54 results about "Wireless signal strength" patented technology

The invention discloses a dairy cow oestrus recognition system based on attitude angle and track fusion of a low-power-consumption Bluetooth ear tag. The dairy cow oestrus recognition system comprises an attitude angle acquisition terminal module, a track behavior reconstruction module, a high-frequency sampling trigger module, an edge recognition and preprocessing module, a fusion judgment and early warning output module and a cloud platform collaboration module. The system periodically collects three-axis attitude angle data through Bluetooth ear tag equipment worn on the ears of a dairy cow, reconstructs a virtual track point string in combination with wireless signal intensity, and identifies behavior trends and spatial path characteristics of individuals respectively; in a suspected state, a short-time high-frequency sampling window is automatically triggered to capture subtle disturbance behaviors, and recognition of complex behaviors such as silent oestrus, short-time oestrus and passive oestrus is achieved. The system adopts a multi-channel collaborative recognition and fusion voting mechanism to output an oestrus judgment result, has the advantages of low power consumption, high adaptation, deployability, expandability and the like, and is suitable for behavior monitoring and intelligent breeding management of a large-scale cow farm.

An example method for determining the distance between the network devices thereby enhancing the accuracy of location determination is presented. In one example implementation, the proposed method entails training, during a training phase, a machine learning (ML) model based on test environmental condition metrics about the network devices. Further, during an inference phase, a network controller may first determine a coarse distance between a pair of network devices using wireless signal strength between the pair of network devices, and then finetune the coarse distance to generate a refined distance using a trained ML model. Further, using the refined distance, the network controller may more accurately determine the location of a network device of the pair of network devices whose location was unknown.

Aspects of the subject disclosure may include, for example, performing signal measurements in a wireless network. An area of interest within a coverage area of the communications network may be identified based on the signal measurements. Zones within the area of interest may be further identified. Additional test measurements within the area of interest may be requested. Test devices may be dispatched to locations within the area of interest to perform the additional test measurements. Other embodiments are disclosed.

A wireless short hop assembly includes a transmitter antenna and an integrated receiver / pulser module. A receiver antenna and a pulser assembly are consolidated into the receiver / pulser module. The transmitter antenna is configured to transmit, via magnetic flux induction, a magnetic carrier wave conveying a wireless signal to the receiver antenna. When the wireless short hop assembly is deployed on subterranean drilling bottom hole assembly (BHA) such that a shock reduction tool is interposed on the BHA between the transmitter antenna and the integrated receiver / pulser module, the integrated receiver / pulser module positions the receiver antenna closer to the shock reduction tool and the transmitter antenna than if the receiver antenna and the pulser assembly were discrete. The wireless signal as received by the receiver antenna is stronger and more stable than if the receiver antenna and the pulser assembly were discrete.

An attachment management system comprises a working vehicle, a plurality of attachments, a mobile terminal, and a plurality of communication tags fixed on the attachments to communicate with the mobile terminal through a wireless signal that is compliant with a near field communication standard. The mobile terminal is switchable between a first mode to receive the wireless signals from the communication tags and a second mode to receive the wireless signals from the communication tags and to transmit attachment information. The mobile terminal displays, in the first mode, tag identifiers and a plurality of pieces of attachment information stored in the tag memories of the communication tags, and in the second mode, the tag identifiers and the plurality of pieces of attachment information stored in the tag memories of the communication tags which transmit the wireless signals each having signal intensity equal to or greater than a predetermined threshold.

An electronic device according to various embodiments disclosed in this document may include a display, a camera, and a processor operatively connected to the display and the camera. The processor may display augmented reality on the display based on an image captured by the camera, display a point moving in the augmented reality on the display in conjunction with the movement of the electronic device, recognize a point selected in the augmented reality, display a guide area including the selected point so that the point moves within a specific area, store sensor information including a geomagnetic value measured while the point moves within the guide area, store wireless signal strength information measured while the point moves within the guide area, and correct the geomagnetic value included in the sensor information using a reference direction and the direction of the electronic device at the time of measurement of the geomagnetic value. Various other embodiments may also be possible.

The application discloses an indoor and outdoor seamless positioning method, system, device and medium, and relates to the technical field of information systems.The method comprises the following steps: acquiring the wireless signal strength of a current positioning point; judging the area type where the current positioning point is located according to the wireless signal strength; when the current positioning point is located in an indoor area, adopting a WiFi position fingerprint positioning technology to determine the position coordinates of the current positioning point; when the current positioning point is located in an outdoor area, adopting a GPS positioning technology to determine the position coordinates of the current positioning point; and when the current positioning point is located in an indoor and outdoor boundary area, adopting an indoor and outdoor fusion positioning technology based on a KNN algorithm to determine the position coordinates of the current positioning point.The application can realize the smooth transition and seamless connection of indoor and outdoor positioning.

This invention discloses a method and device for rapid location of mobile terminals involved in crimes, specifically relating to the field of wireless signal positioning technology. It involves setting sampling points at the crime scene to acquire wireless signal strength, direction of arrival, and sampling coordinates; performing peak extraction and directional clustering to generate candidate location points; performing micro-displacement re-measurement around the candidate location points; determining the boundary orientation of obstructions based on the peak migration trajectory of the re-measured signal strength; distinguishing between leakage and reflection candidate points by registering the directional changes of the candidate location points with the boundary orientation of the obstructions; determining the terminal entity candidate region based on the asymmetric attenuation characteristics of the wireless signal strength at leakage candidate points; and combining this with consistency verification between the terminal entity candidate region and the reflection candidate points, thereby achieving rapid and accurate location of the mobile terminal involved in the crime. This invention effectively improves the accuracy and efficiency of locating mobile terminals involved in crimes.

The invention belongs to the technical field of construction project management and cloud communication, and discloses a construction project management cloud server communication method based on AI big data, and the method specifically comprises the following steps: 1, collecting and preprocessing multi-dimensional state data; network environment data of a construction site and working state data of terminal equipment are collected in real time by deploying a network detection node and an equipment end communication module through a cloud server end, and the network environment data comprise bandwidth, delay, packet loss rate, jitter, wireless signal strength and network topology connection state of each candidate communication path; the equipment working state data comprises an equipment type, a working mode, a to-be-transmitted data volume and a data priority. Dynamic adaptation of communication parameters of the construction project management cloud server is achieved through the AI big data technology, the problem that existing static configuration cannot cope with violent network fluctuation and equipment state dynamic change on a construction site is solved, and the reliability, the real-time performance and the resource utilization rate of communication are remarkably improved.

The invention relates to an indoor wireless signal strength prediction method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: according to a three-dimensional model of an indoor area, constructing an energy flow diagram corresponding to a source node, which is used for representing wireless signal propagation paths from the source node to each target node and a wireless signal energy attenuation relationship of each wireless signal path; the target node is associated with a plurality of receiving points; acquiring a plurality of wireless signal propagation paths from the source node to each target node according to the energy flow diagram, and determining a target propagation path from the plurality of wireless signal propagation paths; wherein the contribution degree of the target propagation path to the signal intensity of the target node meets a preset condition; and based on the target propagation path, determining a ray emission direction of a receiving point associated with the target node and performing ray tracing to obtain predicted wireless signal intensity of the receiving point associated with the target node. By adopting the method, the signal strength prediction efficiency can be improved.

The embodiment of the invention provides a control method and device of a mobile storage device, electronic equipment and a computer readable storage medium, and relates to the field of smart home. The method comprises the following steps: acquiring an image frame acquired by a camera of the mobile storage device at a current time step, and converting a pixel coordinate into a first coordinate in a world coordinate system; acquiring the wireless signal strength of the terminal held by the user at the current time step, and acquiring a second coordinate of the landmark in the world coordinate system; the first coordinate and the second coordinate are fused according to the first confidence coefficient and the second confidence coefficient, and the displacement direction of the mobile storage device is obtained according to the corrected coordinate and the real-time coordinate of the mobile storage device; and acquiring point cloud data acquired by the laser radar at the current time step, and determining the displacement speed of the mobile storage device according to the distance. According to the embodiment of the invention, through combination of the image, the signal intensity and the point cloud data, the mobile storage device can automatically follow the user.

This invention discloses a spatiotemporal synchronous high-precision positioning method and system based on multi-sensor fusion, belonging to the field of positioning technology. The method includes the following steps: Step 1: Acquiring images from a visible light camera, a 3D point cloud coordinate image from a ToF depth camera, angular velocity and acceleration from an inertial measurement unit, and wireless signal strength from a wireless signal module; Step 2: Based on a pre-calibrated homogeneous transformation matrix, reprojecting the 3D point cloud coordinate image acquired by the ToF depth camera onto the image plane of the visible light camera to obtain spatially aligned coordinates; Step 3: Based on the signal strength indication received by the wireless signal module, calculating and correcting the distance observation value using a nonlinear ranging model to obtain the corrected distance observation value. This invention effectively solves the inherent defects of single-sensor positioning in complex environments through a complete spatiotemporal synchronization and multimodal data fusion framework.

A method of reducing power consumption of a first wireless communication device is described. A charge level of a battery associated with the first wireless communication device is monitored. A wireless communication session between the first wireless communication device and a second wireless communication device is maintained. Based at least in part on the charge level of the battery being within a low battery threshold range, a wireless signal strength associated with the wireless communication session is monitored. Based at least in part on the wireless signal strength reaching a power saving threshold that is above a minimum connection threshold for maintaining the wireless communication session, a power saving action associated with a wireless interface that supports the wireless communication session is performed.

This invention belongs to the field of intelligent low-voltage power distribution and provides a method and system for controlling the status of IoT meter switches based on dual-mode communication. The technical solution involves receiving IoT meter switch status control commands; collecting power line carrier signal strength and low-power wireless signal strength; determining the communication mode used for transmitting the IoT meter switch status control commands based on the power line carrier signal strength and low-power wireless signal strength; generating a corresponding switch component switching strategy based on the target communication mode; communicating with an external IoT switch based on a preset communication protocol corresponding to the communication mode; and generating control signals to control the opening and closing actions of the external IoT switch. This improves communication stability and reliability.

The invention relates to a wireless signal feature determination method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: extracting an initial wireless signal feature subset corresponding to each candidate feature vector in a candidate feature vector group from a multi-source wireless signal feature set; for each preset feature screening algorithm, processing each candidate feature vector based on the preset feature screening algorithm and each initial wireless signal feature subset to obtain a local feature selection vector corresponding to the preset feature screening algorithm and a corresponding evaluation index value; and screening the local feature selection vectors based on the evaluation index values to obtain a global optimal wireless signal feature subset corresponding to the wireless signal strength prediction task. By adopting the method, the model performance of the machine learning prediction model of the wireless signal strength can be improved.

A monitoring system can be utilized to provide remote services, for example, caregiving services, to a user. The monitoring system can perform a mapping of a site and then use this information along with sensor data to determine a status of the client user. Based on the status, the monitoring system sends a notification to a contact based on a profile configuration associated with the client user. The monitoring system can use any one or more training algorithms, such as a machine learning algorithm, to determine one or more locations of a site associated with a client user. Once these locations are determined the monitoring system is able to provide to the contact accurate and reliable information about the client user so as to improve the services and quality of experience associated with the client user.

This application provides a method for determining a wireless signal strength in an area, a computer-readable storage medium, and an electronic device. The method includes: obtaining building diagram information, wherein the building diagram information comprises a position of a target signal source, a target area, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information; converting the building diagram information into a polar coordinate system; determining an attenuation amount of a target pixel based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system, wherein the propagation path penetrates at least part of the one or more obstacles; and determining a signal strength of the target pixel based on a signal strength of the target signal source and the attenuation amount of the target pixel.

The application provides a signal detection method and device of a wireless device, equipment and a storage medium. The method is applied to a wireless device, and the wireless device is at least one. If there are multiple wireless devices, the multiple wireless devices are devices under the same account. The method specifically comprises the following steps: periodically sending a wireless signal detection instruction to at least one hanging device, wherein the wireless signal detection instruction is used for instructing each hanging device to periodically determine wireless signal strength information corresponding to the wireless device; receiving multiple wireless signal strength information sent by the at least one hanging device; and sending the multiple wireless signal strength information and identification information of the corresponding wireless device to a wireless device management server, so as to instruct the wireless device management server to determine the transmission signal state of the corresponding wireless device according to the identification information of the wireless device and the multiple wireless signal strength information. The application can determine the transmission signal state of at least one wireless device under the same account, and meets the current signal detection requirement.

To ensure that the automatic door system opens properly while suppressing response delays. [Solution] The mobile robot system includes a door processing circuit that controls the door actuator of an automatic door device based on a signal from a wireless receiver of the automatic door device, a wireless transmitter that transmits a wireless signal for opening the door, and a robot processing circuit, and a mobile robot that moves around the area where the automatic door device is located. The door processing circuit is configured to perform controls related to opening the door actuator based on the strength of the wireless signal received by the wireless receiver.

The invention relates to the technical field of positioning identification, and further relates to a positioning method and device, a main control circuit board, wearable intelligent equipment and a computer program product. The method comprises the following steps: receiving real-time wireless signal strength of a plurality of wireless signal transmitting points in a target building; determining a weight corresponding to each wireless signal transmitting point according to the maximum value of the plurality of real-time wireless signal intensities and the plurality of real-time wireless signal intensities; determining signal intensity information corresponding to each floor according to the reference wireless signal intensity of a plurality of wireless signal transmitting points pre-detected by each floor, the plurality of real-time wireless signal intensity and the weight corresponding to each wireless signal transmitting point; and taking the floor with the signal intensity information meeting a preset condition as the floor where the user is located. According to the method, misjudgment of floor positioning is effectively reduced, the positioning reliability is improved, and the accuracy of floor positioning is remarkably improved.

Embodiments of the present disclosure relate to the generation of alarm signals based on wireless signal strength measurements between data acquisition devices, such as character readers or other mobile devices, and their respective hosts, such as their charging stations. An exemplary method utilizing this approach involves determining a received signal strength indicator (RSSI) of a wireless signal between a mobile device and a host. This determination can be made either at the mobile device or the host. Then, if the RSSI falls within a first RSSI range associated with generating a first alarm signal, at least one of the mobile device or the host generates a first alarm via its respective alarm module. Conversely, if the RSSI falls within a second RSSI range, at least one of the mobile device or the host generates a second alarm via its respective alarm module.

The invention relates to the technical field of industrial communication, and provides a WiFi and power carrier redundant backup communication method, which comprises the following steps of: simultaneously establishing a wireless communication channel and a power carrier communication channel between a client and a control end for transmitting data; the two channels periodically send heartbeat messages containing signal strength information; the exchange control module receives the heartbeat message, extracts wireless signal strength and a power carrier signal-to-noise ratio, compares the wireless signal strength with a preset wireless signal strength threshold value, compares the power carrier signal-to-noise ratio with a preset power carrier signal-to-noise ratio threshold value, and determines a main channel according to a comparison result; when the main channel changes, data transmission is switched to the changed main channel, and the other channel serves as a backup channel and continues to send the heartbeat message. The reliability and the stability of data transmission between the wind power cabin and the fan blades are improved.

The invention discloses a wireless network positioning method based on signal heat map super-resolution enhancement, which comprises the following steps: firstly, establishing an off-line fingerprint database by collecting signal intensity data of channel state information, and then mapping the off-line fingerprint database to an RGB space to generate a wireless signal intensity heat map; and performing super-resolution reconstruction on the heat map by using the trained CNN network to enhance details. During online positioning, matching a real-time signal of a to-be-measured point with the reconstructed heat map through a KNN algorithm to obtain a heat map positioning coordinate; meanwhile, the LSTM network predicts the current position according to the wireless signal intensity value sequence, a KNN matching result and LSTM prediction coordinates are fused through a Kalman filter, optimal position estimation is achieved through state updating and error correction, and a stable and accurate final positioning result is output. According to the invention, a wireless signal positioning technology and an image processing technology are fused and cooperatively provided to meet different positioning precision requirements and positioning services of different scenes, and a new solution is provided for the field of indoor positioning.

The invention provides an indoor wireless propagation model correction test data sampling method and device, and relates to the technical field of indoor wireless communication. The method divides an intrinsic length grid through a spatial domain, samples a time domain according to a specific frequency of a frequency band, and eliminates fast fading by combining the intrinsic length grid and the time domain, and specifically comprises the following steps: determining a sampling region taking an information source as a center and 2R as a radius, and dividing the grid according to the intrinsic length 2L of the spatial domain; sampling at the central point of each grid according to a time domain sampling frequency, wherein each grid samples no less than 50 data; and processing the sampling data, and averaging to obtain wireless signal intensity data after removing anomalies. The device corresponds to the function module of the method. According to the sampling method combining the spatial domain and the time domain, the limitation that the Lee's theorem only depends on spatial sampling is broken through, the problems that spatial domain sampling is difficult and sampling points are insufficient due to the fact that the indoor space is limited are solved, and the accuracy and reliability of indoor propagation model correction are improved.

The embodiment of the invention discloses an indoor 5G three-dimensional fingerprint database construction method and related equipment, and aims to solve the core problem that a 5G network lacks direct position reporting functions such as MDT and the like, and a traditional fingerprint database cannot be associated with a real user position. The method comprises the following steps: acquiring original MRO data of a measurement report of a 5G network and corresponding signaling data, and analyzing to obtain a user identifier and wireless signal characteristics of a serving cell and an adjacent cell; acquiring actual position information of a user, and associating the actual position information of the user with the user identifier; based on the wireless signal characteristics, distinguishing indoor and outdoor sampling points, and determining a critical point when the user enters and exits from the room according to the sudden change of the wireless signal intensity when the user enters and exits from the room; and constructing an indoor 5G three-dimensional fingerprint database corresponding to the building, the unit and the floor based on the position information of the critical point and the actual position information of the user.

The application discloses a positioning method, device, equipment and medium of a handheld device. When the smart wearable device detects that the state of the smart wearable device is changed from a worn state to an unworn state, a first scene image is captured. When the strength change of the wireless signal fed back by the handheld device exceeds a set threshold, the current first wireless signal strength is recorded and a second scene image is captured. When the smart wearable device detects that the state of the smart wearable device is changed from the unworn state to the worn state, the second wireless signal strength fed back by the handheld device is acquired. The first scene image and the second scene image can reflect the scene position of the handheld device. According to the change of the deviation of the first wireless signal strength and the second wireless signal strength, the change of the distance between the handheld device and the smart wearable device can be determined. Therefore, the handheld device can be positioned based on the first wireless signal strength, the second wireless signal strength and the first scene image and the second scene image, and the rapid searching of the handheld device is realized.

This disclosure proposes a cell reselection method, communication system, and related equipment for an integrated air-space-ground network, relating to the field of wireless communication technology. The method includes: a terminal listening to broadcast messages and obtaining coverage information of the currently camped cell and neighboring cells from the broadcast messages, wherein the currently camped cell and neighboring cells are either non-terrestrial network cells or terrestrial network cells; if the currently camped cell is a non-terrestrial network cell, the terminal determines the positional relationship information between the terminal and the currently camped cell based on the coverage information of the currently camped cell, and triggers cell reselection measurement based on the positional relationship information between the terminal and the currently camped cell; if the currently camped cell is a terrestrial network cell, the terminal triggers cell reselection measurement based on the wireless signal strength of the currently camped cell; the terminal performs cell reselection based on the cell reselection measurement results. This enables the terminal to select a suitable terrestrial network cell or non-terrestrial network cell for camping within the integrated air-space-ground network.

The throwing and trailer intelligent matching and docking system based on the wireless communication technology comprises a vehicle-mounted terminal which is arranged in a tractor and used for controlling a wireless communication device to receive a wireless signal of a specific frequency band sent by a trailer so as to be matched with the corresponding trailer, the signal intensity monitoring equipment is controlled to judge the intensity of the received wireless signals to obtain specific distance parameters of the tractor and the trailer; the temperature and humidity monitoring equipment is arranged in the trailer and used for monitoring specific temperature and humidity parameters of the trailer; and the signal intensity monitoring equipment is used for monitoring the intensity of the wireless signals received by the vehicle-mounted terminal, then judging the intensity of the wireless signals to obtain specific distance parameters of the tractor and the trailer, and finely adjusting the driving direction of the tractor.

The invention discloses a double 5G WIFI device roaming automation test method and system, and the method comprises the following steps: S1, deploying a to-be-tested device in a wireless signal overlapping coverage area of two APs, the to-be-tested device being configured with two radio frequency modules; s2, controlling a digital programmable attenuator to automatically adjust the wireless signal intensity of the two APs through a test control unit, and simulating the signal intensity change caused by the movement of the to-be-tested equipment between the two APs; s3, when a roaming threshold value set by the to-be-tested equipment and a signal difference value condition between double frequencies are met, the to-be-tested equipment completes roaming switching from one AP to the other AP; and S4, collecting and recording test parameters of the to-be-tested equipment in the roaming process in real time. According to the invention, the roaming test of the double 5G WIFI devices can be realized automatically, efficiently and accurately, so that the high-quality test requirement is met.

An anti-jamming method (10.1, 10.2) and a vehicle anti-theft device (20) are disclosed. The device (20) includes a signal jammer detection module (22) and a processor (18). The signal jammer detection module (22) is configured to monitor wireless signal strength or connectivity status of modules such as a GSM module (25), GPS module (26), and Bluetooth module (21). The processor (18) is configured to determine the presence of a signal jammer (7) when the monitored signal strength exceeds a predetermined threshold or upon simultaneous connectivity failure. In response, the processor (18) autonomously initiates one or more vehicle anti-theft measures (24), which may depend on the engine's operational state (33). The anti- theft measures (24) may include forcing the vehicle's transmission (6) into a Park position to immobilise the vehicle (1). The invention overcomes the problem of being unable to remotely communicate with and control a stolen vehicle due to the presence of a signal jammer (7).