345 results about "Global Positioning System" patented technology

The invention discloses a mobile phone anti-theft system and method based on a camera and a GPS (Global Position System) of a mobile phone. The mobile phone anti-theft system comprises a mobile phone CPU (Central Processing Unit), a microprocessor, a camera driving module, an input module and an unlocking detection module, wherein the input module is connected with the unlocking detection module; the unlocking detection module is connected with the mobile phone CPU; and the mobile phone CPU is connected with the camera driving module through the microprocessor. Compared with the prior art, the mobile phone anti-theft system and method provided by the invention have the advantages as follows: an unlocking operation is carried out when the mobile phone is used after the mobile phone is lost or stolen, and a background operation program which is installed in the mobile phone is triggered and started when the unlocking operation is inaccurate; and a user who currently uses the mobile phone is positioned and photographed through a GPS module and the camera of the mobile phone; meanwhile, obtained information is sent to a mailbox or other addresses which are specified by the user in time, so that the user is convenient to alarm and can find the mobile phone back accurately in time, and the problems of the mobile phone loss and personnel information release of the user can be solved.

The invention discloses an ultra-wideband laser radar inertial navigation cooperative SLAM (Simultaneous Localization and Mapping) method and system, which are suitable for robot positioning and mapping tasks in a GPS (Global Positioning System)-free environment. According to the method, high-frequency motion priori of an IMU, relative pose constraint of LiDAR and absolute ranging information of UWB are fused, a unified factor graph optimization model is constructed, and multi-sensor cooperative positioning is realized; in the system initialization stage, IMU bias calibration, UWB base station coordinate configuration and LiDAR initial attitude estimation are completed; in the operation process, IMU pre-integration is utilized to predict the pose, LiDAR point cloud registration is utilized to obtain the relative motion between key frames, UWB ranging is combined to construct a residual item, a self-adaptive weight mechanism is introduced to suppress ranging abnormity, and the fusion robustness is improved; the system supports geometric feature loopback detection, cross-frame constraints are constructed in combination with UWB to carry out closed-loop optimization, and an optimization result is used for real-time incremental updating of a global map; the method has the advantages of high positioning precision, strong anti-interference capability, wide application scene and the like.

The invention relates to the technical field of aerospace, in particular to low-altitude traffic flow airspace-oriented real-time planning, and provides a centimeter-level precision detection network covering a low-altitude airspace by integrating multi-dimensional data sources such as radar electromagnetic feature recognition, ADS-B (Automatic Dependent Surveillance-Broadcast) automatic monitoring, Beidou or GPS (Global Positioning System) space-time reference positioning and the like. The three-dimensional trajectory and motion situation of the aircraft are solved in real time, intelligent reconstruction of an airspace sector and adaptive optimization of a flight corridor are realized by adopting a dynamic programming algorithm driven by reinforcement learning based on the real-time pose data of the aircraft, and a flight conflict prediction model constructed by combining a space-time convolutional neural network is used for predicting the flight conflict. According to the method, potential risks can be pre-judged, an optimal avoidance path can be generated, full-process digital management and control from identity verification to airspace authorization can be realized by constructing an aircraft digital identity authentication system and a dynamic access control mechanism, and modules such as a three-dimensional navigation information service module, a low-altitude digital communication private network module and an intelligent early warning and warning system module are integrated. And the guarantee of full-life-cycle service is provided for the low-altitude aircraft.

A system of a vehicle for processing communication with connected objects is provided. The processing by the system uses a processor of the vehicle and processing and data from one or more servers of a cloud system. The connected objects include objects having communication capabilities that are either fixed at specific locations as infrastructure proximate to where the vehicle is located or locations proximate to where the vehicle is moving. The system includes a global positioning system of the vehicle for generating geo-location for the vehicle and a heading direction. The geo-location is shared with a server of the cloud system using a communications device of the vehicle. The server of the cloud system is configured to receive the geo-location of the vehicle to identify the heading direction of the vehicle. The communications device of the vehicle is configured receive state data from at least one of said connected objects.

The invention discloses an unmanned aerial vehicle cluster intelligent cooperative positioning method and system based on machine learning, relates to the technical field of artificial intelligence and unmanned aerial vehicles, and aims to solve the problems that positioning signals are attenuated and drifted and the spraying precision is affected due to spray droplets of unmanned aerial vehicles in agricultural plant protection. According to the scheme, multi-source heterogeneous sensor data of a global positioning system, an inertial measurement unit, vision, ultra wide band and the like are acquired through each unmanned aerial vehicle in a cluster and are locally estimated; the central node cooperatively aggregates data, models fogdrop interference such as fogdrops by using a deep learning model, and dynamically corrects sensor noise; according to the method, the positioning robustness, the positioning precision and the self-adaptability are remarkably improved, and the spraying precision in a complex environment is ensured.

The invention discloses a construction site three-dimensional modeling method based on multi-sensor fusion. The method comprises the following steps: synchronously acquiring data by using a laser radar, a camera, an infrared sensor, a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit); the method comprises the following steps of: performing denoising and filtering operation on collected original data, aligning a timestamp and a space of the collected data, fusing the collected multi-source data, and aligning and fusing the processed multi-source point cloud data through a point cloud registration and fusion algorithm to generate a complete three-dimensional point cloud model; generating a grid model by using a surface reconstruction algorithm based on the point cloud data, and performing texture mapping in combination with texture information collected by a camera; the model is simplified and the precision of the model is improved through a model optimization technology, and a reliable three-dimensional visualization foundation for construction management and analysis is formed; real-time detection and modeling of dynamic targets such as mobile equipment and workers on a construction site are realized, and the real-time response capability of the system in a complex construction site environment is ensured through combination of a lightweight neural network architecture and an edge computing technology.

The invention discloses a cross-scale self-supervised spatio-temporal trajectory basic model training method, which comprises the following steps of S1, preprocessing original GPS (Global Positioning System) data to obtain trajectory data of different spatial granularities; s2, encoding the trajectory data of the spatial granularities to obtain trajectory representations corresponding to the spatial granularities; s3, on the basis of the trajectory representation of each spatial granularity, randomly selecting a part of elements to execute mask operation, and calculating the difference between the predicted trajectory data and the real trajectory data as mask reconstruction loss; s4, performing comparative learning training on the positive sample pair and the negative sample pair to construct comparative learning loss; s5, performing dynamic fusion on the trajectory representation of each spatial granularity and the importance weight to obtain a unified representation after trajectory fusion; and S6, performing weighted summation training on the mask reconstruction loss and the contrast learning loss through weight hyper-parameters to obtain total training loss of the model, updating model parameters to convergence by adopting a gradient descent algorithm, and generating a pre-training model.

A client device includes: a display device that includes a touchscreen; a camera; a global positioning system (GPS) device; at least one processor; and a memory that stores a plurality of photographs generated by the camera, application data corresponding to a plurality of applications including at least one application that facilitates storage and selective deletion of the photographs based on subsets of photographs containing images of different people, subsets of photographs taken at different locations and subsets of photographs containing images of particular groups of people.

The invention provides a binocular vision global positioning system and method for a mobile robot, and relates to the technical field of robot vision navigation, and the method comprises the steps: carrying out the adaptive exposure compensation of binocular images of a left camera and a right camera, extracting edge contour feature points irrelevant to illumination, and generating a high-quality depth feature map through the combination of parallax calculation; meanwhile, feature units are constructed according to the inflection points, so that the global position of the mobile robot is determined. Therefore, the problem that the global positioning precision is reduced due to unstable visual feature extraction caused by rapid change of illumination intensity of the mobile robot in a multi-region switching scene can be solved to a certain extent.

A system for forming and maintaining GPS tracked and mapped environmentally-clean chemical-based fire protection zones formed over property and ground surfaces in and about a neighborhood of homes, that proactively inhibit fire ignition and flame spread when exposed to wild fire. The system includes a GPS-tracking anti-fire (AF) liquid spraying system wirelessly connected to a wireless communication network supporting a network database. The GPS-tracked anti-fire liquid spraying system is used to spray particular GPS-specified ground surfaces in and about the neighborhood, with an environmentally-clean anti-fire chemical liquid so to form environmentally-clean chemical fire protection zones over the GPS-specified property surfaces, while generating GPS-coordinate and time / date stamped data records pertaining to the application of the environmentally-clean anti-fire chemical liquid spray during the formation of the environmentally-clean chemical fire protection zones. The GPS-coordinate and time / date stamped data records are transmitted over the wireless communication network for storage in the network database. A mobile computing system is used to access the GPS-coordinate and time / date stamped data records from the network database, relating to the formation of the GPS-specified environmentally-clean chemical fire protection zones, so as to verify that the GPS-specified environmentally-clean chemical fire protection zones were formed at the GPS-specified property surfaces on the particular date, to proactively inhibit fire ignition and flame spread when exposed to wild fire.

Described herein are unmanned aerial vehicles (UAVs) and antenna assemblies thereof for shaping radiation patterns in global positioning system applications. For example, an embodiment pertains to an antenna assembly onboard an aerial vehicle. The antenna assembly includes a radiating element coupled to a chassis of an aerial vehicle and positioned in parallel with the chassis, a substrate coupled to the radiating element, a ground plane coupled to the substrate, and a feed cable coupled to the radiating element through the substrate and the ground plane. The ground plane includes a center portion in parallel with the chassis and with the radiating element, and side portions positioned at an angle relative to the chassis and to the radiating element.

A hydrofoil board having a hydrofoil configured to be automatically controlled to stabilize the board in a level position even when incurring waves. The hydrofoil includes a pair of individually controllable flaps that control the pitch and direction of the hydrofoil board when propelled in motion. A processor uses an inertial measurement unit (IMU) to obtain orientation and acceleration information of the hydrofoil board. A global positioning system (GPS) unit is also used as an additional speed and location sensor. The processor combines IMU data with a user / rider's input, such as selected speed and direction via handheld wireless controller, and individually controls the flap motors to position the flaps, and the propulsion motor to set speed. In one example, the controller is configured to bring the hydrofoil board to a complete and stabile stop.

A sonar target locking system to position a sonar assembly to maintain the sonar array of the sonar assembly pointing at a position of a user-set (desired) target even when the watercraft is rotating or moving in various motions. The sonar target locking system includes electro-mechanical assembly that can be steered electrically to maintain the sonar array pointing at the position of the desired target. The system may be activated using at least one of a foot pedal, handheld remote control, or a display of a fish finder head unit. The system may use GPS and IMU inputs to generate control signals to steer the electro-mechanical assembly to maintain the sonar array pointing at the position of the desired target.

A high-altitude platform and method for in-flight navigation, the platform comprising a ground-facing camera and a computing device including a memory and a processor, the memory storing instructions which when processed cause the computing device to perform a position determination method, comprising: acquiring one or more images from the ground-facing imaging device; retrieving, from an image dataset associated with a trained model, a plurality images associated with an area of interest; processing, using an image comparator, the acquired one or more images and the retrieved images associated with terrain of interest to derive therefrom respective acquired image feature sets; using a loss function, comparing each acquired image feature set to each retrieved image feature set to identify for each acquired image a corresponding matching retrieved image; using the matched image and the optical characteristics of the ground-facing camera, determining the position of the platform.

A method for labeling vehicular sensor data includes accessing sensor data captured by a plurality of sensors disposed at a vehicle. The method also includes accessing global positioning system (GPS) sensor data of the vehicle. For each time step of a plurality of time steps associated with the sensor data, vehicle position information is extracted from the GPS sensor data that represents a respective geographic location of the vehicle at the respective time step. For each time step of the plurality of time steps of the recording of sensor data, respective location-based information associated with the respective geographic location of the vehicle at the respective time step is obtained from a database. For each time step of the plurality of time steps of the recording of sensor data, the recording of sensor data at the respective time step is labeled using the respective obtained location-based information.

The present invention relates to method and system for controlling speed of vehicle by using GPS location, real-time traffic light status and machine learning techniques to recommend cruising speed to vehicle without stopping at the traffic lights. The method includes determining status of traffic lights located on route of traffic junctions and associated time period for status of traffic lights based on data received from sensors. The method includes broadcasting status of traffic lights and associated time period. The method includes calculating in real-time a recommended cruising speed of the vehicle based on GPS location associated with vehicle, status of traffic lights and associated time period, and a time period required by vehicle to arrive at the traffic lights using machine learning techniques. The method includes providing in real-time the recommended cruising speed to vehicle. The method includes adaptively controlling in real-time speed of vehicle to recommended cruising speed.

The invention relates to the technical field of dam termite prevention and control in water conservancy and hydropower engineering, in particular to a dam termite nest positioning method and detection equipment based on intelligent multi-mode fusion, which utilizes technologies such as geological radar, infrared thermal imaging, RTK (Real Time Kinematic) and GPS (Global Positioning System) positioning and is assisted by a machine learning algorithm to carry out data processing. An infrared thermal imaging camera carried by a crawler chassis is used for rapidly scanning the surface of a dam and finding out temperature abnormal points which may be termite activity areas, an underground high-resolution image is further obtained through a carried ground penetrating radar, meanwhile, coordinate information of the areas is collected, a high-precision dam area map is combined, and the termite activity area is obtained. The termite nest position is further accurately confirmed; by means of the method, the accuracy and efficiency of dam termite nest positioning can be remarkably improved, meanwhile, the environmental pollution risk caused by a traditional method is reduced, and the method is beneficial to protection of safe and stable operation of a water conservancy project and makes a contribution to environmental protection.

The invention is suitable for the field of farmland weed treatment, and provides an unmanned vehicle-mounted remote sensing detection-based farmland early weed identification method, which comprises the following steps of: constructing an unmanned vehicle-mounted remote sensing detection system and acquiring a multispectral image, a thermal infrared image and GPS (Global Positioning System) data; data transmission and preprocessing of the multispectral image and the thermal infrared image are carried out; carrying out weed recognition on the preprocessed image by using a weed recognition algorithm; experiments prove that the weed recognition result method greatly improves the monitoring efficiency, is especially suitable for large-scale farmland, reduces herbicide abuse, and gives consideration to both production benefits and environmental protection. The technology can effectively reduce resource competition between crops and weeds, directly improve the yield and quality, and reduce manpower and pesticide cost at the same time. And the data can be integrated into a precision agricultural system to promote the implementation of technologies such as variable fertilization and intelligent irrigation. In addition, the flexibility of the unmanned system enables the unmanned system to adapt to complex terrains, and a new solution is provided for organic agriculture and breeding test fields.

The invention discloses a concrete dam crack inspection method based on an unmanned aerial vehicle carrying an infrared combined optical camera. Core equipment comprises a multi-rotor unmanned aerial vehicle carrying a global positioning system, an infrared thermal imager and a high-resolution optical camera. The invention aims to improve the concrete dam crack detection efficiency and accuracy. According to the method, an infrared camera and an optical camera are carried by an unmanned aerial vehicle to obtain dam surface temperature distribution and visible light images. By means of the infrared thermal imaging technology, a thermal abnormal area caused by the crack can be recognized, and the optical camera provides fine crack form and position information. In the inspection process, an infrared thermal imaging instrument is used for detecting the whole dam and positioning an abnormal area, and then a method of combining the infrared thermal imaging instrument and an optical camera is used for respectively detecting internal and external damages of the abnormal area. The method overcomes the problems of high labor cost, low detection efficiency and difficulty in complete coverage of a traditional inspection method, is especially suitable for rapid and accurate detection of large-area concrete dam surface cracks, and provides effective technical support for safety maintenance of dams.

A system for a host vehicle operating on a road surface includes a polarimetric camera, a global positioning system (“GPS”) receiver, a compass, and an electronic control unit (“ECU”). The camera collects polarimetric image data of a drive scene, including a potential driving path on the road surface. The ECU receives the polarimetric image data, estimates the Sun location using the GPS receiver and compass, and computes an ideal representation of the road surface using the Sun location. The ECU normalizes the polarimetric image data such that the road surface has a normalized representation in the drive scene, i.e., an angle of linear polarization (“AoLP”) and degree of linear polarization (“DoLP”) equal predetermined fixed values. The ECU executes a control action using the normalized representation.

Provided is a smart stroller including a stroller, master control module and power control module. The stroller includes a chassis support, a front wheel support which two front wheels are disposed at, a rear wheel support which two rear wheels are disposed at, a seat, handle, guardrail and canopy. The master control module is disposed on a base of the handle of the stroller. The master control module includes a controller, brake controller, first wireless communication device, and global positioning system. The power control module is disposed at the bottom of the rear wheel support and includes a second wireless communication module, power source module, foot brake component, drive motor, deceleration mechanism, and drive controller. The smart stroller is applicable to a global positioning system and an anti-theft system and capable of performing video surveillance, automatic braking, music playing and storytelling to ensure user safety and captivating user experience.

The present application refers to a process and a system for collecting, storing, analyzing and visualizing electrocardiographic (ECG) data collected by portable ECG device (100) with embedded wireless communication technology, additionally containing a portable ECG device (100), a hermetically sealed box (200) of medicines containing a lock system comprising a lock (220), a first device (310) to be accessed by the patient, a second device (320) to be accessed by the medical professional, a platform for graphical display of ECG data, and a remote data storage and processing central. The hardware board of the portable ECG device contains wireless communication technology, global positioning system (GPS), start button (141), rechargeable battery charging port, and an equipment configuration and programming port. The battery (120) is Li-Ion type, containing LEDs indicating device operation, and waiting for connection. The battery status is displayed on the app display. In one embodiment, an electrode (130B) is positioned on the bottom cover (110B) of the housing (110A, 110B, 110C) of the ECG device (100).

A system and method for locating a trailer hitch on a trailer to facilitate coupling the trailer hitch to a vehicle's towing device. The system includes a human-machine interface, a camera, a global positioning system, a remote computing system, a vehicle-to-infrastructure communication network, controllers, memory, sensors, and an application for trailer hitch identification.The application for marking trailer hitches includes: capturing a coupled and / or uncoupled state of the trailer hitch, recording optical data with the camera when the vehicle trailer hitch is in the coupled and uncoupled states, determining a distance of the trailer hitch relative to the camera when the vehicle trailer hitch is in the coupled state, identifying the installation location of the trailer hitch on an image defined by the recorded data, and creating a marker on the image of the trailer hitch.

A detection system for a host vehicle includes a camera, global positioning system (“GPS”) receiver, compass, and electronic control unit (“ECU”). The camera collects polarimetric image data forming an imaged drive scene inclusive of a road surface illuminated by the Sun. The GPS receiver outputs a present location of the vehicle as a date-and-time-stamped coordinate set. The compass provides a directional heading of the vehicle. The ECU determines the Sun's location relative to the vehicle and camera using an input data set, including the present location and directional heading. The ECU also detects a specular reflecting area or areas on the road surface using the polarimetric image data and Sun's location, with the specular reflecting area(s) forming an output data set. The ECU then executes a control action aboard the host vehicle in response to the output data set.

The invention discloses a transport case real-time positioning method and device based on multi-sensor fusion, and belongs to the technical field of Internet of Things and intelligent logistics. The method comprises the following steps: acquiring positioning parameters and motion state parameters of a transport case in real time through sensors such as a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit), and carrying out noise filtering, timestamp synchronization and coordinate system unified preprocessing operation on data; an extended Kalman filtering and particle filtering mixed model is adopted, and a weight coefficient is dynamically adjusted according to the GPS confidence coefficient and the IMU confidence coefficient, so that adaptive data fusion is realized; transmitting a positioning result through 4G / 5G and LoRa dual-mode communication, and judging reliability based on a residual error to trigger calibration or switch a positioning mode; according to the method, the problems of insufficient precision, poor robustness and limited real-time performance of a single sensor in a complex environment are solved, centimeter-level positioning precision in the complex environment is realized, the anti-interference performance of positioning is improved, the real-time performance and low power consumption of data transmission are ensured, and a fusion result is prevented from being polluted by abnormal data.

A work vehicle including a chassis, a ground-engaging mechanism, an input device, a global positioning system, and a controller. The input device providing a bench surface. The global positioning system configured to provide a chassis heading signal, a chassis inclination signal indicative of a main fall angle, and a chassis roll signal indicative of a cross slope angle. The controller configured to receive the chassis heading signals, record the chassis heading signal from a first location to a second location; use the recorded chassis heading signal as a reference chassis heading signal; receive a current chassis heading signal; determine an orientation error based on the reference chassis heading signal and the current chassis heading signal; and send a command to actuate the ground-engaging mechanism to shift the current heading to align with the reference heading based on the orientation error.

This disclosure relates generally to a method and system for sensing alcohol intoxication and raising an alert. State-of-the-art methods for detecting alcohol intoxication majorly includes breath alcohol devices, bodily fluid testing, transdermal sensors, mathematical algorithms, and optical techniques. However, the impact of alcohol is not same for all but differs based on individuals' physiological traits and capacity to tolerate. Personalized systems that can sense alcohol intoxication based on individuals present alcohol consumption activity as well as the past history of consumption is not yet achieved. The proposed method of sensing the alcohol intoxication state of the subject is based on cumulative scoring technique using sensors and applications pre-installed in an GPS enabled wearable device and a mobile device. The method also triggers an alert to the subject consuming alcohol as well as to an emergency contact about altered physical and cognitive functioning under the influence of the alcohol.

The invention discloses an unmanned aerial vehicle real-time modeling method and system for a power transmission line disaster scene, relates to the technical field of power operation and maintenance, and aims at a global positioning system signal missing scene. The problem that the sub-graphs are difficult to align when the pose drifts and the common view is weak in the traditional method is solved. A global pose optimization model fuses historical constraints of preprocessing training data, a single-machine positioning result of local pose data and visual features of an operation key frame image set, an internal constraint system without external positioning signals is constructed, pose errors are corrected, strong dependence on an image common-view area is broken through, and the positioning accuracy of the operation key frame image set is improved. Multi-unmanned aerial vehicle pose stability and local data efficient fusion are achieved, early-stage data preprocessing, pose resolving and later-stage three-dimensional reconstruction are combined, the real-time dense map generation period is shortened, support is provided for fault positioning, damage assessment and emergency repair scheme making after power transmission line disasters, and the emergency response efficiency and reliability are improved.

The embodiment of the utility model discloses a camera device and a monitoring system, and the camera device can be applied to various fields of entertainment, traffic, security and protection and the like. The camera device comprises a body, an interface module and a cover body. The body is a structural main body of the camera device. The interface module is provided with at least one connecting interface, the connecting interface is used for being connected with external cables, and the external cables comprise but not limited to a power supply connecting cable, a network connecting cable, an alarm connecting cable, an audio connecting cable, a global positioning system connecting cable and the like. The cover body and the body have a split state and a connected state. In the split state, the connection interface is configured to be in an exposed state. And in the connection state, the cover body is configured to shield the connection interface. The camera device adopts a tail-line-free design, is relatively simple in structure and relatively light in weight, and can be conveniently transported and installed.

The invention relates to the technical field of computer vision and three-dimensional reconstruction, in particular to a large-scene three-dimensional reconstruction method based on adaptive partitioning and geometric optimization, which comprises the following steps: acquiring an original image set without a GPS (Global Positioning System) tag to construct a weighted image association graph; performing splitting processing on the weighted image association graph by adopting a self-adaptive partitioning method to obtain a plurality of blocks; independently executing Colmap on each block to obtain local sparse point clouds and camera parameters, and unifying all the local sparse point clouds to a global coordinate system by adopting a Umeyama algorithm to form a complete sparse point cloud; a complete sparse point cloud is adopted to pre-train the 3DGS model, and reliable Gaussian center points are screened to form a stable point cloud; constructing low-frequency shape constraint loss, and performing weighted optimization on the low-frequency shape constraint loss, color loss and structure loss to obtain a pre-trained 3DGS model; obtaining a large-scene three-dimensional reconstruction result through the optimized 3DGS model; the method has good adaptability to geometric structure dominated scenes, and the engineering feasibility and efficiency of large-scale scene reconstruction are effectively improved.