far exceeded the preset value, which was judged to be unreasonable;

[0064] The platform quickly analyzed the data connection section by section, and found that the data connection section was delayed by 70% due to policy changes and technical adaptation; the ethics approval section was delayed by 80% due to the impact of new regulations and process reset; and the training section was delayed by 70% due to imbalance in personnel allocation. These abnormal reasons were output to the management module in a structured manner, with pop-up windows showing policy and regulatory provisions, voice prompts for key delay points, and mobile terminals pushing detailed correction strategies (such as sending a technical team to the site to overcome data interfaces, special personnel to keep a close eye on ethics declarations, and adjusting training to an online asynchronous mode), to help the project get back on track and steadily move towards the implementation of results.

[0065] Project management information output module, which is used to display the acquired abnormal reasons to the corresponding management personnel.

[0066] Embodiment 2, as Embodiment 2 of the present invention, is implemented on the basis of Embodiment 1, and differs from Embodiment 1 in that:

[0067] The project results management module is used to analyze the scientific research projects corresponding to the reasonable results obtained, store the scientific research records and research results of the scientific research projects, conduct corresponding transformation analysis based on the scientific and technological achievements, and transmit the transformation analysis results to the intellectual property protection module.

[0068] First, relying on advanced blockchain distributed ledger technology and cloud storage architecture, we build exclusive archives for scientific research projects to ensure that data cannot be tampered with and is traceable throughout the process. For scientific research records, we subdivide experimental raw data (covering various instrument monitoring values, sample observation details, stored in the form of time series and multi-dimensional data tables), research logs (daily work records of scientific researchers, problem-solving ideas, key meeting minutes, supporting voice-to-text entry and intelligent classification and labeling), project documents (project application, mid-term inspection report, final summary, with electronic signature of approval process), etc. For research results, we accurately classify and store them according to academic achievements (various versions of papers from preprints to formal publication, conference report PPT and videos, and related citation networks updated in real time), technical achievements (various drafts of patent applications, responses to examination opinions, software code bases and version iteration logs, engineering drawings CAD files), and physical results (high-resolution 3D scanning models, quality inspection reports, prototype operation manuals). Each data unit is associated and mapped according to the project, sub-topic, and task module levels. Artificial intelligence natural language processing and machine learning algorithms are introduced to regularly "deepen and cultivate" the stored data. Automatically extract keywords and core ideas of papers, identify core innovations of patent technologies, draw technology evolution roadmaps (based on correlation analysis of patent families and cited patents), mine hidden rules of experimental data (such as discovering the influence of different sample parameter combinations on achievement indicators through cluster analysis), and integrate fragmented knowledge into a structured "scientific research knowledge map";

[0069] An interdisciplinary "Technology Industrialization Review Group" will be formed, covering scientific research leaders, engineering and technology experts, production process masters, and industrial economists. Based on market and technology evaluations, it will generate transformation analysis results, which will then be transmitted to the intellectual property protection module.

[0070] The intellectual property protection module is used to process the obtained conversion analysis results. It is also used to manage the project's patent applications, copyright registrations and other intellectual property matters, and transmit management information to the project management information output module. The management information here is mainly patent information on scientific research projects.

[0071] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0072] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0073] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A new type of intelligent management and control platform for scientific research projects, characterized by: include: The project establishment analysis module is used to analyze the scientific research feasibility of scientific research projects based on the basic project information transmitted by the project information collection module, and to comprehensively calculate the scientific research feasibility value from the two aspects of technical feasibility and market demand feasibility. At the same time, the scientific research projects are judged based on the scientific research feasibility value, and the project establishment results and non-project establishment results are generated. The project establishment results are transmitted to the project progress tracking and analysis module, and the non-project establishment results are transmitted to the project management information output module; The project progress tracking and analysis module is used to analyze the obtained project establishment results, and to judge the rationality of the project progress by analyzing the project progress of the scientific research project to generate reasonable results or unreasonable results, and transmit the reasonable results to the project achievement management module. At the same time, the unreasonable results are analyzed, and the abnormal reasons are determined in combination with the project progress, and the abnormal reasons are transmitted to the project management information output module; The project achievement management module is used to analyze the scientific research projects corresponding to the reasonable results obtained, store the scientific research records and research results of the scientific research projects, and conduct corresponding transformation analysis based on the scientific and technological achievements to obtain the transformation analysis results, and at the same time transmit the transformation analysis results to the intellectual property protection module; The intellectual property protection module is used to process the obtained conversion analysis results. It is also used to manage the project's patent applications, copyright registrations and other intellectual property matters, and transmit management information to the project management information output module.

2. A new type of scientific research project intelligent management and control platform according to claim 1, characterized in that: It also includes a project information collection module and a project management information output module; The project information collection module is used to obtain the basic information of scientific research projects and transmit the obtained basic information to the project establishment analysis module. The basic information obtained includes the basic content of the project, the content and method of the project research, and the project schedule. The project management information output module is used to display the acquired abnormal reasons and management information to the corresponding management personnel.

3. According to claim 1, a new type of intelligent management and control platform for scientific research projects is characterized in that: The project establishment analysis module analyzes the technical feasibility of scientific research projects in the following ways: The required technologies of the scientific research project are obtained and labeled as i, where i = 1, 2, ..., j, where j represents the number of required technologies. At the same time, the maturity of the required technology i is quantified, and the quantified maturity is assigned a value and recorded as Fi. Similarly, the maturity values ​​of all required technologies i are obtained, and the mean value of the maturity values ​​of the required technologies is calculated and recorded as the technology value Fp; At the same time, the technical resources of the scientific research project are obtained and labeled as n, where n = 1, 2, ..., m, where m represents the number of technical resources, and the difficulty of obtaining technical resource n is quantified, and the quantified difficulty of obtaining is assigned a value and recorded as Gn, and then the mean of the assigned technical resource values ​​is calculated as the resource value Gp; At the same time, the technical value Fp and the resource value Gp are summed to obtain the technical feasibility value L1 of the scientific research project.

4. A new type of scientific research project intelligent management and control platform according to claim 1, characterized in that: The project establishment analysis module analyzes the feasibility of market demand for scientific research projects in the following ways: Obtain the target group of the scientific research project, obtain the number of people in the target group, and calculate the proportion of the number of people. Then, rate the proportion of the number of people obtained, and assign values ​​to the different levels obtained as the group demand value. Then, randomly obtain h users, conduct questionnaire tests on h users, and count the questionnaires of users to obtain the corresponding survey values ​​on the questionnaires. Similarly, obtain the survey values ​​of h users, and calculate the mean of all survey values ​​as the expected value Kh. At the same time, estimate the overall users based on the expected value Kh. Then, the calculated group demand value and expected value are summed to obtain the market demand value L2.

5. According to claim 1, a new type of intelligent management and control platform for scientific research projects is characterized in that: The specific way in which the project establishment analysis module judges the scientific research project according to the scientific research feasibility value is as follows: The scientific research value is calculated by calculating the sum of the technical feasibility value L1 and the market demand value L2, and the scientific research value is compared with the preset value. If the scientific research value is greater than the preset value, it means that the scientific research project is feasible and a project establishment result is generated. Otherwise, if the scientific research value is less than the preset value, it means that the scientific research project is not feasible and a non-project establishment result is generated. Then the project establishment result is transmitted to the project progress tracking and analysis module, and the non-project establishment result is transmitted to the project management information output module.

6. A new type of scientific research project intelligent management and control platform according to claim 1, characterized in that: The specific method for the project progress tracking and analysis module to analyze the project establishment results is as follows: Analyze the project establishment results, monitor the progress of the scientific research project periodically, obtain the real-time project progress, and obtain the corresponding time period, obtain the corresponding benchmark progress based on the time period, and then calculate the difference between the real-time project progress and the benchmark progress and record it as the progress difference; If the progress difference is greater than the preset progress value, it means that the real-time progress project deviates greatly, which means that the project progress in the current time period is unreasonable, and unreasonable results are generated. On the contrary, if the progress difference is less than the preset progress value, it means that the real-time progress project deviates slightly, which means that the project progress in the current time period is reasonable, and reasonable results are generated, and unreasonable results are analyzed.

7. A new type of scientific research project intelligent management and control platform according to claim 1, characterized in that: The specific method for the project progress tracking and analysis module to analyze unreasonable results is as follows: Then, the unreasonable results are analyzed, the project progress corresponding to the current cycle is obtained, and the project progress is segmented. The real-time project progress after segmentation is compared with the benchmark progress to determine the cause of the abnormality, and then the cause of the abnormality is transmitted to the project management information output module.

8. According to claim 1, a new type of intelligent management and control platform for scientific research projects is characterized in that: The specific method for the project achievement management module to obtain the conversion analysis results is: Use blockchain distributed ledger technology and cloud storage to build a dedicated archive for scientific research projects. Scientific research records are subdivided into experimental raw data, research logs, and project documents. Research results are accurately classified and stored by academic, technical, and physical objects. Each data is associated according to the project level. Artificial intelligence and machine learning algorithms are introduced to explore the value of stored data, extract key content of papers, identify patent innovations and draw up a technology roadmap, explore the patterns of experimental data to build a "scientific research knowledge graph", and form an interdisciplinary "technology industrialization review group" to generate conversion analysis results through market and technology evaluation, which are then transmitted to the intellectual property protection module.

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