82 results about "Raspberry pi" patented technology

Disclosed are a closed type error-proofing system for an SMT production line and an operation method therefor. The system comprises an error-proofing system APP, a background management system, a real-time production line monitoring system, an intelligent line-side warehouse system, a chip mounter intelligent self-locking system, a material splitting module, a bulk material module, a material label management system, and a central control system. The error-proofing system APP is running in Raspberry Pi; the central control system is installed on the Raspberry Pi; the Raspberry Pi is separately connected to an alarm and a power supply; and the background management system, the real-time production line monitoring system, the intelligent line-side warehouse system, the chip mounter intelligent self-locking system, the material splitting module, the bulk material module, and the material label management system are separately connected to the central control system. According to the present invention, the chip mounter intelligent self-locking system of the intelligent closed type error-proofing system for an SMT production line is used to be bound with a tray on a FEEDER and is connected to the intelligent line-side warehouse system, thereby effectively eliminating the hidden dangers of wrong station scanning, wrong material taking, wrong material collection, and wrong material replacement caused by operators not understanding the processes or not following the regulations.

The invention relates to the technical field of programming teaching, in particular to a graphical programming system based on a big language model and hardware constraints and a use method, and aims to realize automatic generation from a natural language to a graphical code by integrating the big language model and a Blockly graphical platform, and dynamically adapt in combination with hardware constraints of a master control development board (such as Raspberry Pi). The system comprises a client program, a knowledge base and an interactive programming interface, supports a user to control external hardware equipment through a natural language instruction, and simultaneously provides functions of code real-time mapping, dynamic debugging and teaching connection. The method reduces the programming threshold of software and hardware combination, is suitable for the fields of artificial intelligence education, Internet of Things development and robot control, and significantly improves the development efficiency and user experience.

The invention discloses an AI visual area personnel departure monitoring system and method based on real-time video analysis, and the method comprises the steps: receiving a factory starting signal through a Raspberry Pi, transmitting a starting operation signal to a departure detection model, and triggering the model to start real-time video data analysis. The system is integrated with a high-performance monitoring camera to capture real-time video streams in a factory environment. And through a YOLO algorithm and a human body posture estimation algorithm, performing intelligent analysis on personnel positions, actions and behavior modes in the video data so as to judge whether an off-post behavior exists or not. And when personnel leaving or other abnormal behaviors are detected, the system generates and uploads alarm information, including abnormal types, time, positions and risk assessment, and meanwhile, the system automatically pushes the early warning information to related personnel. The Raspberry Pi is also responsible for analyzing signals from the server. And if the early warning information is received, the Raspberry Pi controls the audible and visual alarm to give an alarm. And if no alarm information exists, the Raspberry Pi continuously monitors the working state of the factory.

The invention relates to the technical field of vehicle remote control, in particular to a CAN-to-MQTT-based target vehicle remote control and data transmission system and method.A low-delay and stable communication link is established by adopting an MQTT server, and a CAN-to-MQTT data communication link is realized by means of hardware equipment of Raspberry Pi 4B and a Python data protocol conversion script; the upper computer builds target vehicle remote driving, and feeds back the road driving condition in real time by means of a camera. According to the method, a lower-delay and more stable control and communication link can be provided based on the DBC of original equipment, consumption-level hardware and an industrial-level communication protocol are deeply fused, the system cost is remarkably reduced on the premise that the performance is guaranteed, a replicable engineering normal form is provided for a remote control technology in a medium-low speed scene, and the method is suitable for popularization and application. When a plurality of interference target vehicles execute a standard test working condition, the interference test scene can be realized by remote control of a safety officer and sending of an automatic driving control instruction by a terminal computer.

1. Name of the design product: Development board (RP2350 - Tiny). 2. Use of the design product: Development board for Raspberry Pi micro - control unit. 3. Design key points of the design product: Lies in the shape. 4. Picture or photo that best shows the design key points: Perspective view 1.

The invention discloses an all-dimensional integrated intelligent baby crib which comprises a crib body, a master control PCB arranged on the crib body, and an environment detection module, an intelligent sleep inducing module, a sleep detection module and an intelligent reminding module which are connected with the master control PCB. The environment detection module is used for comprehensively monitoring the living environment of the baby, monitoring the temperature, humidity, illumination and gas quality and automatically adjusting the temperature; the intelligent sleep inducing module is used for outputting and transmitting baby crying sound to a Raspberry Pi 4B13 for processing after a sound sensor collects the baby crying sound, and when the baby crying sound is detected, the system starts an MP3 playing module 11 to play preset pacifying music to help the baby to fall asleep quietly; the sleep detection module is used for monitoring the sleep condition of an infant, and data are sent to the HT32 main controller in real time to be analyzed and displayed to parents through an APP; and the intelligent reminding module is used for comprehensively analyzing data of each sensor, uploading the data to the cloud platform through the EC600M4G module, and reminding parents of any abnormal condition in time through an APP.

The present invention relates to a device and a system for debugging a solid state disk device, the device comprising: a joint test action group add-on board; and a Raspberry Pi. The Raspberry Pi comprises a general purpose input output interface coupled to the joint test action group add-on board; and a processing unit coupled to the general purpose input output interface. The processing unit is configured to emulate a plurality of joint test action group commands to the solid state disk device through the general purpose input output interface to dump data generated by the solid state disk device during runtime of the solid state disk device. Using the device as described above can reduce the cost required to debug the solid state disk device.

1. The name of this design product: adapter board (Raspberry Pi interface adapter board Pi5). 2. Purpose of this design product: adapter board for connecting Raspberry Pi HDMI and Type C interfaces. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

This invention relates to the field of intelligent driving assistance technology, specifically disclosing a driver state monitoring system based on intelligent image recognition. Built on a Raspberry Pi embedded platform, it includes a video acquisition module, a core algorithm processing module, and a peripheral control module. The video acquisition module is compatible with USB or CSI cameras, acquiring and preprocessing driver facial images. The core algorithm processing module incorporates a lightweight facial key point detection model to extract facial features and identify dangerous behaviors such as closed eyes and head tilting, and features a feature calibration and fatigue grading mechanism. The peripheral control module connects to alarm and display components, triggering corresponding warning actions and can be expanded to include multiple alarm methods. The system can also track continuous driving time and expand remote monitoring functionality. This invention features low hardware cost, low power consumption, convenient deployment, fast edge-side inference response, and accurate monitoring. It is adaptable to multiple scenarios, requires no manual intervention, comprehensively prevents fatigue driving, and is easy to deploy on a large scale.

The invention discloses an intelligent recyclable garbage sorting method based on AI identification, which comprises the following steps: S1, garbage is put into a sorting mechanism arranged in a garbage sorting device, and then the garbage on the sorting mechanism is shot through a camera; s2, the camera transmits a shot picture to an AI recognition module, and the AI recognition module recognizes a garbage type in the picture and transmits a recognition result to a Raspberry Pi control module; s3, the Raspberry Pi control module controls the sorting mechanism to throw the garbage into the classification garbage cans of the corresponding types according to the result transmitted by the AI recognition module, the type of the thrown garbage can can be automatically, rapidly and accurately recognized, the sorting mechanism is controlled to throw the garbage into the corresponding classification garbage cans, the process is highly intelligent, and the efficiency is high. The garbage sorting efficiency and accuracy are greatly improved, meanwhile, the structure is more simplified, the manufacturing cost is lower, the purchasing cost of a user is reduced, and the garbage sorting device is very suitable for being used in families.

1. The name of this design product: expansion box (Raspberry Pi 5 multi-function expansion box A, B, C). 2. Purpose of this design product: expansion box for Raspberry Pi 5 function expansion and shell protection. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the key points of the design: 3D drawing of Design 1. 5. Designate Design 1 as the base design.

1. Name of the product in this design: Adapter (PCIE to MiniPCIe). 2. Purpose of this design: To expand the MiniPCIe interface of Raspberry Pi. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The application discloses a water surface floating object detection method and device based on a Raspberry Pi and an improved YOLOv5 algorithm, wherein the method comprises the following steps: first, on the basis of the original YOLOv5, a CBAM attention mechanism and a transformer module are integrated, and the model is pruned; second, the model is trained on a computer, and when the loss of the model no longer decreases and the accuracy no longer increases, the training is stopped; third, the trained model is deployed on a Raspberry Pi carried on a UAV; and fourth, a camera carried on the UAV is used to shoot a water surface photo, and the Raspberry Pi is used to detect water surface floating objects in the photo in real time. On the one hand, the improved YOLOv5 algorithm is used to detect water surface floating objects in real time, and the detection accuracy and the resource occupation of the model are optimized while the detection speed is ensured; on the other hand, the detection algorithm is realized based on the Raspberry Pi, the cost of using a graphics card and an edge device is saved, and the application has practical significance and commercial value in the field of UAV cruising.

The present invention relates to a semi-physical simulation system and simulation method for fault-tolerant cooperative control of a cluster of unmanned aerial vehicles (UAVs), comprising: an information interaction between a cluster ground station computer and a semi-physical simulation platform for fault-tolerant control of a cluster of UAVs based on Raspberry Pi; the cluster includes UAVs with digital simulation and UAVs simulated through Raspberry Pi; each simulated single UAV includes two Raspberry Pis, a simulated UAV model and a controller of the simulated UAV; an instruction upload terminal is used to set the simulation scenario of the entire cluster; a database server is used to calculate neighbor information and assist in completing communication between UAVs; a flight state display terminal for cluster UAVs is used to receive the states of each UAV, draw the flight trajectories of the entire UAV cluster and visualize the flight states of each UAV. The semi-physical simulation system of the present invention can simulate the communication between UAVs in a UAV cluster, enhance the flexibility and authenticity of the simulation system, and greatly shorten the development cycle of a real cluster system.

The present invention discloses a communication system and protocol method for a networked intelligent intersection without traffic lights. The present invention combines the CSMA / CA channel listening and conflict avoidance ideas with the time division multiple access method in VeMAC to construct a CVMAC protocol that can dynamically adjust the working mode according to the channel busyness, solving the problem of node information access conflict; CVMAC determines the protocol type according to the estimated channel node access density, uses CSMA / CA protocol scheduling when the density is low, and adopts the VeMAC protocol mode for transmission when the density is high; the present invention also builds a MAC protocol prototype verification system based on the Raspberry Pi platform to simulate and verify the scenario, and through the statistics of a large number of data packets, it can calculate the bad packet rate, communication delay, and vehicle throughput. The present invention can effectively solve the data conflict problem when high-density vehicle nodes in networked intelligent intersections without traffic lights access the dispatching center, and can greatly reduce the cost of physical scenario verification through the simulation of the scenario.

The invention discloses a photovoltaic panel bimodal dynamic detection method and system based on a lightweight edge intelligent box, and belongs to the technical field of photovoltaic power station intelligent operation and maintenance and edge computing crossing. The system comprises a Raspberry Pi Compute Module 5 core processor, a Raspberry Pi core processor, a Raspberry Pi core processor, a Raspberry Pi core processor and a Raspberry Pi core processor; a double-model dynamic architecture; and the security collaboration mechanism has the advantages of realizing collaborative analysis, dynamic switching and security processing of visible light and infrared thermal imaging, and solves the problems of hardware limitation, algorithm defects and system splitting in the prior art.

The invention relates to the technical field of pipeline safety detection, in particular to a method for detecting defects in a small-diameter pipeline, which comprises the following steps of: planning a detection track of a magnetic robot based on a circumferential welding seam of the pipeline; the stress condition of the robot in the track path is analyzed, and the magnetic force of the robot is determined; the robot collects a pipeline image and identifies defects in the pipeline through the deep learning network; a control system of the robot is built, a mobile computer is used for remotely controlling the Raspberry Pi 4b, and then the Raspberry Pi 4b is used for controlling a robot motor to achieve autonomous operation. According to the detection method, the defect detection efficiency of the small-pipe-diameter pipeline is improved, the automation degree is high, the designed robot can freely run in the iron pipeline, and the good prospect is achieved.

The utility model discloses an intelligent distribution network external damage early warning device, which comprises a box body, a power supply module is arranged in the box body, the output end of the power supply module is connected with a raspberry Pi main board, the output end of the raspberry Pi main board is connected with a communication module, a microphone is fixedly arranged on the box body, and the microphone is connected with the communication module. A microphone is arranged in the box body, an output end of the microphone is connected with the Raspberry Pi main board, a support rod is detachably arranged at the bottom of the box body, and a triangular support mechanism is slidably sleeved outside the support rod. According to the utility model, the Raspberry Pi main board is used for collecting sound around the distribution network device, and automatic recording and audio data analysis are realized through the Raspberry Pi main board; and once possible threats are detected, early warning information is immediately sent to the server through the communication module, so that prediction and early warning of the construction equipment which may damage the cable are realized, and the requirement of manual monitoring is reduced.

The present application relates to the field of garbage disposal, and in particular to an intelligent garbage sorting trolley based on Raspberry Pi. It includes: a visual module, a bottom layer module and a grabbing module; the visual module includes: a camera for obtaining a long-range image of garbage and an image of a garbage bin, determining the target location of garbage and the category of garbage, and a Raspberry Pi for determining the location of the garbage bin; the bottom layer module includes: a trolley chassis that moves through Mecanum wheels, as well as a single-chip microcomputer and an encoder; the single-chip microcomputer determines the set moving speed and initial rotation direction of the Mecanum wheel, and also drives the Mecanum wheel root to move to the target location of garbage and the location of the garbage bin corresponding to the garbage category; the grabbing module includes: a robotic arm, and a motor that drives the robotic arm to grab garbage and deliver the garbage. The present application uses a visual module to identify and classify garbage and a garbage bin, and then drives the Mecanum wheel to move to the garbage and the garbage bin corresponding to the garbage classification in turn through the cooperation of the single-chip microcomputer and the encoder.

1. Name of this product: Expansion Board (Raspberry Pi 5 PCIE to 4-channel PCIE). 2. Purpose of this design: For expansion of serial bus interface in embedded modules. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The present invention relates to the technical field of human health monitoring. Disclosed are a fall detection method and system, an electronic device and a medium. The method comprises: acquiring an image for detection at a current moment; using a lightweight YOLOv5s network to process the image for detection at the current moment, so as to determine whether a target in the image for detection at the current moment has fallen, thereby obtaining a first determination result; if the first determination result is yes, using OpenPose to process the image for detection at the current moment, so as to determine whether the target in the image for detection at the current moment has fallen, thereby obtaining a second determination result; if the second determination result is yes, determining that the target in the image for detection at the current moment has fallen; and, if the second determination result or the first determination result is no, updating the current moment, and returning to the step of acquiring an image for detection at a current moment. The present invention can reduce occupation of computational resources of edge devices such as Raspberry Pi, thus greatly improving the device reliability.

1. Name of this design product: Raspberry Pi All-in-One Computer (RPI‑HMI‑080D / 101D). 2. Purpose of this design product: Display and touch devices for open source hardware. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Design 1, Stereoscopic drawing 2. 5. Designate Design 1 as the base design.

1. The name of this design product: Expansion Board (Raspberry Pi PI5 Dual-Channel PCIe). 2. The purpose of this design product: Raspberry Pi PI5 expands the PCIe interface. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The utility model relates to the field of computer hardware, and provides a case convenient for installing a mainboard, which comprises a Raspberry Pi 4B mainboard and a mainboard case mechanism, and the outer side of the Raspberry Pi 4B mainboard is provided with the mainboard case mechanism. According to the mainboard case mechanism, the plane bottom plate is firstly placed on the ground, then the installation bottom plate is fixed to the plane bottom plate through the bolts, when the mainboard case mechanism needs to be used, due to the fact that the installation bottom plate is of the n-shaped structure, the space below the installation bottom plate can provide a large space for heat dissipation, and in the subsequent using process, the installation bottom plate is not prone to falling off. The Raspberry Pi 4B mainboard can be used as a heat dissipation buffer zone, heat accumulation is reduced, ice bags can be placed in the space under special conditions, the heat dissipation effect is enhanced, then the copper columns are fixed to the installation bottom plate through bolts at equal intervals, then the Raspberry Pi 4B mainboard is fixed to the copper columns, the copper columns can jack up the Raspberry Pi 4B mainboard, and the Raspberry Pi 4B mainboard is fixed to the installation bottom plate through bolts. Therefore, a certain space is generated on the lower side of the Raspberry Pi 4B mainboard, and heat dissipation of the Raspberry Pi 4B mainboard is facilitated.

1. The name of the design product: Touch display (capacitive / resistive 3.5 inch). 2. The use of the design product: Raspberry Pi SPI display and touch device. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: Design 1 perspective view 1. 5. Design 1 is designated as the basic design.

1. Name of the product in this design: Portable testing device housing (cervical cancer). 2. Purpose of this design: As an integrated mounting platform, the front is used to mount the display screen, the rear is used to mount the Raspberry Pi development board, and the back is used to mount the camera module. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

1. Name of the product of this design: Compute Module Motherboard (Raspberry Pi CM5‑IO‑BASE‑A). 2. Purpose of this design product: Suitable for interface expansion of computing module motherboard. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention provides a Raspberry Pi-based navigation situation voice automatic early warning method, which comprises the following steps of: reading an NMEA0183 statement output by an AIS (Automatic Identification System) receiver, analyzing to obtain dynamic and static information of each target, and storing the dynamic and static information into a memory list by taking MMSI (Minimum Mobile Subscriber Identity) as an index; by taking the position of the ship as an original point, taking the heading of the ship as an x axis of a polar coordinate system and taking a starboard as a y axis, calculating the distance and the orientation of each target relative to the ship in the memory list, filtering out the targets in a target filtering range according to a preset Range threshold, and forming a temporary drawing list; calculating the DCPA and TCPA of each target in the temporary drawing list in real time, comparing the DCPA and TCPA with an alarm threshold value and an early warning threshold value preset by a user, and marking the target as an alarm state or an early warning state according to a comparison result; aiming at the target marked as the alarm state or the early warning state, generating a structured text field; and inputting the structured text fields into a voice synthesis module, and generating and playing complete early warning voice in real time by splicing off-line stored fixed audio paragraphs.

The utility model relates to an intelligent accompanying robot based on Raspberry Pi. Each module of the robot comprises a corresponding standard interface, a control module comprises a Raspberry Pi main control board, an I / O expansion board and a first metal rod, and the I / O expansion board is in communication connection with the Raspberry Pi main control board; the motion module comprises a chassis, wheels and a motor, the motor is connected with the I / O expansion board through a standard interface, the Raspberry Pi main control board is connected with the chassis through a first metal rod, and the I / O expansion board is connected with the Raspberry Pi main control board through the first metal rod; the sensing module and the audio module are fixedly connected with the chassis and are connected with the I / O expansion board through standard interfaces; the display module is connected with the I / O expansion board through a standard interface; and the power supply module is fixedly connected with the chassis, comprises a plurality of independent battery assemblies and is connected with the other modules through standard interfaces respectively. Compared with the prior art, the intelligent accompanying robot based on the Raspberry Pi has the advantages that the expansibility and scene adaptability of the intelligent accompanying robot based on the Raspberry Pi are improved, and the maintenance complexity is reduced.

1. The name of this design product: Game console expansion board (Raspberry Pi 1.3-inch GamePi13). 2. Purpose of this design product: Game console expansion board for open source hardware. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.