791 results about "Smart technology" patented technology

The present invention provides systems and methods for dynamic detection and prevention of electronic fraud and network intrusion using an integrated set of intelligent technologies. The intelligent technologies include neural networks, multi-agents, data mining, case-based reasoning, rule-based reasoning, fuzzy logic, constraint programming, and genetic algorithms. The systems and methods of the present invention involve a fraud detection and prevention model that successfully detects and prevents electronic fraud and network intrusion in real-time. The model is not sensitive to known or unknown different types of fraud or network intrusion attacks, and can be used to detect and prevent fraud and network intrusion across multiple networks and industries.

A system and method for facilitating welding system diagnostics is provided. The invention includes a welder, a local system, a remote system, and / or an alarm component. The invention further provides for receiving sensor input(s), performing test sequence(s) based, at least in part, upon the sensor input(s) and / or performing internal diagnostics. The invention further provides for determining a health status of the welder and communicating the health status of the welder to the local system, the remote system and / or the alarm component. The health status of the welder can include welder alarm(s) and / or fault(s). Information regarding the health status of the welder can be sent by telephone, voicemail, e-mail and / or beeper. The welder can communicate with the local system and / or remote system to schedule maintenance. The invention further provides for a expert component to facilitate welding diagnostics based, at least in part, upon the health status of the welder, welder data, an expert data store, a local service support data store, a remote expert data store and / or a remote service support data store. The expert component can employ various artificial intelligence technique(s) (e.g., Bayesian model, probability tree network, fuzzy logic and / or neural network) to facilitate welding diagnostics based, at least in part, upon the health status received from the welder. The expert component can adaptively modify its modeling technique(s) based upon historical success (e.g., learn from success of previous welding diagnostics). The invention further provides for the welder, local system and / or remote system to initiate corrective action, at least temporarily, based, at least in part, upon the health status of the welder.

A method for structuring specialist system based on knowledge discovery includes forming new knowledge base unit by knowledge obtained from inference mechanism and knowledge learned from failure and mistakes, adding new knowledge obtaining-channel on said system, setting knowledge discovery process module in databank and setting knowledge discovery-creating mechanism and model in knowledge base.

The invention relates to the technical field of traffic control and artificial intelligence and provides a traffic signal self-adaptive control method based on deep reinforcement learning. The method includes the following steps that 1, a traffic signal control agent, a state space S, a motion space A and a return function r are defined; 2, a deep neutral network is pre-trained; 3, the neutral network is trained through a deep reinforcement learning method; 4, traffic signal control is carried out according to the trained deep neutral network. By preprocessing traffic data acquired by magnetic induction, video, an RFID, vehicle internet and the like, low-layer expression of the traffic state containing vehicle position information is obtained; then the traffic state is perceived through a multilayer perceptron of deep learning, and high-layer abstract features of the current traffic state are obtained; on the basis, a proper timing plan is selected according to the high-layer abstract features of the current traffic state through the decision making capacity of reinforcement learning, self-adaptive control of traffic signals is achieved, the vehicle travel time is shortened accordingly, and safe, smooth, orderly and efficient operation of traffic is guaranteed.

The invention relates to the artificial intelligence technical field, in particular to a text classification feature selection and weigh calculation method based on field knowledge. The method combines sample statistics and field glossaries to construct a filed classification feature space, utilizes internal knowledge relations in the field, calculates the similarity between the glossaries, and then adjusts the corresponding feature weight of classification feature vectors. Moreover, the method adopts a learning algorithm of a support vector machine to construct a field text classification model and then realize field text classification. As shown by text classification laboratory results of the Yunan tourist field and the non-tourist field, the classification accuracy of the method is improved by 4 percent compared with the text classification effect of the improved TFIDF feature weigh method.

The invention discloses an internet-facing filtration system of unhealthy information and a method thereof. The unhealthy information filtration system comprises a user data submission module, a user service management system, an auditing platform for user mutual information, an operation platform for purifying service, a knowledge base, and at least an indexing engine. The user data submission module is connected with the user service management system that is connected with the operation platform for purifying service. The operation platform for purifying service is connected respectively with the auditing platform for user mutual information and each indexing engine. The indexing engine is connected with the knowledge base. A plurality of intelligent technologies including word segmentation, keywords matching, and vector model as well as a plurality of processing algorithms with high performances are applied in the invention to process data. According to the invention, indexing services of information including sensitive information, erotic information, vulgar information, junk information, and commercial advertisements and the like are provided for the internet community, so that a high-efficient information management mean is provided for the client.

A method and system managing radio frequency identification (RFID) systems. The system monitors the performance of systems that use RFID tags and readers. It operates at multiple levels to ensure the optimal performance of readers, tags, antennae, and the information processing systems that acquire and convey tag data. The management system may employ artificial intelligence techniques such as genetic algorithms, fuzzy logic, neural networks, Bayesian networks, support vector machines or statistical methods to develop, maintain and exploit models of RFID system behavior. By comparing the actual performance of RFIDs and related components, the management system can detect and report failures and partial failures of components. The management system may also send signals to components to enhance performance of the overall RFID system.

The invention discloses a wisdom skynet video behavior analyzing system which comprises a plurality of front end video collecting systems and a central monitoring system. The central monitoring system comprises a plurality of video behavior analyzing servers, a storage server, a monitoring server and a client side, wherein each video behavior analyzing server receives video information of one front end video collecting system respectively, automatically analyzes all kinds of exception behaviors by the adoption of an advanced image analyzing processing technology, a computer vision technology, a computer network technology and an artificial intelligent technology and generates alarming signals, the video behavior analyzing servers are respectively connected with the storage server, the monitoring sever and the client end through an interchanger, and the monitoring server is further connected with a third party alarm linkage server. The wisdom skynet video behavior analyzing system is provided with multiple detection modules, users can selectively install certain modules according to actual needs, installation is convenient, the operation is simple, and video behavior analysis can be carried out automatically. A distribution type structure is adopted by the wisdom skynet video behavior analyzing system, and data transmitting and processing speed can be improved.

The invention discloses a deep learning computing system and method for cloud terminal edge computing fusion and relates to the fields of cloud computing, edge computing and artificial intelligence technology. According to the method, deep learning computing is distributed to a cloud terminal, a pipeline and an edge side, the cloud terminal is responsible for basic model training of a large historical data computing quantity, personalized model distribution is performed according to the demand of the edge side, nodes from the cloud terminal to the edge side deploy a deep learning model after learning, the deep learning model is used for completing inference, the edge side continuously feeds back an inference result, and then the inference result is uploaded to the cloud terminal to continuously optimize the model. Compared with the traditional mode that training and inference are both performed on the cloud terminal, in the whole deep learning computing process, the computing model iscontinuously optimized, personalized model distribution is performed according to the demand of the edge side, bandwidth is effectively utilized, network transmission efficiency is guaranteed, and real-time service execution efficiency is improved.

The invention relates to a plant growth chamber based on artificial intelligence technique and a control system thereof. The control system comprises an environmental parameter sensor, an environmental parameter transmitter, an artificial intelligence debugging device, an environment control driver and an environment control actuator, wherein a signal input terminal of the environmental parameter transmitter is connected with the environmental parameter sensor while an output terminal is connected with a signal input terminal of the artificial intelligence debugging device, the artificial intelligence debugging device configures the environmental conditions of the plant growth chamber through an expert system and according to plant types and experimental conditions, the environment control driver drives to starting or stopping devices in the environment control actuator, and the environment control actuator controls the environmental parameters to achieve target setting values. A framework, an upper cover mounted on the top of the framework, and a growth chamber body supported by the framework are detachably assembled. The plant growth chamber based on artificial intelligence technique and the control system thereof are capable of simulating different climates, provides favorable conditions for further study of influence law of physiological ecology caused by different environmental factors and compositions thereof, and has the advantages of large capacity, long service life and the like.

The invention is an electronic shelf (eShelf). The eShelf uses highly conductive electrodes to solve the long-line addressing problems using very-simple, low-cost manufacturing processes to build very-long, reflective, “no-power”, full-color, liquid crystal displays (LCDs) with perfect image retention. The electronic shelf is composed of an eSheet cholesteric LCD attached to a shelf product sensor pad that can turn a normal store aisle into an interactive, full-color, fun and informative shopping experience. The eShelf is the next generation of in-store smart technology combining product management with customer interaction and advertising. The true success of the eShelf will depend on the countless apps that will run on or interact with the eShelf to help customers make their purchasing decisions. These software applications will allow the eShelf to interact with the customers smart mobile device, such as, a tablet, smartphone, smartwatch, or Google Glass.

The invention relates to an examination room intelligence monitoring system and a method thereof. The system comprises: a signal input system, a signal pretreatment system, an examination room behavior single-mode state identification system, an examination room behavior multi-mode state decision and identification system and an examination room monitoring management background system. The signal input system sends a collected sound / video signal to the signal pretreatment system so as to perform pretreatment. After the pretreatment, the signal is sent to the examination room behavior single-mode state identification system and the examination room behavior multi-mode state decision and identification system so as to be performed classification identification and determination. Then a generated identification result is sent to the examination room monitoring management background system so as to realize a purpose of monitoring examination room behaviors. By using the examination room intelligence monitoring system and the method of the invention, an artificial intelligence technology can be used to process video information, audio information and sensor multi-mode state information simultaneously. And then suspected violation behaviors in the examination room can be identified so that an alarm can be given.

The invention discloses an intelligent household information system of an internet of things, which comprises a terminal device system, a secure transmission system, an information management system and an application system; the terminal device system consists of a hardware sub-platform, a system and software sub-platform, an internet of things sub-platform, a 3G sub-platform and an input and output sub-platform, and the system adopts delicate intelligent design, comprises an industrial automation technology, an intelligent technology and a network communication technology and realizes the fusion of two nets; and the sub-platform of the internet of things consists of infrared, Bluetooth, RFID, RS232, RS485, RJ45, USB, DB9, a DB25 common serial interface, a parallel interface, other interfaces and an SAM secure access module. The system does not need message sending or phone activation, realizes complete combination of security defense and household management, overcomes the problems of communication time delay, image effects, unitary instructions and functional defects, has low purchase, maintenance and working cost and truly realizes intelligent active household management.

The invention discloses an on-line transformer fault diagnosis method based on support vector machines (SVM) and dissolved gas analysis (DGA), which belongs to the field of transformer fault diagnosis. The method comprises the following steps of: acquiring the concentration of fault feature gases including H2, CH4, C2H2, C2H4 and C2H6 in transformer insulating oil by a gas chromatographic analysis method, normalizing the data through a preprocessing system, sending the data to a classification diagnosis system assembled by an integrative learning method and formed by six SVM classifiers according to a decision process, classifying the measurement data through calculation, judging the running state of the transformer, and at last outputting the diagnosis results. In the method, the support vector machines (SVM) of the artificial intelligence technology are adopted to analyze the gases in the oil, and the relation between gas components and the running state of the transformer can be objectively and essentially reflected, thereby the accuracy of fault diagnosis is effectively improved.

The invention provides an intelligent water-treatment microorganism machine vision identification system and a method. By using artificial intelligent technology, the system and the method can real-timely shoot microscopic images of microorganism in water and carry out the steps of automatic image pre-treatment, image segmentation, microorganism characteristic parameter extraction and selection, and microorganism classification and identification. The system and the method have the advantages that optimal segmentation threshold value can be searched automatically in HIS color space by using self-adaptive image segmentation algorithm; and the classifier is designed in a voting manner to obviate the low classification accuracy by using single classifier so as to effectively improve the entire classification accuracy and accurately identify microorganisms in drinking water and urban domestic sewage. The implementation of the method can further shorten the microorganism detection period in the water treatment process and accurately predict the condition of the water-treatment microorganisms to allow the operators to take measures in time. Accordingly, the method and the system can powerfully ensure the safety of drinking water and the normal operation of urban domestic sewage treatment facility so as to achieve considerable economic and social benefits.

A system and method facilitating lithography defect solution generation is provided. The invention includes a defect solution component and a defect alert component. The defect solution component provides potential solution(s) to a defect within the lithography process utilizing artificial intelligence technique(s) (e.g., Bayesian learning methods that perform analysis over alternative dependent structures and apply a score, Bayesian classifiers and other statistical classifiers, including decision tree learning methods, support vector machines, linear and non-linear regression and / or neural network).

The present invention discloses a cancer pathology auxiliary diagnosis method based on an artificial intelligence technology. The method comprises the following steps of: canning a plurality of digital pathology images of a system into a computer, performing marking of diseased areas by pathologists to form a digital pathology image database; performing preprocessing of the digital pathology images to form a data set for algorithm training, performing sample collection, and forming a data subset for training; allowing a full convolutional network to use the data subset for training to performiteration training to regulate parameters, and constructing an artificial intelligence analysis module; scanning diagnosis pathology images, and decoding the diagnosis pathology images to access the artificial intelligence analysis module; and performing diagnosis and marking of the diagnosis pathology images by employing the artificial intelligence analysis module, and performing feedback of themarked pathology information to doctors. The cancer pathology auxiliary diagnosis method based on the artificial intelligence technology is high in diagnosis accuracy and can effectively assist doctors in discrimination of cancer pathology information.

The invention belongs to the technical field of computer vision and artificial intelligence, and particularly relates to a large-scale face recognition method based on a depth convolution neural network model. The method comprises steps of putting forward a residual error learning depth network model facing large-scale face recognition, wherein the residual error learning depth network model is formed by a convolution layer, a residual error layer and a full connection layer, and the residual error layer is formed by adding one path of multiple convolution layer cascade data and one path of original data to calculate the sum; and carrying out normalization operation in batch after each convolution layer in the model. According to the invention, by use of the characteristics of strong learning ability and good residual error learning convergence of the depth convolution neural network, layers of the model are increased in the aspect of the layer number of the network model; and in the aspect of residual error layer structure, the invention provides a highly efficient residual error layer structure. In the field facing the large-scale face recognition, the accuracy of the provided method is greatly improved compared with a base line model, and the accuracy of face retrieval in a million-class face recognition database can reach 74.25%.

The invention discloses an intelligent dialogue method and apparatus which relate to the technical field of artificial intelligence and are invented for solving the problem that intelligent dialogue can be realized only by enabling a user to clearly ask a question. The method comprises the steps of searching for a preselected dialogue scene, wherein the dialogue scene comprises at least one topic corresponding to the dialogue scene; sending guide information corresponding to the topic to a client, so that the client can perform voice type question-asking according to the guide information; receiving reply information sent by the client; judging whether the reply information is in a preset range of the topic corresponding to the dialogue scene or not; if a judgment result is that the reply information is in the preset range, continuing to send the guide information to the client according to the topic corresponding to the reply information; and if the judgment result is that the reply information is not in the preset range, sending the guide information to the client according to a preset scene skip rule. The method and the apparatus are mainly applied to a man-machine dialogue process.

The invention discloses a fault diagnosis and prediction method for a numerical control machine tool spindle, and belongs to the field of numerical control machine tools. The method includes the following steps of database establishment, signal acquisition and analysis, fault diagnosis and fault prediction. Advanced artificial intelligence technologies such as a nerve network, an expert system and a support vector machine are used for conducting fault diagnosis and prediction, measured data transmitted from a high-precision laser displacement sensor, an infrared temperature sensor and an acceleration sensor are rapidly analyzed through a mixed reasoning model, fault sources are effectively inferred and fault diagnosis and prediction of the numerical control machine tool spindle are conducted in the running process of the numerical control machine tool spindle according to numerical control machine tool spindle models established by various machine tools, and therefore the fault diagnosis accuracy and efficiency of the numerical control machine tool spindle are greatly improved, relative prediction is conducted on the tendency of the state of the numerical control machine tool spindle, and the maintenance cost of the numerical control machine tool spindle is effectively reduced.

The invention relates to a fault diagnostic expert system for a marine electrical propulsion system and an establishing method thereof and belongs to the technical field of artificial intelligence. According to the invention, an artificial neural network technology is introduced into the expert system design to establish the fault diagnostic expert system for the marine electrical propulsion system; the fault diagnostic expert system for the marine electrical propulsion system mainly comprises a man-machine interface module, a neural network module, a knowledge maintenance module, a data management module, a data acquisition module and a database. According to an operation principle and a typical fault mechanism of each equipment of the electrical propulsion system, the invention discloses a design method of a fault diagnosis knowledge base for the electrical propulsion system. The fault diagnostic expert system for the marine electrical propulsion system and the establishing method thereof have the advantage that the expert system structured by applying an artificial neural network solves the problems of knowledge acquisition bottleneck, knowledge maintenance difficulty, low reasoning speed and the like of a conventional expert system, and the practicality of the fault diagnostic expert system is improved.

The invention discloses a model generation method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, in particular to the technical field of deep learning. The specific implementation scheme is as follows: determining data used for model training according to a detected first user operation acting on a current application interface; performing model training based on the data through a deep learning framework module integrated in the current application; and generating and outputting a code file corresponding to the trained model according to the model deployment environment. According to the embodiment of the invention, the client can be visualized by integrating the application of the deep learning framework; therefore, adeveloper only needs to operate on the application interface to realize model training; a developer can realize model training based on a deep learning framework without knowing about program development and mastering related interface and parameter adjustment mode details of a deep learning framework program, and then a code file of the trained model is obtained, so that the model training efficiency is improved, and the workload is reduced.

The invention relates to an integration method of collaborating the assembly design, the process planning and the simulation verification of a complicated product, belonging to the research contents of a modern manufacture integration technology in the technical field of advanced manufacture. The invention provides technical methods and decision supports for remotely collaborating the assembly design, the analysis estimation, the planning optimization and the assembly process simulation of the complicated product, stimulates the organic integration of the assembly design and the assembly process, comprehensively utilizes a digital design and manufacture technology, a network technology and an artificial intelligence technology and provides the method for collaborating a human-computer collaboration working mode and a human-human collaboration working mode and collaborating the assembly design, the analysis estimation, the planning optimization the assembly simulation of the complicated product and finally realizes the multi-subject collaborative optimization design of the product-developing process. To a certain degree, the invention solves the problem of difficulty for collaborating and integrating the assembly design, the process planning and the simulation verification of the complicated product and provides an effective path for closely integrating the assembly design and the assembly process.

The invention belongs to the technical field of artificial intelligence, and provides a teaching method based on the AR (augmented reality) technology, a cloud service platform and a teaching system,wherein the method comprises the steps: transmitting structured knowledge contents to a physical robot and a user terminal based on a knowledge map; receiving image information and voice information,collected by the physical robot, of a real scene, respectively performing facial expression recognition and voice emotion recognition of the image information and the voice information, and acquiringfacial expression information and voice emotion information; performing the fusion calculation of the facial expression information and the voice emotion information to obtain real emotion informationof a user; adjusting the knowledge contents presented to the user in real time according to the real emotion information of the user, thereby solving a technical problem of a poor teaching effect ofthe robot in the prior art.

An NIPS (Network Intrusion Prevention System) adopts the structure that an NIPS framework in linkage with a cloud / fire wall is connected to a cloud security. The cloud security technology, the artificial intelligence technology and the network invasion prevention technology are combined together by adopting a novel design concept and manner. The novel technical characteristics of the cloud security are utilized to combine with the advantages of real-time extraction, interactive coordination and linkage and abnormal information identification of the dynamic cloud / fire wall technology, so that the detection and identification accuracies, the dynamic interactive coordination and linkage performance and the intelligent blocking decision-making performance are improved, false alarm and high alarm loss rate are avoided, and both the key technology and the core problems in integral dynamic defense and detection of the computer network security are well solved, accordingly, the safe reliability and integral dynamic linkage defense capability of the computer network are improved.

The present invention relates to tactile warning panels, and in particular to tactile warning panels that are designed and built with multifunction / multipurpose capabilities that serve the visually impaired and enable the deployment of smart city technology by integrating tactile warning systems and subsurface enclosures that can withstand pressures of five (5) tons up to and exceeding sixty (60) tons and incorporate small cells, beacons, sensors, Fog Computing, electric energy generation, rechargeable power supplies, wireless M2M communication and a plethora of other smart city technologies.

The invention relates to an intelligent video director method based on microphone array sound guidance, belonging to the field of intelligent technology. The method comprises the following steps of: photographing several positions of a space / region by the user and taking the photos as demonstrations and memorizing the photos in a training set; collecting the sound in the space / region by a microphone array; analyzing the audio data of each microphone by a sound source localization method to locate the positions of the sound source; referring to the training set to calculate the photographing parameters of the camera / high-speed balls corresponding to the positions of the sound source by a K-neighbor method; and guiding the camera to photograph by the given parameters. The method can alternatively capture corresponding target videos automatically, needs not to measure or collate the position of the camera, and has excellent adaptability to the environment; the specified range GCC-PHAT time delay computation method and the least square method position-computation method adopted by the method have a certain immunity to the noise interference so that the method can inhibit the interference of the corresponding noise well.

The invention discloses an artificial intelligence machine learning experiment skill scoring system, and particularly relates to the technical field of artificial intelligence. The artificial intelligence machine learning experiment skill scoring system comprises a hardware architecture and a software architecture, the hardware architecture is composed of a laboratory end device and a server machine room device, and the software architecture is set as a distributed micro-service hierarchical architecture. According to the invention, the cameras with multiple visual angles are adopted to acquire experimental operation video data of students; artificial intelligence technologies such as deep learning, Pattern recognition, Image processing, natural language processing, special intelligent experiment equipment and informationized electronic test paper are matched to achieve automated scoring, meanwhile, the system stores the experiment operation video and the scoring result; A teacher canlog in the system through the Internet to manually recheck an intelligent scoring result error, an automatic scoring result can be autonomously learned through a deep learning algorithm, the accuracyof automatic scoring is improved, and students can carry out score query and dispute processing through the Internet.

The invention discloses a realization method of intelligent non-player characters in an interactive game, the method controls the intelligent behaviors of the non-player characters through a game engine at a server end, a network application programming interface containing JavaBot, a JavaBot bottom-layer processing unit, as well as client ends of a BDI reasoning unit. In addition, the invention also discloses an interactive game system to realize the method. The invention has the advantages that the game engine increases one layer of the game Agent unit, which can make the game developers work with AOP way when programming and processing NPC behaviors without considering the implementation details. Therefore, such the intelligent NPC realization system can be more helpful to express the intelligent behaviors of non-player characters in the game, as well as better support the application of intelligent technology in the game.

The invention relates to an intelligent control device for inspection and maintenance of automobile, which belongs to a technical field of communication and artificial intelligence. The intelligent control device for inspection and maintenance of the automobile comprises a vehicle-mounted unit connected with a motor control network which is connected with a monitoring service system of a motor repair center (comprising a communication gateway) in a wireless way by a GSM network. The vehicle-mounted unit is arranged on the controlled automobile and is communicated with the monitoring service system through the GSM network; the communication gateway takes charge of the wireless communication of the vehicle-mounted unit and the monitoring service system; the monitoring service system is the core of the system, which can carry out human-computer interaction, intelligent fault diagnosis, remote control, etc. The device has the advantages of carrying out failure warning, maintenance suggestion, remote control, fault diagnosis, etc., thus providing various fast, convenient and more humanized services for users.