3329results about How to "Improve transmission efficiency" patented technology

The invention relates to the technical field of communication optimization, in particular to a wireless communication method and system of a vehicle diagnosis system. The method comprises the following steps: identifying a plurality of signal sources in an environment and three-dimensional space data of a current position of a vehicle; performing scene interference intensity comprehensive evaluation on the plurality of signal sources in the environment to obtain a current scene interference intensity evaluation value of the vehicle; environment obstacle space layout analysis is carried out on the three-dimensional space data of the current position of the vehicle, environment three-dimensional modeling is carried out, and a vehicle environment three-dimensional point cloud model is constructed; signal multi-path propagation evolution is carried out according to the current scene interference intensity evaluation value of the vehicle and the vehicle environment three-dimensional point cloud model, and optimal signal frequency band analysis is carried out, so that optimal signal frequency band parameters are extracted; and carrying out dynamic transmission frequency modulation and signal adaptive coding based on the optimal signal frequency band parameter, and constructing a dynamic signal transmission strategy. According to the invention, efficient and stable wireless communication is realized, and the vehicle-mounted communication performance is improved.

The invention relates to a multi-channel firmware upgrading method and system supporting breakpoint resume, and the method comprises the steps: segmenting a firmware file into a plurality of firmware data blocks, and generating a unique identifier and a checksum for each firmware data block; acquiring a network transmission channel, performing task matching with the network transmission channel according to the unique identifier to obtain a corresponding distribution transmission task, and establishing a corresponding initial record document; transmitting the firmware data block through the network transmission channel according to the distribution transmission task, monitoring the transmission state in real time, and carrying out breakpoint record updating on the initial record document to obtain a corresponding updated document; when it is detected that transmission is completed, verifying the firmware data block according to the checksum, and recombining the firmware data block to obtain the firmware file; and generating a corresponding upgrading report based on the updating document and the upgrading information. The upgrading strategy can be continuously optimized, and the system management efficiency can be improved.

The invention discloses a data security sharing method and system, and relates to the technical field of data security, and the method comprises the steps: receiving to-be-shared data uploaded by a data provider; fragmenting the data by adopting a biologically inspired adaptive fragmentation algorithm; generating a digital fingerprint for each fragment by using a multi-dimensional dynamic Hash algorithm; encrypting data fragments by adopting a post-quantum encryption algorithm and storing the data fragments in a decentralized network; recording the access authority, the digital fingerprint and the storage position information to a block chain security account book; when a data request is received, the access permission is verified; carrying out identity verification by adopting multi-mode biological feature recognition; after the verification is passed, obtaining a digital fingerprint and a storage position from the block chain; acquiring the encrypted fragments from the decentralized network and decrypting the encrypted fragments; verifying the integrity by using the digital fingerprint; and recombining the verified fragments to obtain complete data and returning the complete data to the requester. According to the method, efficient data sharing is realized while the data security is guaranteed, and the data value and privacy protection are effectively balanced.

The invention provides an encryption transmission method and system of a wireless information transmission communication base station, relates to the technical field, discloses the encryption transmission method of the wireless information transmission communication base station, and belongs to the technical field of wireless communication. The method comprises the following steps: receiving a communication signal and extracting identity authentication information and a signal characteristic parameter; performing identity authentication scoring based on a deep neural network, performing signal feature scoring through spectral analysis, and constructing a communication security assessment model; a key pair is generated by adopting an elliptic curve cryptographic algorithm, and data is encrypted after being subjected to confusion transformation and diffusion transformation; transmitting a key by using a quantum key distribution technology; and selecting an optimal transmission channel based on the operation state data of the communication base station, and performing data transmission by adopting interleaving coding and adaptive power control technologies. According to the invention, the security and transmission reliability of wireless communication are improved, and the anti-interference capability is enhanced.

The invention provides a dual-mode network communication method and system based on HPLC + HRF, and the method comprises the steps: carrying out the network initialization, and carrying out the initialization configuration of an HPLC module and an HRF module; data acquisition and feature extraction; training and predicting an LSTM neural network; selecting and optimizing a communication mode; dynamically adjusting the data transmission rate based on the prediction result of the LSTM neural network in combination with the current actual monitoring data; performing data transmission in the data transmission process according to the selected communication mode and data transmission rate; and data fusion and optimization: carrying out fusion processing, error correction and optimization sorting on the data from the HPLC and the HRF at a receiving end. By fusing the LSTM neural network prediction technology and the adaptive rate adjustment technology, accurate prediction of network communication link quality and intelligent optimization of the data transmission rate are realized, and the defects of the traditional network communication technology in a complex environment are effectively overcome.

The invention belongs to the technical field of perovskite solar cells, and particularly discloses a carbazolyl conjugate enhanced self-assembled monomolecular layer and a preparation method and application thereof, and the self-assembled monomolecular layer takes carbazole as a substrate and an aromatic ring as a conjugate linking group. The highly conjugated molecular system can induce molecular orbital overlap, increase dipole moment, promote formation of a compact self-assembled monomolecular film, reduce interface non-radiative recombination and enhance hole extraction and transmission performance. Meanwhile, phosphoric acid is used as an anchoring group, so that firm self-assembly of SAM molecules on the surface of the ITO substrate can be realized. The SAM material is simple in preparation method, high in yield, low in preparation cost and good in stability. When the compound is applied to a trans-perovskite solar cell as a hole transport layer, photoelectric conversion efficiency exceeding 24.6% can be obtained, and the compound is an organic semiconductor material with a very good prospect.

The invention discloses a laser SLAM (Simultaneous Localization and Mapping) method in a dynamic environment of a well mine, which relates to data processing and comprises the following steps of: performing mapping by utilizing a Cartograph SLAM algorithm; segmenting the PCD point cloud map by adopting an octree-based segmentation method according to a preset movement or deformation frequency threshold value of an object in each region in the well mining environment; adjusting the map resolution of each area in the PCD point cloud map according to the segmentation result; a change detection algorithm is used to carry out change detection on an area with object movement or deformation frequency exceeding a threshold value in the segmented PCD point cloud map, and new point cloud data of the change area is updated to the original PCD point cloud map in an increment mode; carrying out registration and fusion on the PCD point cloud map after local updating and an original PCD point cloud map; the global consistency is improved by aiming at the poor global consistency existing in the laser SLAM mapping of the well industry and mining in the prior art.

The invention discloses a video transmission method and system based on streaming processing, and relates to the technical field of video transmission, and the method comprises the steps: collecting a video stream, carrying out the preprocessing, extracting a video frame, packaging the video frame into a picture stream, carrying out the data fragmentation, distributing an initialization path for fragmented data, and calculating an initial traffic proportion; and optimizing path selection and adjusting path flow distribution according to network feedback to obtain a path optimization result, and transmitting the fragmented data according to the path optimization result. Through multi-level feature extraction and key frame selection of video frames, fragmented packaging of video data is realized, a dynamic path optimization technology is combined, path selection and flow distribution are dynamically adjusted based on a Q learning algorithm and a luminescence firefly algorithm, the transmission efficiency is improved, video image processing and a dynamic network optimization technology are fully combined, and the video image processing efficiency is improved. And a brand new solution is provided for efficient and stable transmission of high-definition video streams.

The invention relates to the technical field of distributed file processing, in particular to a distributed file processing method and system, and the method comprises the following steps: based on a task distribution node and a data exchange interface, extracting path characteristics of a task input / output file, analyzing a file exchange sequence of a task path, and calculating a topological structure and length of the path. According to the method, the flexibility and the adaptability of task allocation are realized by combining task state monitoring and real-time adjustment of dependent path weights and task priority marks, resource allocation and a short-time task sequence are optimized by utilizing request frequency and time period records, high-frequency request resource conflicts are effectively relieved, the resource allocation efficiency is improved, and the resource allocation efficiency is improved. Through node historical resource distribution data and time distribution trend analysis, task distribution is adjusted and resource loads are balanced in combination with differences, the stability and balance of the system are enhanced, a file transmission path is optimized based on a load state and a task execution path, and a concurrent task distribution strategy is improved.

The invention discloses a point cloud data processing method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring initial point cloud data to be sent; dividing the initial point cloud data into a group of point cloud blocks; performing graphical representation on the basis of the point cloud data in each point cloud block in the group of point cloud blocks to generate a group of graph structure data, one graph structure data in the group of graph structure data corresponding to one point cloud block in the group of point cloud blocks, and the graph structure data being used for representing features of the corresponding point cloud block; and encoding the group of graph structure data to obtain a group of data packets, and sending the group of data packets to a target terminal so as to perform decoding reconstruction at the target terminal to obtain target point cloud data. The technical problems that the processing efficiency of the point cloud data is low and the effect cannot be quickly achieved in the related technology are solved.

The invention discloses a low earth orbit satellite Internet of Things communication method and system based on a dynamic block chain, and the method specifically comprises the steps: taking at least one ground station as a consensus node in each network partition, forming a consensus network, and selecting a main node from a plurality of consensus nodes of each consensus network through employing an RBFT algorithm; a satellite transit algorithm is adopted to predict transit information of each low-orbit satellite, and the low-orbit satellites passing through any consensus network are set as accounting nodes of the consensus network according to the transit information; the method comprises the following steps: acquiring a service request of a satellite communication terminal, forwarding the service request to a main node of a consensus network to which the service request belongs through a low-orbit satellite of a transit satellite communication terminal, performing verification and priority ranking on the service request according to the main node, and if the verification is passed, performing broadcast and consensus verification on all nodes of the current consensus network. According to the invention, the communication efficiency and safety of the low-orbit satellite Internet of Things are improved, and reliable technical support is provided for satellite Internet application.

The invention relates to the technical field of data packet transmission, and discloses a data packet transmission control method and device for a low-power-consumption dual-mode Bluetooth chip, and the method comprises the steps: obtaining a signal strength parameter, a power consumption parameter, a transmission rate parameter and an environment parameter of the dual-mode Bluetooth chip, inputting the parameters into a deep time convolution network, and carrying out the time sequence feature extraction, obtaining a transmission mode switching judgment result; calculating transmission state evaluation data; the chip transmitting power is adjusted in a grading mode, standby power consumption is controlled through a nanoamp LDO circuit, and a dynamic power control parameter is obtained; performing compression coding on the data packet to obtain a dual-mode transmission protocol configuration parameter; executing time sequence sampling, and constructing a dual-mode state feature sequence; the data packet delivery success rate, the end-to-end transmission time delay and the total power consumption of the system are calculated, transmission control parameter optimization is carried out through double-layer deep reinforcement learning, target transmission control parameters are obtained, and the optimal balance of the transmission performance and the power consumption of the dual-mode Bluetooth chip is achieved.

The invention discloses an omnibearing risk early warning monitoring method and system based on intelligent wearable equipment, and relates to the technical field of health management, and the method comprises the steps: collecting and compressing multi-modal data through the intelligent wearable equipment, transmitting the compressed data to a central database, and carrying out the data restoration; multi-modal data analysis is carried out on the restored multi-modal data, comprehensive features are extracted, and a logic regression model is constructed to evaluate the health score of the user. According to the invention, the intelligent wearable device collects and compresses the multi-modal data, and transmits the compressed data to the central database for data restoration; performing multi-modal data analysis on the restored multi-modal data, extracting comprehensive features, and constructing a logic regression model to evaluate health scores of the users; the data processing and transmission efficiency is improved, the accuracy and response speed of health monitoring are improved, and the accuracy of data analysis is enhanced.

The invention provides a time division duplex multi-carrier synchronous transmission method based on 5G, which is used for solving the problems of inflexible carrier time slot allocation and inaccurate time delay compensation in synchronous transmission. By dynamically adjusting time slot allocation and working frequency bands of carriers in a network control center, the method optimizes network loads and reduces cross interference; the time delay of each carrier is compensated in real time by adopting a synchronous signal calibration algorithm, so that strict alignment of transmission time slots is ensured; the transmitting end dynamically adjusts the transmitting power according to link state information, and the receiving end reduces interference and signal attenuation through a multi-carrier cooperative interference management and multi-path delay compensation mechanism; and a receiving end performs joint decoding based on channel estimation and integrates demodulation signals of all carriers, so that the transmission efficiency and the signal quality of the 5G network are improved. The method is suitable for a base station system and a base station and repeater extension coverage system, and is especially suitable for a distributed wireless system including an optical fiber remote distributed system, a cable remote frequency shift repeater system and the like.

The invention discloses a multi-device cooperative management system based on cloud edge cooperation, and relates to the technical field of Internet of Things communication, and the system comprises a device management module which is used for connecting edge devices, carrying out the centralized management of the edge devices, and carrying out the optimal scheduling based on the functions and distribution positions of different edge devices; and the data acquisition module is connected with the equipment management module. According to the multi-device collaborative management system based on cloud edge collaboration, a comprehensive and accurate data basis is provided for multi-device collaborative management, and information exchange and collaborative work between devices are promoted; the optimization decision-making unit can formulate an equipment optimization management strategy according to the operation scheme generated by the big data analysis unit and the prediction result obtained by the prediction analysis unit, and continuously performs optimization adjustment according to the real-time operation condition of each piece of edge equipment; therefore, the system can adapt to continuously changing equipment operation environments and task requirements, and more efficient multi-equipment collaborative management is realized.

The invention relates to the technical field of data storage management, in particular to a data storage method based on a large model. The method comprises the following steps: performing input class cluster fragmentation optimization on a target pre-training large model to obtain storage modulus fragmentation data; constructing an intelligent fragmentation storage strategy by using the storage modulus fragmentation data; obtaining target model training data; performing intelligent fragmentation storage on the target model training data by using an intelligent fragmentation storage strategy, and performing redundancy compression optimization to obtain dynamic redundancy storage index data; and training data storage space optimization is carried out according to the dynamic redundancy storage index data, and an optimized data storage strategy is obtained. According to the method, intelligent fragmentation storage and refined data redundancy compression are performed on the data, so that efficient and stable model training data access is realized, the problem of low data storage and access efficiency in a large model training process is solved, and the model training efficiency and reasoning real-time performance are remarkably improved.

The invention provides a distribution network monitoring heterogeneous converged communication self-switching device and a distribution network monitoring heterogeneous converged communication self-switching method. The system comprises a communication module unit, a data processing unit and a switching execution unit. In the data processing unit, an environment sensing unit receives state data of the communication module unit, and a PICO unit processes link state data and uploads the link state data to an MCU unit for processing; the data encryption unit is used for encrypting and decrypting transmission data; the data caching unit is used for storing data transmitted during communication abnormity or switching and reissuing the data after communication recovery; and the MCU processing unit executes a link switching strategy according to the data processed by the PICO unit, and controls the switching execution unit to switch when detecting that the quality of the current main communication link is reduced to be below a preset threshold value. According to the invention, automatic and rapid switching in different network environments is realized, and the transmission stability and efficiency of the monitoring data of the power distribution network are remarkably improved.

The invention discloses a wireless communication network data secure transmission method and system, and relates to the technical field of secure transmission. During system operation, agricultural monitoring data are collected in real time through various sensor devices arranged in an agricultural environment, encryption processing is performed by using a symmetric encryption algorithm, and a dynamic key length adjustment mechanism is supported; a random number generator is integrated, unified management is performed on key generation, distribution, updating and destruction in a system, a timestamp or a random serial number is embedded into each data packet, the uniqueness of the timestamp or the serial number is verified at a receiving end, so that replay attacks are resisted, and the data are comprehensively analyzed and evaluated according to a set algorithm, so that the replay attack is prevented. The method comprises the following steps: acquiring a security data transmission performance index SDTP through calculation, generating a monitoring report, detecting abnormal conditions in a data transmission process, including channel quality reduction, data loss or verification failure, and providing a visual monitoring result.

The invention discloses a one-way optical shutter video stream transmission method based on weak supervision semantic segmentation, and belongs to the technical field of one-way optical shutter information transmission. Comprising the following steps: carrying out key region and background region classification and marking on all video data received by an optical shutter outer end through a weak supervision semantic segmentation model; performing priority division on a key region and a background region in the video frame; dividing the data packets according to time windows, and packaging the data packets; performing dynamic data compression and segmented coding on the packaged data packet; reed-Solomon redundant coding is carried out on all the data packets of the key area after compression coding is carried out on the data packets of the key area; dynamically adjusting the transmission sequence of the data packets to perform link scheduling; and a receiving end carries out de-encapsulation and data restoration, and reconstructs the restored video frame. According to the method, redundancy and compression of data transmission contents are accurately controlled, so that the transmission efficiency and reliability are remarkably improved, the bandwidth utilization is optimized, and the transmission reliability and stability are enhanced.

The invention relates to the technical field of data processing, in particular to a data transmission method and system for industrial edge gateways, and the method comprises the steps: obtaining industrial production equipment data, constructing a data queue, and obtaining the busy degree of each edge gateway based on the operation data of the data queue; according to the busy degree of each edge gateway, obtaining transmission results after the different data queues are transmitted to the cloud server, and calculating feedback rewards transmitted by the edge gateways by selecting the different data queues; and on the basis of the feedback rewards, using a UCB algorithm to calculate the confidence coefficient of each queue for transmitting data to the cloud server, and adjusting the data queue through which the edge gateway passes when transmitting the data to the cloud server according to the confidence coefficient. According to the method, the data transmission strategy is dynamically adjusted by monitoring the busy degree of the edge gateway and the transmission result of the data queue in real time, and rapid changes of task frequency, data volume and network conditions are better adapted, so that the data transmission efficiency is improved.

The invention provides a data encryption method and device, a computer program product and a data encryption system. The method comprises the following steps: acquiring initial data and a network transmission rate; according to the network transmission rate, the initial data is segmented to obtain data to be transmitted, and the size of the network transmission rate and the size of a data segment are in positive correlation; performing multi-layer encryption on the to-be-transmitted data to obtain encrypted data; and sending the encrypted data to the target terminal. According to the scheme, the problems that a single-layer encryption method in the prior art is easy to crack and the data security is relatively low are solved.

The invention discloses an electric power fault diagnosis and prediction system based on big data, particularly relates to the field of intelligent diagnosis of an electric power system, and aims to solve the problems of fault response delay and insufficient diagnosis precision. Localized intelligent diagnosis of power faults is realized, and stable operation and rapid recovery of a power system are guaranteed; a priority classification and sorting uploading mechanism is combined to ensure that key data is transmitted preferentially, diagnosis errors caused by delay are reduced, and the analysis stability of a central dispatching center is enhanced; through comprehensive judgment of a global deviation aggregation index and a trust stability harmonic measurement index, accurate classification of local node diagnosis controllability is realized, more accurate key data is guaranteed to be obtained, finally, the fault response capability of a system and the safety of a power system are improved, and powerful technical support is provided for intelligent diagnosis and maintenance.

The invention provides a regional target characterization method and device based on a global discrete grid, and relates to the technical field of global discrete grids. The method comprises the following steps: under the condition that a to-be-represented region target is a circular region target, determining three first grid codes used for identifying the circular region target based on the central latitude and longitude of the circular region target, the physical radius of the circular region target and a preset grid level; and under the condition that the to-be-represented region target is a polygonal region target, vertex extraction is performed on a polygonal region of the polygonal region target to obtain a plurality of extracted target vertexes, and second grid codes at the plurality of target vertexes are determined based on latitudes and longitudes of the plurality of target vertexes and a preset grid level. According to the invention, the number of grid codes for identifying the area target can be reduced, the data storage amount and the transmission data amount of the equipment are reduced, and the grid code transmission efficiency of the equipment is improved.

The invention discloses a distributed remote sensing method and device based on a satellite internet and a storage medium, and the method comprises the steps: receiving a remote sensing image obtaining request corresponding to a target region and sent by a user terminal through the satellite internet, and uploading a remote sensing image obtaining task to a first remote sensing satellite through the satellite internet and an inter-satellite link; remote sensing images corresponding to the target areas are collected respectively; based on the remote sensing image, generating a space confidence map corresponding to the first feature map, and determining a target feature image block in the first feature map; receiving target feature image blocks sent by the second remote sensing satellites, and splicing and fusing the plurality of target feature image blocks corresponding to the second remote sensing satellites and the first feature map to generate a second feature map; and transmitting the second feature map to the user terminal in real time through the satellite internet and the inter-satellite link. The technical effect of improving the distribution capability of the satellite for the remote sensing information and the distributed computing capability of the remote sensing task is achieved.

The invention relates to the field of power grid energy scheduling, in particular to a multi-microgrid intelligent energy scheduling method and system based on deep learning. The method comprises the following steps: acquiring a plurality of micro-grid multi-dimensional state parameters; performing multi-time-window change analysis on the multi-dimensional state parameters of the plurality of microgrids, and performing deep convolution learning to generate state convolution diagrams of the plurality of microgrids; identifying a plurality of microgrid nodes; performing node relative position analysis on the plurality of micro-grid nodes one by one, and performing node topological association mining to generate micro-grid node topological association representation; performing dynamic state attribute mapping based on the micro-grid node topology association representation and the state convolution graphs of the plurality of micro-grids, and constructing a micro-grid topology twinborn model; and performing power grid state trend evolution on the state convolution graphs of the plurality of micro-grids one by one, and performing energy demand prediction to generate a plurality of micro-grid energy demand prediction values. According to the invention, high-efficiency and high-utilization-rate energy scheduling is realized.

A foldable pushing chain type lifting platform belongs to the technical field of pushing chains and lifting platforms and comprises a meshed pushing chain system, an X-axis limiting mechanism and a Y-axis limiting mechanism, one side of the bottom of the meshed pushing chain system is fixedly connected with a base, the meshed pushing chain system outputs pushing chains upwards in the Z-axis direction, and the X-axis limiting mechanism and the Y-axis limiting mechanism are fixedly connected with the base. The top end of the pushing chain is fixedly connected with a top table used for bearing a lifted object, an X-axis limiting mechanism is further connected between the top table and the base, and the side, away from the meshing type pushing chain system, of the X-axis limiting mechanism is connected with a Y-axis limiting mechanism. The X-axis limiting mechanism is of a folding arm structure which only rotates around the X axis and limits the pushing chain and the top table to move in the X-axis direction. According to the invention, the pushing chain is used as a driving part, and the device has the advantages of high speed, large bearing capacity, high precision, long maintenance period, multi-point control, good stability, low initial height, large stroke, small occupied space and strong environmental adaptability.

The invention provides a digital person business card interaction method, electronic equipment and a storage medium, and belongs to the technical field of data processing, and the method comprises the steps: responding to a business card viewing instruction, and outputting a target digital person business card associated with the business card viewing instruction; receiving an inquiry instruction based on the target digital person business card, and judging whether the inquiry instruction has a corresponding standard problem or not; if yes, inputting an information set associated with the standard question and the target digital person business card into a pre-trained information desensitization large model; if not, calling a preset search engine to search the inquiry instruction, determining a search data set based on a search result, and inputting the inquiry instruction, the target digital person business card and the search data set into a pre-trained information desensitization large model; and obtaining a desensitization answer output by the information desensitization large model, and outputting the desensitization answer. According to the method, the interaction efficiency of the recruitment process can be remarkably improved, the hysteresis of information transmission is reduced, and the personal information security is protected.

The invention relates to the technical field of federated learning, and discloses a discriminator knowledge distillation personalized federated learning method based on a conditional generative adversarial network. The problems of appearance of massive participants and influence of non-independent identical distribution of data on federal learning data cost and personalized learning efficiency are solved; a discriminator knowledge distillation model fused with the conditional generative adversarial network is put forward to be embedded into a personalized federated learning framework; the differentiated feature representation of the client model is enhanced through the discriminator knowledge distillation model, so that the personalized model effectively recognizes and captures specific modes and features of individuals, the representation capability and the personalized effect of the model are enhanced, the higher model compression rate is achieved, and meanwhile, the user experience is improved. The conditional generative adversarial network fused with the discriminator generates synthetic data specific to each client, and the synthetic data improves the generalization ability of personalized federal learning and the adaptability of the model on the premise of fully ensuring the data privacy.

The embodiment of the invention provides a machine vision-oriented data processing method and device, equipment and a medium, and belongs to the technical field of visual data processing. The method comprises the following steps: inputting obtained initial visual information into a trained end side compression model, and performing different types of feature extraction on the initial visual information through a multi-level encoder to obtain corresponding types of encoding features under each level; carrying out vector quantization processing on each coding feature based on the visual codebook to obtain compression information of a corresponding type, so that after the edge cloud side system receives the compression information of each type, feature reconstruction is carried out on the coding features represented by the compression information of different types through a multi-level decoder; decoding features of corresponding types under each layer are obtained, and then target visual information matched with the initial visual information is obtained. The transmission efficiency of the visual data can be improved.

The invention relates to the technical field of solar cells, in particular to a perovskite solar cell, a preparation method thereof and a photovoltaic module. The invention aims to solve the problem that the cell performance is influenced by non-uniform coverage of the perovskite layer on the hole transport layer. For the purpose, the preparation method of the perovskite solar cell comprises the steps of preparing a hole transport layer on a substrate, preparing an interface modification layer on the hole transport layer, preparing a perovskite layer on the interface modification layer, and sequentially preparing an electron transport layer and an electrode on the perovskite layer to obtain the perovskite cell, the wettability of the hole transport layer can be improved by introducing 3-hydroxyphenylboronic acid into the adjacent interface of the perovskite layer and the hole transport layer, so that the coverage rate of the perovskite layer is increased, meanwhile, the 3-hydroxyphenylboronic acid is coordinated with metal ions in the perovskite layer, non-radiative recombination between the hole transport layer and the perovskite layer interface can be reduced, and the hole transport efficiency is improved. And the carrier transmission efficiency is improved.