113 results about "Context sensing" patented technology

A surveillance system and method includes a plurality of sensors configured to monitor an environment. A plurality of analytic engines is associated with each of the plurality of sensors. The plurality of analytic engines employs different technologies and is configured to analyze input from the sensors to determine whether an event has occurred in a respective technology. A unifying data model is configured to cross correlate detected events from the different technologies to gain integrated situation awareness across the different technologies.

A system for distributing information via short-range wireless communication. A mobile server receives information from an information provider for distribution to encountered devices. The information received from the service provider may contain both content to be distributed and context information that controls how the content is distributed. The mobile server may sense current environmental conditions, which are compared to distribution rules created from the context information to control how content information is distributed. The present invention is suitable for many applications, including the distribution of podcast-related information.

A mobile device is provided that includes at least one sensor that provides contextual information to the device. When the mobile device receives an incoming message, or notification, the device responds thereto based at least in part upon the contextual information.

A system for distributing information via short-range wireless communication. A mobile server receives information from an information provider for distribution to encountered devices. The information received from the service provider may contain both content to be distributed and context information that controls how the content is distributed. The mobile server may sense current environmental conditions, which are compared to distribution rules created from the context information to control how content information is distributed. The present invention is suitable for many applications, including the distribution of podcast-related information.

The invention discloses an improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM (KS-weighting matching region)). The improvement is reflected as follows: 1) confirming a candidate region by utilizing Kalman filtering; 2) fixing a camera or not by adopting different pedestrian detecting strategies; 3) proposing a pedestrian detecting method of an HLS (hue, lightness and saturation) model with multi-characteristic fusion; and 4) dividing pedestrians based on CA obvious region detection of context sensing. According to the invention, pedestrians can be recognized accurately under complex occasions of blur details, complex backgrounds, noise influences and the like. And the improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM) provided by the invention can be used for pedestrian detection and recognition at places with high visitor flow rate, such as remote sensing satellite images, malls, subway stations, railway stations, airports, as well as intelligent traffic control, intelligent vehicle auxiliary driving, pedestrian flow rate statistics and analysis places.

The invention discloses an individualized service recommendation system and a corresponding method including the following steps: various operation information existing on a terminal is monitored by a user information collector and after a pre-processing the operation information is stored in a user information database; and if the user information database is updated, a user behavior analyzer is started for analysis; the user behavior analyzer scans the user information database and extracts the new user information and stores the new information in a resource information database, and then new recommendation strategies are computed and stored in a recommendation strategy database; a context sensing processor senses the present context of the user and sends out the present context description information and an individualized recommendation processor is started; the individualized recommendation processor acquires the present context information after receiving the information from the context sensing processor and also acquires a matched optimal recommendation strategy by searching the recommendation strategy database and then matches the proper resource information according to the optimal recommendation strategy and by searching the resource information database so as to generate the individualized recommendation service in real time.

Disclosed is a context sensing application platform based on main body and a work method thereof, wherein the creation core of the invention is to supply a general-purpose processing model for obtaining context information, wherein the processing model comprises a gatherer communication module, a context information processing module, a management module, a knowledge information base, a context application processing module and a context sensing application platform of the context application processing module, when the application platform is supplied for sensing the context application, two mutually-independent and mutually-coordinated context information processing flows are proposed on how to use the context information processing steps, are mutually transparent, and share knowledge information through a synchronous control mechanism. The two processing flows are both on the basis of the context sensing and application platform of the invention, cover each flow of the context information processing, and reach knowledge sharing. The invention uses a main body to describe the context information, and reaches the universal share of knowledge information in the calculating field.

A system and method for vehicle collision mitigation with vulnerable road user context sensing. The system and method include determining one or more biosignal parameters and one or more physical movement parameters associated with a vulnerable road user (VRU). The system and method also include determining a context of the VRU based on the one or more biosignal parameters and one or more physical movement parameters associated with the VRU. Additionally, the system and method include determining one or more physical movement parameters associated with a vehicle. The system and method further include estimating a probability of collision between the VRU and the vehicle based on the context of the VRU, the one or more physical movement parameters associated with the VRU, and the one or more physical movement parameters associated with the vehicle. The system and method also include providing a human machine interface output response based on the estimation of probability of collision between the VRU and the vehicle, wherein the human machine interface output response is provided on at least one of the following: a head unit of the vehicle, a wearable computing device, and a portable device.

The present invention is directed to a presence and availability system including:(a) an input (e.g., an interface) operable to receive an agent report from a context sensing agent in a host entity associated with a person, the agent report comprising presence information and the person having an address in an associated name space;(b) a tracking agent 154 operable to tag at least some of the presence information with at least one classification tag; and(c) a policy agent 158 operable to determine presence information to be provided to a requester based on the at least one classification tag.

Disclosed is a context sensing-based intelligent mobile terminal field monitoring method. A monitoring system is arranged for monitoring. The monitoring system comprises a video acquiring end, a server end, and a video playing end, which are connected through a network. An intelligent mobile terminal acquires field video data and transmits the video date together with corresponding context data to the server end. The video playing end is connected with the server end through the network for checking videos and realizing the field monitoring. The method can allow real-time video acquisition and transmission at anytime and anywhere flexibly and conveniently and integrate context sensing information, such as filed video position information. Therefore, the interaction bottleneck is reduced; users do not need to classify the videos and add notes to the videos artificially; the searching and analyzing of the videos are facilitated; the system is enabled to have stronger adaptability; and the adoption of a mixed mode 3G mobile phone video transmission QOS strategy, the video quantity is good and the screen is smooth.

Aspects of the present disclosure relate to context aware stopping of a vehicle without a driver. As an example, after a passenger has entered the vehicle, the vehicle is maneuvered by one or more processors in an autonomous driving mode towards a destination location along a route. The route is divided into two or more stages. A signal is received by the one or more processors. The signal indicates that the passenger is requesting that the vehicle stop or pull over. In response to the signal, the one or more processors determine a current stage of the route based on a current distance of the vehicle from a pickup location where the passenger entered the vehicle or a current distance of the vehicle from the destination location. The one or more processors then stop the vehicle in accordance with the determined current stage.

A method, a system, and a server provide context aware multiple-input-multiple-output MIMO antenna systems and methods. Specifically, the systems and methods provide, in a multiple MIMO antenna or node system, techniques of antenna / beam selection, calibration, and periodic refresh, based on environmental and mission context. The systems and methods can define a context vector as built by cooperative use of the nodes on the backhaul to direct antennas for the best user experience as well as mechanisms using the context vector in a 3D employment to point the antennas in a cooperative basis therebetween. The systems and methods utilize sensors in the nodes to provide tailored context sensing versus motion sensing, in conjunction with BER (Bit Error Rate) measurements on test signals to position an antenna beam from a selection of several “independent” antenna subsystems operating within a single node, as well as, that of its optically connected neighbor.

The invention discloses a socialized convolution matrix decomposition-based document context sensing recommendation method. The method comprises the steps of firstly capturing context information of an article description document by utilizing a convolutional neural network (CNN), and taking obtained context eigenvector and Gaussian noise as potential vectors of a project; secondly, by utilizing acharacteristic that interests and hobbies of users are more easily influenced by trusted friends (having direct link relationships), determining a potential eigenvector of a target user by calculating an average value of potential eigenvectors of the friends; and finally predicting score information of the user for the project according to a joint probability distribution function of the user andthe project. According to the method, the CNN is seamlessly integrated in matrix decomposition technology-based socialized recommendation (SocialMF) from the perspective of a probability, so that thefriends having a trust relationship with the target user and interests relatively close to those of the target user can be further identified in a learning process, and the purpose of optimizing a recommendation result is achieved.

A method for providing context sensing and fusion may include receiving physical sensor data extracted from one or more physical sensors, receiving virtual sensor data extracted from one or more virtual sensors, and performing context fusion of the physical sensor data and the virtual sensor data at an operating system level. A corresponding computer program product and apparatus are also provided.

The invention relates to a rich internet application method based on Flex and web three-dimensional (3D) technology. The rich internet application method provides a Flex foreground display module, a Unity 3D programming module, a Flex and the Unity 3D communication module, a data transmission module, a data processing module, a user registration module, an uploading and downloading module and a data storage and retrieval module. Through adoption of a rich internet data transmission strategy based on context sensing, a system can automatically forecast a next action of a user, and carries out data transmission through utilization of network idle time. Page response time is greatly reduced, and user experience is improved.

The invention discloses a prompting method and device, and an electronic device. The prompting method is applied to the electronic device and comprises the steps of: acquiring a first parameter associated with a current state of the electronic device, wherein the first parameter is a non-time parameter; acquiring a prompt triggering parameter; judging if the first parameter and the prompt triggering parameter are satisfied with a preset condition, and obtaining a judgment result; when the judgment result shows that the first parameter and the triggering parameter are satisfied with the preset condition, acquiring a prompt message; and outputting the prompt message. By applying the invention, prompt based on the non-time parameter can be realized through context sensing, the prompting success rate is increased, the daily application need of people is satisfied, and a user is avoided forgetting again.

The invention discloses a context awareness recommendation system and method based on federal learning, and provides a user-defined data cooperation protocol module which is used for splicing user score data and context information to obtain user data containing the context information and sending the user data to a client. The client trains a local recommendation model according to the user data and the server weight parameters, and sends the local model weight parameters to a central server. The central server aggregates the local model weight parameters of all the clients to obtain new server weight parameters such that a round of training is completed. Te local recommendation model is trained for multiple times until the local recommendation model converges. The trained local recommendation model is used for processing the new user data to obtain recommendation content for the user. According to the method, the federal learning technology is applied to the recommendation system, and the context information is combined in the recommendation system, so that the privacy of the user is protected, and the recommendation accuracy is relatively high.

The invention discloses a support vector regression recommendation method based on context sensing. The method comprises the following steps: constructing a user characteristic attribute matrix; obtaining an item characteristic attribute matrix and an item characteristic attribute preference matrix, and constructing a user preference matrix; constructing a context situation matrix and a grading matrix, and constructing a context-based user preference model according to the context situation matrix, the user characteristic attribute matrix, the user preference matrix and the grading matrix; optimizing the context-based user preference model by virtue of a support vector regression SVR algorithm, so as to obtain an effective grading prediction model; and calculating the grades of items which are not bought by a target user based on the grading prediction model, and recommending front L items with the highest grades to the target user. The invention further discloses a corresponding system. The method and the system can be applied to the recommendation of supplementary services of civil aviation passengers, and services suitable for the passengers can be rapidly and accurately found from numerous services.

Methods, systems and apparatus are presented that can warn a machine operator of an object in a machine path when an operator is not looking in the machine travel direction. A situational awareness detector (SAD) can be configured to determine operator orientation and operator sight direction or field of view. A SAD can be configured to determine machine or implement travel path and whether an object of interest such as a boundary, pond, rock pile, etc. is positioned within the travel path. By comparing operator line of sight or field of view with machine and / or implement travel path, a SAD can determine operator awareness of the object in the travel path. If an operator is unaware of the object, an alert can be provided. If a determination is made that an operator is aware of an object, a system of the invention can refrain from providing an alert.

The invention discloses a music recommendation method and device based on context sensing. The method comprises the following steps: obtaining the context information of current equipment; according to the corresponding relationship of the context information and music characteristics, obtaining the music characteristics corresponding to the context information; and according to the music characteristics, obtaining the music, which is matched with the music characteristics, of a server side, and recommending the music to the music player of current equipment to be played. The device comprises an information acquisition module, a characteristic acquisition module and a music acquisition module. The context information of the equipment is associated with the music characteristics, the music characteristics of recommended music are determined according to the context information of the current equipment, and therefore, the method gets rid of personal experiences, does not depend on personal users and is suitable for general personalized service.

A system and method for vehicle collision mitigation with vulnerable road user context sensing. The system and method include determining one or more biosignal parameters and one or more physical movement parameters associated with a vulnerable road user (VRU). The system and method also include determining a context of the VRU based on the one or more biosignal parameters and one or more physical movement parameters associated with the VRU. Additionally, the system and method include determining one or more physical movement parameters associated with a vehicle. The system and method further include estimating a probability of collision between the VRU and the vehicle based on the context of the VRU, the one or more physical movement parameters associated with the VRU, and the one or more physical movement parameters associated with the vehicle. The system and method also include providing a human machine interface output response based on the estimation of probability of collision between the VRU and the vehicle, wherein the human machine interface output response is provided on at least one of the following: a head unit of the vehicle, a wearable computing device, and a portable device.

The invention discloses an Internet of Things environment control method and device based on context-aware. The method comprises the following steps: an environment control device in a network collects context-aware data to judge whether people are in a controlled zone or not; if people are in the controlled zone, the environment control device ensures that an intervalometer resets to a set time, humiture is processed by treating forecast average vote numbers as a PMV value, and then correspondence of the data is performed according to a set value table, a comfort degree mapping table and a control rule mapping table to obtain a control strategy of a controlled terminal; if people are not in the controlled zone, the environment control device detects whether a working controlled terminal exists or not, if no, no operation is carried out; if yes, the turning on or the turning off of the intervalometer is judged, if the intervalometer is turned off, the turning on of the intervalometer is performed, and when the intervalometer returns to zero, a control command is transmitted to close the working controlled terminal, if the intervalometer is turned on, countdown is performed continuously until the intervalometer returns to zero, or the controlled zone is detected again to ensure that whether people are in or not. The method and the device, provided by the invention, can realize intelligently real-time control of the controlled terminal to adjust the environment so as to meet comfort degree requirements of users.

The invention discloses a target sentiment analysis method and system based on an attention gated convolutional network, and the method comprises the steps: step 1, inputting a given context word vector and a corresponding target word vector, and enabling the given context word vector and the corresponding target word vector to serve as inputs for training; step 2, performing multi-head attentionmechanism interaction by utilizing the context words and the context sensing target words; step 3, enabling the sentiment feature vectors cintra and tinter generated by two channels to respectively pass through a gating convolution mechanism to generate a context word representation ai and a context word representation ui with context perception target word representations; step 4, pooling the emotion feature oi, and selecting the most representative feature; step 5, performing full connection on the pooled feature word vectors, and then performing classification through a Softmax classifier;and step 6, training and updating the attention gated convolutional network model by minimizing the cross entropy loss function. The accuracy can be effectively improved, the convergence time can be shortened, and the practicability is higher.

The invention provides a system for establishing access control policies in a private cloud environment. The system comprises a database (100), a context-sensing module (200), a local access control policy establishing module (300), a local access control policy optimizing module (400), a global access control policy establishing module (500), a global access control policy decomposing module (600), a sensitive information management module (700), a field information management module (800) and an auditing module (900). The system dynamically establishes the local access control policy in the private cloud environment, so that the established policy can meet requirements on dynamism and adaptivity of the private cloud environment; the system also realizes establishment and decomposition of a global access control policy which describes a composite service security requirement, so that the aim of avoiding leakage of sensitive information in the access control policy of a collaboration-participating service provider is achieved. The system has the characteristics of high security, high executing efficiency and high expandability.

The present invention relates to the sound symbol detection of context sensing. A low-power sound identification sensor is configured to receive an analog signal containing symbol sound, the sparse sound parameter information is extracted from the analog signal and is sampled periodically, and the context values are updated to indicate the current environmental condition. The sparse sound parameter information and the context values are compared by a symbol sound parameter database of the sound identification sensor stored locally to identify the sound or voice contained in the analog signal, so that the sound or voice identification is suitable for the current environmental condition.

A blood glucose measurement system is configured to detect a wireless communication channel in proximity to the measurement system. An electronic data management unit of the measurement system automatically identifies a source of the detected wireless communication channel and uses the source information based on a stored rule set to automatically adjust at least one feature relating to the measurement system for use thereof.

The invention provides a pest image classification method based on context sensing dictionary learning. The method comprises the following steps that: context sensing information of pest images in the known category is added into a pest image sample base to obtain a plurality of types of training samples, a learning function is constructed, and the training samples are used for completing pest image redundant dictionary learning; the pest images to be classified are subjected to preprocessing to obtain test samples; the test samples are subjected to sparse representation dimensionality reduction processing; the test samples subjected to the sparse representation dimensionality reduction processing are read into a sparse representation classifier, and the residual error of the context sensing information of the test samples and various types of the training samples is calculated according to a redundant dictionary obtained through learning; and the residual error of the context sensing information of the test samples and various types of the training samples is analyzed, and the categories of the test samples are determined. The pest image classification method has the advantages that the precision and the efficiency of the pest image classification in complicated scenes can be improved, and a traditional crop pest diagnosis mode is improved.

The invention discloses a target tracking method based on deep and shallow feature adaptive fusion and context information, and the method comprises the steps: firstly obtaining a first frame image ofa video image sequence, and building a deep feature model and a shallow feature model based on a context sensing framework; acquiring a plurality of second frame images of the video image sequence, and calculating a deep feature response and a shallow feature response of a corresponding tracking target by using the deep feature model and the shallow feature model; obtaining the position of the tracking target in the corresponding second frame image according to the response sum after the deep feature response and the shallow feature response are adaptively fused; judging the average peak related energy based on the threshold, and updating the deep feature model and the shallow feature model until the video image sequence is finished, so that the target can be effectively tracked, and theaccuracy is relatively high.

The invention relates to a self-adaptive subjective and objective weight context sensing system based on feedback and a working method thereof. The context sensing system comprises an original context information collection module, a context fusion module, a context reasoning module, a context application module and a user module. The user module is connected with the context fusion module. According to the context sensing system, a self-adaptive subjective and objective weight distribution mechanism based on user feedback is introduced into the context fusion module, contribution rates of subjective and objective weights of various context information are dynamically adjusted and optimized, the context information fusion accuracy and efficiency are improved, and the system can provide relatively intelligent and personalized service for a user.