918 results about "Signal lamp" patented technology

The invention relates to the technical field of intelligent traffic management, and discloses a road traffic signal lamp management system based on big data, which comprises a data acquisition and fusion module for acquiring traffic sensor data, visual data, GPS track data and external environment data, generating unified traffic state data through space-time alignment, data filtering and multi-modal data fusion; and the flow prediction module is used for predicting the traffic flow of a single intersection and a region by using a time sequence model and a graph neural network based on the traffic state data generated by the data acquisition and fusion module. Through multi-modal data acquisition and space-time alignment, Kalman filtering, Bayesian inference and other technologies, deep fusion of different data sources is realized, the comprehensiveness and accuracy of data are significantly improved, dynamic changes of a complex traffic scene can be truly reflected, high-quality basic data are provided for subsequent flow prediction and optimization control, and a core technical support is formed.

The invention provides an intelligent traffic dynamic green wave control method and system, a storage medium and a program product, and relates to the field of traffic control systems.The method comprises the steps that real-time traffic data of all lanes and emergency data published by a traffic management department are obtained; obtaining traffic flow prediction results of different directions of each road section in a future preset time based on a neural network model; outputting the congestion level and the congestion duration of each road section in combination with the emergency situation data and a traffic flow theoretical model, and further determining an adjustment sequence; and on the basis of the traffic flow prediction result, calculating the optimal green wave bandwidth of the signal lamp at each intersection in each target road section by using a particle swarm optimization algorithm to obtain an optimal timing combination scheme of the signal lamp in each target road section, and performing real-time timing control. By implementing the method, the traffic flow can be dredged more efficiently, the parking frequency and delay time of vehicles on the road are reduced, the overall traffic capacity of the urban road is improved, and energy consumption and environmental pollution are reduced.

The invention discloses a road right sharing configuration method and a traffic control system, and relates to the technical field of special vehicle road right sharing, and the method comprises the steps: obtaining the real-time position and speed information of a common vehicle and a special vehicle at an intersection; determining the traffic flow condition of the current intersection by using a traffic flow prediction model; according to the real-time position and speed of the special vehicle and the traffic flow condition of the current intersection, the period and phase duration of the signal lamp are dynamically adjusted through a bidirectional dynamic green wave algorithm, a signal lamp control strategy is obtained, and it is ensured that the special vehicle can pass through the intersection without stopping; configuring intersection signal lamps according to the signal lamp control strategy; according to the invention, through combination of prediction of the traffic flow condition of the intersection and the real-time position of the special vehicle, the period duration and the phase duration of the signal lamp at the intersection are automatically adjusted, the influence on common vehicles at other phases is reduced as much as possible while the special vehicle is ensured to pass through the intersection without stopping, thereby realizing dynamic distribution and sharing of the road right of the special vehicle, and improving the traffic safety. And the utilization rate of special lane resources is furthest improved.

The invention is applicable to the field of safety detection, and provides a camera detection method based on wireless signals, which comprises the steps of probe equipment connection, data acquisition, data analysis, data threshold calculation, model calling and judgment, label judgment and classification, equipment list display, positioning search, signal lamp strip control and the like. According to the invention, the network traffic in the WiFi environment is obtained through the Bluetooth probe device, illegal wireless camera detection and positioning are identified by performing feature analysis and uplink and downlink calculation on the traffic, and the method is mainly used for detecting and positioning illegal wireless cameras so as to protect security of confidential places and confidential conferences, personal privacy and social security.

The invention provides a distributed multi-agent traffic signal cooperative control method, and belongs to the field of intelligent traffic control. The method comprises the steps of performing initialization operation on a road network environment, constructing an adjacency list according to a topological structure of an urban road network, and regarding each traffic signal lamp control intersection in the urban road network as an independent intelligent agent; for each intelligent agent, acquiring a local observation state of the intersection where the intelligent agent is located; performing action selection through sampling according to the action probability distribution; sending the selected action to the traffic simulator by using the intelligent agent, updating the state of the traffic signal lamp, and calculating and returning the intelligent agent information of the next time step by using the traffic simulator; sending the action probability distribution to all neighbor agents; and parameter updating is carried out until a preset training round is reached, and cooperative control of the traffic signals is completed. By adopting the distributed multi-agent reinforcement learning framework, the exploration efficiency is improved, and the collaboration among the agents is promoted.

The invention discloses a global traffic signal control method based on a regional context enhanced large language model, and the method comprises the steps: dividing a target region into K traffic signal lamp control regions according to a traffic network structure of the target region; global real-time traffic information of the target area is collected and converted into global traffic text information; and inputting the global traffic text information into the large language model after LoRA fine tuning, and outputting a global traffic signal lamp control strategy of the target area, namely a traffic signal lamp phase of each intersection. In the fine tuning process of the large language model, an optimal phase decision is generated by using a reinforcement learning agent, a decision result is converted into text data, a region-level optimal phase decision data set is constructed according to an adjacent region division strategy, fine tuning is performed on the model by using the data set, region loss is calculated, and the large language model is optimized through the loss. According to the invention, optimization of global traffic signal lamp control can be realized, the overall traffic delay is reduced, and the traffic efficiency is improved.

The embodiment of the invention provides a training method of a signal lamp control model, a signal lamp control method, a device, equipment, a medium and a product, and relates to the technical field of urban road traffic. The method comprises the following steps: acquiring a plurality of first traffic data, constructing a state characterization matrix and a reward function according to the plurality of first traffic data, and performing model training according to the plurality of first traffic data, the state characterization matrix and the reward function to obtain a signal lamp control model. According to the method, in a model training process, a state representation matrix is utilized to dynamically quantify passing priorities of buses in all directions, and meanwhile, a reward function is utilized to guide the model training process, so that a signal lamp control model obtained through training can recognize and preferentially respond to bus passing demands, and signal lamp actions are dynamically adjusted; therefore, the collaborative optimization of multi-direction bus priority requests in a complex scene is realized, and the coordination capability and response efficiency of a bus priority system in a complex urban traffic environment are improved.

The invention provides a highland cooperative control method fusing a graph convolutional neural network and reinforcement learning, through controlling urban road traffic signal lamps, an expressway ramp signal machine and a variable speed limit unit, expressway traffic congestion is relieved, the urban traffic passing efficiency is improved, road driving vehicles are controlled by means of the signal lamps and the speed limit unit, and the traffic efficiency is improved. Traffic flow scheduling optimization in a global road network is achieved; the whole structure adopts a distributed cooperative control framework, is controlled by a decision-making agent, and performs autonomous decision-making and adjustment according to real-time traffic conditions, so that the adaptability and robustness of the system are enhanced, and the defects of large data calculation amount, difficulty in processing, control strategy lag and the like caused by traditional centralized control are effectively avoided; the graph convolutional neural network model is constructed to aggregate the feature information of the peripheral decision intelligent agent, and the control weight is dynamically allocated, so that the information sharing capability is enhanced, the suboptimal decision caused by lack of comprehensive perception of the surrounding environment is prevented, and the cooperation efficiency of the whole system is improved.

The embodiment of the invention provides a signal lamp countdown prediction method and device, equipment and a storage medium. The method comprises the following steps: acquiring at least one piece of historical trajectory data of a target intersection; according to the road network data of the target intersection, determining an association relationship between roads corresponding to the historical trajectory data; according to the incidence relation between the roads corresponding to the historical track data, grouping the historical track data to obtain a grouping set; and determining phase information of the target intersection according to the historical trajectory data in each group. The method can improve the prediction accuracy of signal lamp countdown.

A method (400) for controlling one or more turn signal lamps (140a, 140b) of a vehicle (100), the method (400) comprising steps of receiving (202), by at least one processor, a navigation data associated with one or more turns. Further, identifying (204), by the at least one processor, at least one turn signal lamp from the one or more turn signal lamps (140a, 140b) for controlling based on the navigation data. Furthermore, receiving (206), by the at least one processor, speed data of the vehicle (100) and correlating (208), by the at least one processor, the speed data of the vehicle (100) and the navigation data. Moreover, controlling (210), by the at least one processor, the at least one turn signal lamp from the one or more turn signal lamps (140a, 140b) based on the correlation.

The invention relates to the technical field of train tracks, and discloses a train traveling track autonomous verification system based on spatio-temporal feature fusion, which comprises a multi-source sensing acquisition module used for acquiring spatio-temporal information of track environments in front of and behind a train, a sensing data preprocessing module used for filtering a three-dimensional point cloud of the spatio-temporal information, and a verification module used for verifying the three-dimensional point cloud of the spatio-temporal information. The target identification and feature extraction module is used for identifying a signal lamp state based on an image and a depth map of spatio-temporal information; the traffic decision and track verification module is used for issuing a communication and instruction according to a target identification result; the method is used for detecting the running state of each module of the system. By fusing point cloud data, image information and a GNSS positioning result, a unified spatial-temporal characteristic model is constructed, high-precision fitting and dynamic offset judgment of a train running track are achieved, and the effect that the track detection precision is remarkably superior to that of a single sensor scheme is achieved.

The utility model relates to the technical field of traffic management, in particular to a bidirectional early warning device with an adjustable display surface for an intersection without traffic lights, which comprises a square upright post, a first early warning information display screen and a second early warning information display screen. The square stand column is used for being installed on the roadside of an intersection of a main road and a branch road. The first early warning information display screen is arranged on the first side face of the square stand column so that the display face of the first early warning information display screen can face the vehicle coming direction of the main road. The second early warning information display screen is hinged to the second side face, adjacent to the first side face, of the square stand column, the hinge axis of the second early warning information display screen extends in the vertical direction, and the second early warning information display screen can be opened inwards or outwards based on the second side face of the square stand column so that the second early warning information display screen can face the vehicle coming direction of the branch road. Even if the included angle deviation of the intersecting roads is large, the vehicle driving direction of the branch road can still be kept basically perpendicular to the second early warning information display screen, and the visual recognition effect of the warning information is greatly improved.

The invention provides a signal lamp fault intelligent diagnosis method and system based on the Internet of Things, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting the electrical parameters, environment data, working time sequence information and video image data of a signal lamp unit in real time, and constructing a multi-mode data set of the operation state of a signal lamp; step 2, transmitting the multi-modal data set to a central diagnosis platform, performing feature extraction and preliminary fault identification by using a pre-trained fault identification model, and generating fault type and fault position information; and step 3, based on the fault position information, selecting a plurality of monitoring devices in time-space association to form a diagnosis group, and performing fusion analysis and collaborative diagnosis on multi-source data of the diagnosis group to generate a fault judgment result. According to the invention, intelligent diagnosis and operation and maintenance management of the operation state of the signal lamp are realized, and the accuracy of fault identification and the processing efficiency are improved.

The invention discloses an AI algorithm-based road section violation behavior accurate identification and automatic warning system, and the system comprises an image acquisition module which is used for collecting a road monitoring image and carrying out the standardization processing; the feature extraction module is used for extracting semantic and structural information in the image based on a visual self-distillation network; the behavior modeling module is used for constructing a traffic behavior characteristic probability distribution model by using an improved multi-dimensional Gaussian modeling method; the anomaly detection module is used for comparing the current image features with the normal behavior model and outputting an anomaly score and a regional thermodynamic diagram; the warning judgment module judges whether warning is triggered or not according to the abnormal score and the state of the signal lamp; and the warning execution module is used for carrying out acousto-optic prompt, voice broadcast and image display through edge equipment. According to the method, image processing and AI identification technologies are fused, automatic identification and real-time warning of road section violation behaviors are realized, and the method has the advantages of high precision, fast response and easy deployment.

The invention relates to an intelligent traffic signal control method and system based on traffic flow prediction, and belongs to the technical field of intelligent traffic. Traffic vehicle video streams and traffic flow data are collected through a high-definition camera and a traffic flow sensor group, different vehicles and speeds, directions and movement tracks thereof are identified through the traffic vehicle video streams, special vehicles are judged, traffic violation behaviors and road abnormal conditions are monitored according to the traffic vehicle video streams and the traffic flow data, and the traffic violation behaviors and the road abnormal conditions are monitored. A traffic prediction model is established according to traffic vehicle video streams and traffic flow historical record data, and traffic flow, vehicle positions, vehicle categories, lane line information, vehicle movement tracks, traffic violation, road abnormal conditions, and traffic flow values and vehicle speeds in future time periods of all lanes at all intersections are obtained from a server in real time. And different signal lamp control schemes are generated according to different vehicles. According to the invention, a signal control scheme is designed in combination with vehicle types, traffic violation, road abnormity and other conditions, and accurate traffic congestion dispersion is realized.

The invention discloses an inland waterway congestion dredging method and device, and relates to the field of traffic control, and the method comprises the steps: obtaining multi-source traffic data and waterway meteorological and hydrological data of each ship in a waterway; performing space-time registration and fusion processing on the multi-source traffic data, generating comprehensive traffic situation information of the whole section of the channel, and extracting traffic flow characteristic parameters and channel congestion indexes; inputting the traffic flow characteristic parameters, the channel congestion index and the channel meteorological and hydrological data into a trained traffic flow prediction model to obtain traffic prediction information of key nodes in the channel in a future preset time window; based on the comprehensive traffic situation information and the traffic prediction information, generating preventive control parameters for channel key node signal lamps; and according to the traffic prediction information and the preventive control parameters, traffic guidance information is generated and sent to the corresponding ship terminals, and the preventive control parameters are sent to the corresponding signal lamp control machines. The overall passing efficiency of the channel can be improved.

The invention discloses an intelligent road traffic signal lamp dynamic regulation and control system and method based on artificial intelligence, and relates to the related field of signal lamp regulation and control, and the system comprises the steps: constructing a traffic state feature vector based on traffic flow data; the traffic state feature vector is analyzed in real time through a deep learning model, the traffic flow change trend in a future time window is predicted, a prediction result is generated, a dynamic signal lamp regulation and control strategy is generated and issued to a signal lamp control unit, the signal lamp state is adjusted in real time through the signal lamp control unit, and a regulation and control result is generated; and storing the regulation and control result and the traffic flow data to a traffic management database to perform data mining optimization, and generating a signal lamp control optimization suggestion to perform dynamic regulation and control on the intelligent traffic signal lamp. The technical problem that a traditional signal lamp is difficult to flexibly adjust according to the real-time traffic flow is solved, and the technical effects of dynamically adjusting the signal lamp time sequence, achieving intelligent timing and reducing the congestion phenomenon and the traffic accident rate are achieved.

The invention provides a signal lamp synchronization method and device, processing equipment, a program product and a medium, and relates to the technical field of Internet of Vehicles, the method comprises the following steps: obtaining signal lamp configuration information of a simulated traffic environment and mapping relation information between the simulated traffic environment and a real traffic environment, testing a signal phase and time sequence SPAT message of a real intersection received by the vehicle in a real traffic environment; according to the signal lamp configuration information, the mapping relation information and the SPAT message, determining a signal lamp group state of a simulation intersection corresponding to the real intersection; updating the simulated traffic environment according to the signal lamp group state corresponding to the simulated intersection so as to realize signal lamp synchronization between the simulated traffic environment and the real traffic environment; the simulated traffic environment is a traffic flow model which is established in simulation software and is used for simulating a real traffic environment. According to the scheme, the problem that the simulation world signal lamp and the real world signal lamp are difficult to accurately synchronize in the prior art is solved.

The embodiment of the invention provides an abnormal signal lamp data processing method and device, equipment, a medium and a program product, which can be used in the technical field of automatic driving. According to the method, after it is determined that abnormal signal lamp data exists in the vehicle flow direction, the abnormal type is determined according to the signal lamp data of the vehicle flow direction, then the signal lamp data of the vehicle flow direction are processed according to a data processing strategy corresponding to the abnormal type, and target signal lamp data corresponding to the vehicle flow direction are determined. According to the scheme, the traffic flow direction signal lamp data is processed according to the data processing strategy corresponding to the abnormal type, so that the situation that the same traffic flow direction has multiple signal lamp data is processed, and the same traffic flow direction only has one target signal lamp data at one moment; the autonomous vehicle may travel according to the target signal light data.

The invention provides a smart city traffic abnormity monitoring method and system based on an Internet of Things large model, and relates to the field of Internet of Things and smart city traffic management. The system comprises an abnormity judgment module and a diversion module. The abnormity judgment module is configured to perform abnormity judgment on the target area according to the multi-source data and determine a plurality of hidden danger hot areas; the diversion module is configured to determine a plurality of standby routes according to the judgment result and the regional road network topological map; determining a plurality of main routes according to the plurality of standby routes and the position information of the plurality of variable information boards, generating a diversion instruction, and sending the diversion instruction to the emergency supervision object platform; and based on the diversion instruction, controlling a plurality of variable information boards to display a sketch of a corresponding main route, and controlling traffic lights on a plurality of standby routes to perform green light signal display according to a passing period. According to the method, the main pushing route of the variable information boards can be reasonably determined and controlled, potential traffic accident hidden dangers are prevented, and traffic safety is guaranteed.

The invention provides a multi-modal traffic flow prediction method and system based on deep learning. The method comprises the steps that an electronic device obtains multi-modal vehicle driving collection data of a specific intersection; predicting by using the traffic flow prediction model to obtain traffic flow prediction data of the specific intersection; and inputting the traffic flow prediction data into the reinforcement learning model of the double-Q network structure to obtain a traffic signal lamp regulation and control strategy of the specific intersection. According to the embodiment of the invention, the traffic flow prediction model is utilized to obtain the traffic flow prediction data, the reinforcement learning model of the double-Q network structure is utilized to construct the Markov decision-making model with the intersection traffic efficiency maximization as the target, the Markov decision-making model is solved, and the traffic signal lamp regulation and control strategy of the specific intersection is obtained. According to the mode, the traffic signal lamp control strategy is determined, model parameters do not need to be calculated again, calculation time consumption is reduced, and sudden events can be handled.

The invention provides a signal machine flashing light monitoring method and system based on full-electronic interlocking, the monitoring method is applied to a monitoring system comprising an interlocking machine and a flashing light power supply, and the monitoring method specifically comprises the steps that in response to a control demand, the interlocking machine outputs a flashing light driving signal to a signal machine, and the signal machine is driven to execute flashing light; filament current and on-off state of each lamp position of the signal machine are collected in real time, and signal machine flashing fault detection is carried out according to the filament current and on-off state of each lamp position; and when a signal machine flashing light fault is detected, the fault type is identified according to a fault detection result, and a corresponding operation and maintenance strategy is formulated. According to the invention, through real-time acquisition and linkage analysis of two parameters of filament current and on-off state, flashing lamp fault identification requirements under full-electronic interlocking are met, the problem of misjudgment caused by frequent fluctuation of current is avoided, other fault types possibly existing in the flashing lamp control process can be further covered, the fault missed judgment risk is reduced, and the working efficiency is improved. And the safety of flashing display of the signal lamp is ensured.

The invention discloses a ship navigation signal lamp with anti-freezing and anti-fog functions, and relates to the technical field of signal lamps, the ship navigation signal lamp comprises a base, the base is fixedly connected with a fixing frame, the fixing frame is fixedly connected with a heat collecting ring, a lamp wick is fixedly connected between the fixing frame and the heat collecting ring, and the fixing frame is fixedly connected with a lampshade. According to the signal lamp, in an environment with relatively low temperature or humidity, the air inlet is automatically and locally closed through the opening and closing plate, and the opening of the air inlet is reduced, so that entering of cold air is reduced; heat generated when the inner lamp wick works is gathered by the heat collecting ring and then sequentially passes through the gap between the lampshade and the heat conducting frame and the gap between the lampshade and the pressurizing ring to be guided to the outer wall of the lampshade in an accelerated mode, the outer wall of the lampshade is prevented from being frozen or condensed fog water while heat dissipation is conducted, a heat source is saved, and meanwhile heat dissipation efficiency is improved. The accelerated hot air flow can blow water flow on the lampshade wall downwards, the water flow is accelerated to flow downwards, and the light transmission of the lampshade is guaranteed.

The invention discloses a traffic signal lamp control method and system based on a traffic large model, and relates to the technical field of traffic control, and the method comprises the steps: collecting and collecting traffic flow data in real time, and carrying out the optimization processing; using historical traffic flow data to train a traffic large model; the real-time traffic flow data is utilized to finely adjust model parameters of the traffic large model, meanwhile, the real-time traffic flow data is input into the traffic large model, and the traffic large model predicts traffic flow data within one hour in the future, generates corresponding traffic signal lamp regulation and control suggestions and transmits the traffic signal lamp regulation and control suggestions to the traffic signal control module; the traffic signal control module has a set of default basic regulation and control strategies; and after receiving the regulation and control suggestion, the traffic signal control module compares real-time traffic flow data with a traffic large model prediction result, generates a final regulation and control plan in the next one hour, and executes the final regulation and control plan. The traffic light control strategy is adjusted in real time, so that the traffic jam is relieved, and the road passing efficiency is improved.

The invention relates to the technical field of traffic management infrastructures, and particularly discloses a holographic traffic signal lamp system and method, and the method comprises the steps: collecting vibration wave data in real time through a vibration detector, and remotely transmitting the collected vibration wave data to a third-party platform; the method comprises the following steps: extracting vibration wave archived data marked as abnormal from a three-party data source as a data set for comparative analysis, and introducing a deep learning algorithm to carry out waveform feature extraction on vibration wave data and each abnormal vibration wave archived data; the vibration wave data and each abnormal vibration wave archived data are subjected to dynamic query response analysis based on fluctuation characteristics, so that potential association between the real-time vibration wave data and the abnormal vibration wave archived data is mined, and intelligent earthquake early warning release is realized. In this way, the problem of false triggering caused by transient interference factors can be effectively solved, the accuracy and reliability of earthquake early warning are improved, and the situations of false alarm and missing alarm are reduced.

The invention discloses a smart city traffic planning method and system based on deep learning, and relates to the technical field of city traffic management, and the method comprises the steps: recognizing an activity region of a traffic disturbance activity, constructing a disturbance region graph Ga, collecting vehicle driving related data and lamp control cycle data, and constructing a standardized data set H; coupling modeling is carried out on path length change and direction deviation of the traffic driving path before and after the traffic disturbance activity so as to quantify the traffic state of the activity area, a path disturbance deviation coefficient Py is acquired, the traffic state of the activity area is evaluated in combination with a path disturbance threshold Pyyz, and when the traffic state is in an abnormal state, the traffic disturbance deviation coefficient Py is calculated. According to the method, signal lamp cycle rhythm analysis is carried out, a phase dislocation propagation index Xw is obtained, and coupling modeling is carried out to obtain a comprehensive rhythm adaptation index Zh, so that the risk level of a traffic signal control system is divided, a system adjustment instruction is generated, intelligent adjustment is carried out, and the intelligent, precise and real-time level of smart city traffic planning is improved.

The invention discloses a traffic signal lamp control method. The method comprises the steps of firstly predicting a first traffic flow and a first congestion level of a target area at a first moment; if the first congestion level is a serious congestion level, determining a second signal lamp timing scheme of the intersection according to the current first signal lamp timing scheme and the signal lamp timing adjustment amount of the intersection for each intersection at the upstream of the target area; if the first congestion level is a general congestion level or a slow traffic congestion level, determining a second traffic flow difference value between the first traffic flow and a traffic flow lower boundary value of a traffic flow range to which the first traffic flow belongs; obtaining a third traffic flow difference value between the traffic flow upper boundary value and the traffic flow lower boundary value of the traffic flow range; and for each intersection, determining a fifth signal lamp timing scheme of the intersection according to a first ratio of the second traffic flow difference value to the third traffic flow difference value. According to the invention, the signal timing scheme of the intersection can be automatically adjusted according to the change of the congestion condition of the target area, and the accuracy of traffic signal lamp control is improved.

The invention discloses sound equipment for adjusting the special effect of a horse race lamp, and the sound equipment comprises a tone detection module which is used for monitoring the rotation angle and direction of a tone modification knob in real time, and outputting a corresponding tone grade signal; the light control module is used for responding to the tone level signal and generating a corresponding light control signal, and the light control signal comprises that relative to a reference tone level, when the tone level is increased by one level, the light irradiation range is expanded by a first preset proportion, the brightness is increased by a first set proportion, and when the tone level is reduced by one level, the light irradiation range is expanded by a second preset proportion; the lamplight irradiation range is shrunk by a second preset proportion, and the brightness is reduced by a second set proportion; and the horse race lamp assembly is used for receiving the light control signal and dynamically adjusting the light effect of the horse race lamp. According to the invention, the signal of operating the tone modification knob by the user can be detected, the tone grade signal can be determined, the mapping relation between the tone grade and the light parameter can be established, the correlation between tone change and the light effect can be ensured, accurate regulation and control of the light irradiation range and brightness can be realized, deep coupling of auditory adjustment and visual feedback can be realized, and the user interaction experience can be improved.

The invention discloses a material warehouse-in and warehouse-out management method, and relates to the technical field of material management, and the method comprises the steps: obtaining goods shelf two-dimensional code information on a goods shelf through a scanning gun, and carrying out the blue display of a preset signal lamp; acquiring dial plate two-dimensional code information on the packaging plate by using a scanning gun, placing the packaging plate at a blue lamp vacancy on a goods shelf, and extracting blue lamp position information of the blue lamp vacancy; binding the position information of the blue lamp with the two-dimensional code information of the dial plate, and storing the information in a preset storage system; obtaining production material information, and sending the production material information to a worker to take a target material; if the target material information is wrong, a target storage position corresponding to the target material is red, and a sound alarm is given; and turning off the red light and the sound alarm, performing secondary scanning on the goods shelf two-dimensional code information and the dial plate two-dimensional code information by using the scanning gun, and putting the target material back to the goods shelf. The method has the effects of reducing the management difficulty and disorder degree of the warehouse materials and improving the safety of the warehouse materials.

The invention discloses an integrated operation and maintenance method for traffic signal lamp fault detection, and the method comprises the steps: S1, signal lamp end detection and fault study and judgment: a signal lamp end fault detection circuit collects the input voltage current value and the output voltage current value of each lamp color channel of a signal lamp, so as to distinguish the abnormal power-off control and the lamp-off control; s2, signal lamp grouping management and information aggregation: the signal lamps transmit the self-inspection data to a near point extension set, and the extension set transmits the gathered and converted signal lamp self-inspection data to an intersection host; s3, lamp and machine integrated fault detection: a signal machine generates a signal lamp with accurate positioning through signal lamp self-inspection data and a connection state reported by an access host, exterior line fault information and multi-channel green conflict research and judgment; and S4, lamp-machine integrated fault operation and maintenance: positioning the fault to a signal lamp or a signal lamp connection external line or a signal machine output external line. And the requirements of signal lamp fault accurate detection and rapid positioning treatment are met.