176 results about "Environment surveillance" patented technology

The invention provides an intelligent agricultural environment monitoring system based on the Internet of Things, and relates to the technical field of data processing. The feature extraction and analysis module is used for performing segmented statistical analysis on the soil humidity original data according to the soil humidity original data in combination with historical soil humidity data, historical environment temperature data and preset near-period soil humidity feedback data, and automatically extracting a humidity change rate and an abnormal trend index data set under multiple time windows; the self-learning judgment module is used for dynamically adjusting the current judgment threshold value based on a self-learning algorithm, judging the soil humidity original data in combination with the humidity change rate and the abnormal trend index, and generating a judgment signal for judging whether local irrigation response is triggered or not; the response control module is used for automatically generating an irrigation equipment starting instruction; the irrigation execution module is used for executing irrigation operation according to the irrigation equipment starting instruction; according to the invention, the accuracy of agricultural environment monitoring is improved.

The invention discloses an intelligent warehousing dynamic optimization system based on a digital twinborn technology. The system comprises the following steps: S1, creating a digital twinborn model: acquiring basic data of an entity warehouse and constructing an accurate digital model; s2, data collection and integration: deploying Internet of Things equipment and realizing real-time transmission and processing of data; s3, constructing an analysis algorithm: developing an advanced analysis algorithm and implementing a machine learning model; s4, dynamic optimization and adjustment: automatically adjusting a storage layout and optimizing a warehouse-in and warehouse-out process; and S5, prediction and early warning: analyzing and predicting potential problems and setting an alarm mechanism based on historical data. According to the invention, the real-time performance and accuracy of data are obviously improved, the environment monitoring capability is enhanced, the cargo safety is guaranteed, and the space utilization rate is greatly improved.

The invention discloses a server fault monitoring system, which relates to the technical field of servers, and is characterized in that a data acquisition terminal deployed in a machine room acquires environment monitoring data and software monitoring data of a server, and the environment monitoring data and the software monitoring data are used as server monitoring data to be sent to a corresponding edge server; and when the edge server detects that the software / hardware monitoring data is abnormal, extracting related abnormal data from the corresponding server monitoring data, and generating an abnormal report log. And the central server determines that the server has a fault according to the exception report log and the related exception data, and generates fault data information. And the monitoring terminal locates a graphic object corresponding to the fault server in the three-dimensional machine room virtual model according to the equipment identifier, updates the display state of the graphic object of the server into a fault state, and generates a fault data interaction label according to the fault data information. According to the invention, the problem of relatively large fault response delay in related technologies can be solved, and the server fault monitoring efficiency can be effectively improved.

Automated, environmentally monitored and controlled storage units and systems for storing, monitoring, and maintaining a supply of products, particularly temperature sensitive pharmaceutical and / or other high-value products, be they temperature sensitive or not. Such automated storage units contain an array of independently addressable holding locations for containers with product in one or more environmentally monitored (e.g., for temperature, humidity, etc.) and controlled zones fitted with appropriate environmental sensors. In preferred embodiments, the automated storage units also include a reader to track product information and status. Product loading, retrieval, and movement within such automated storage units is performed by a computer-controlled robot. A user interface device, preferably in communication with an application service provider to provide remotely managed inventory management and other services, provides users with inventory- and product-specific information.

The invention discloses a base liquor full-life-cycle traceability management method based on a sovereign block chain. The base liquor full-process management is realized by constructing systems such as double-chain cooperation, full-process digital monitoring and credible evidence storage. In the raw material link, a block chain is used for establishing a quality file, and in the production link, the industrial Internet of Things is used as a basis, and a layered chaining and double-code anti-counterfeiting technology is adopted; a dynamic environment monitoring chain is built in a warehouse logistics link, and a multi-source sensing and condition triggering evidence storage strategy is applied; constructing a two-way verification system in a sales link to combine with risk assessment; and a carbon footprint tracking mechanism is introduced in the recovery link. The method can reduce the risk of raw material adulteration, improve the quality inspection efficiency, guarantee the production quality and brand safety, improve the safety and efficiency of warehouse logistics, achieve the guarantee of full-link certified products, improve the full-life-cycle management, improve the reliability of a block chain network, employ the verification mechanism of an oracle machine to verify and guarantee the real chaining of the data of each link, and improve the efficiency of the whole-link certified products. And consistency of online and offline data is ensured.

The invention relates to the technical field of engineering monitoring, measurement and control, in particular to an intelligent acquisition instrument based on AI analysis and self-adaptive sampling and a self-adaptive interrogation method. According to the technical scheme, the device comprises a multi-source sensing interface module, an edge intelligent processing module, a self-adaptive sampling module, a communication module, a storage module, a key interrogation module, a power supply protection module and a structure packaging module, multi-dimensional feature fusion and edge decision making are achieved, the self-adaptive sampling module automatically adjusts sampling frequency according to an AI analysis result and an environment threshold value and has a dynamic threshold value adjusting function, the communication module supports various wireless protocols, and the key interrogation module can achieve automatic sensor recognition and instant data acquisition and uploading. The system can be widely applied to the fields of industrial monitoring, environment monitoring and equipment health management, and efficient and intelligent data acquisition and management are realized.

The invention discloses a coal storage and transportation intelligent management method and system, relates to the technical field of intelligent management systems, and aims to solve the problems of lack of environment monitoring, scheduling decision lag, extensive safety response and serious data island in the prior art. The method comprises the following steps: collecting the physical state, environmental parameters and operation behavior data of a coal storage yard in real time through a distributed sensor network; constructing a three-dimensional dynamic digital twinborn model and inputting the model into a time sequence neural network to predict the risk of spontaneous combustion, collapse or dust explosion in the future; and generating a dynamic scheduling instruction in combination with the task priority and the equipment state, and triggering a multi-level security response mechanism. The system comprises a sensor network module, a data fusion modeling module, a risk prediction module, a scheduling optimization module, and a closed-loop control and safety response module. According to the scheme, safety early warning preposition, scheduling decision intelligent optimization and resource energy efficiency collaborative improvement in the storage and transportation process are achieved, and the response capability and operation reliability of the coal supply chain are remarkably enhanced.

The invention relates to the technical field of building construction monitoring, and discloses a building construction safety environment monitoring system and a monitoring data analysis method. The system comprises a data acquisition unit, a risk judgment unit, an adjustment execution unit, an anomaly analysis unit, a strategy correction unit and a failure early warning unit. The data acquisition unit acquires construction site environment and structure parameters at fixed intervals; the risk judgment unit carries out threshold judgment on the parameters and generates abnormal type signals; the adjustment execution unit executes parameter adjustment according to the priority of the exception type; the anomaly analysis unit calculates a parameter offset proportion and an adjustment efficiency value based on the anomaly signal and the adjustment data; the strategy correction unit adjusts the data acquisition frequency and optimizes the adjustment intensity; the failure early warning unit counts the total amount of abnormities and generates a failure signal in combination with the construction duration. According to the system, comprehensive monitoring, exception handling, system optimization and risk early warning of a construction safety environment are realized.

The invention discloses a highway service area intelligent environment monitoring and management system based on the Internet of Things, and relates to the field of environment monitoring and management, and the system comprises an acquisition module which is used for uploading the carbon emission source data of each energy consumption unit of a target service area, synchronously acquiring the carbon concentration in the environment of the target service area and the associated meteorological parameters of the same time interval, and transmitting the acquired data to a cloud server; constructing a carbon footprint basic data set; the traceability module is used for receiving the carbon footprint basic data set, constructing a traceability link based on the data set, analyzing carbon emission key nodes, and identifying a carbon emission ratio and a generation path of each node; according to the method, carbon emission related data and associated meteorological information are collected, a complete carbon footprint data basis is constructed, carbon emission key links and formation paths are carded out through reasonable analysis, the emission reduction potential of each link is calculated in combination with the actual operation condition of a service area, and links needing to be regulated and controlled are determined according to double judgment standards.

Systems and methods for managing asset risk in computer environment can include receiving, by one or more processors, data indicative of attributes of an asset of the computer environment. The one or more processors can determine a risk context based on the data indicative of the attributes of the asset. The one or more processors can update a risk score of the asset based at least on the risk context. The one or more processors can adjust, responsive to the risk score of the asset, a configuration parameter of at least one of the asset or another asset to mitigate a security risk associated with the asset.

The invention discloses an intelligent agricultural big data system, and belongs to the field of agricultural big data, and the system comprises an environment monitoring module, a sensing layer deploys a sensor to collect original data, and a transmission layer is provided with an edge gateway which is connected with the sensor and carries out the transmission of the original data; the equipment layer is used for regulating and controlling irrigation, ventilation and light supplement schemes, and the control layer is used for optimizing MQTT message middleware to control the agricultural Internet of Things system; according to the data management module, a data collection layer obtains original data, a data processing layer processes the original data according to a three-layer data cleaning mechanism, and a data storage layer stores the processed data; according to the system management module, the data application layer constructs an interface covering Web, a mobile terminal and AR equipment, the data display layer generates a soil moisture thermodynamic diagram, a crop growth distribution diagram and an equipment operation state diagram, and intelligent management of agricultural production is ensured. The advanced Internet of Things technology is adopted, and the accuracy and the real-time performance of data acquisition are improved.

The invention relates to the technical field of multi-cloud resource scheduling, in particular to a reinforcement learning system and method for resource scheduling in a multi-cloud environment, and the method comprises the steps: collecting first state performance monitoring data of a plurality of heterogeneous cloud platforms in the multi-cloud environment in real time through an environment monitoring module, and constructing a dynamic graph structure; performing multiple rounds of message passing and node aggregation on the dynamic graph based on a graph neural network to generate a structured state vector fusing topological features; and analyzing the state vector based on a strategy network, outputting an action parameter containing a resource selection probability and a configuration parameter, analyzing the action parameter through an autoregression decoder, generating a cross-cloud resource scheduling instruction sequence, and converting the cross-cloud resource scheduling instruction sequence into an application program interface instruction for execution. And the strategy adjustment module constructs a multi-cloud environment resource scheduling score and drives dynamic optimization of a strategy network. According to the method, the global optimization capability of multi-cloud environment resource scheduling can be effectively improved.

The invention relates to the technical field of building environment monitoring, and discloses an intelligent building environment monitoring system and method, and the method comprises the steps: S1, collecting the related environment information of each preset monitoring point in a warehouse through a first environment collection module; s2, comparing each acquired environment information parameter with a corresponding preset early warning threshold value, and if any environment information parameter exceeds the corresponding preset early warning threshold value, generating an abnormal early warning signal of the monitoring point; according to the method, warehouse monitoring point environment parameters are collected in real time through distributed sensors, single-point threshold comparison is performed firstly to trigger preliminary early warning, then environment characteristic values are calculated through multi-parameter weighting and compared with a historical abnormal range, high-density sampling analysis is performed on a characteristic value abnormal region through an inspection robot, and the abnormal region is subjected to early warning. The method overcomes the defects that a traditional warehouse environment monitoring mode is high in false alarm rate, lacks comprehensive evaluation, cannot perform dynamic inspection and the like.

The invention discloses a communication machine room environment monitoring system and device, and relates to the technical field of machine room environment monitoring, and the communication machine room environment monitoring system comprises a fusion alarm module, a fault root cause analysis module and a dynamic air duct optimization energy saving module. The fusion alarm module significantly reduces false alarms through heterogeneous sensor space-time alignment, confidence weighting and sound vibration interference filtering; the fault root cause analysis module constructs an equipment dependence graph based on CAD topology and CFD wind resistance, and uses a Bayesian network to lock root cause equipment in a second level and perform 3D visual positioning; the dynamic air duct optimizing and energy-saving module controls a fan and a flow guide plate in a closed-loop mode through a high-resolution thermodynamic diagram and reinforcement learning, cold energy is precisely put according to needs, energy is saved, and consumption is reduced. The system effectively improves the alarm reliability, shortens the fault positioning time, and reduces the PUE of a machine room.

According to the locatable basement area environment monitoring method based on the Internet of Things, Bluetooth mobile beacons are built in a plurality of monitoring modules, communication between receiving base stations in a basement is combined, and the angle between the Bluetooth mobile beacons and a receiving antenna of a data all-in-one machine can be accurately obtained through an AOA positioning algorithm; the position information of the Bluetooth mobile beacon is trimmed through an Atmann-Z model algorithm, the position information of the monitoring module can be accurately obtained, matching of environment monitoring of the monitoring module and the position information can be accurately obtained by combining the position of the monitoring module and data information collected by the monitoring module, and precise environment monitoring in a basement area is achieved.

The invention relates to a field programmable gate array (FPGA)-based intelligent environment monitoring system in the field of environment monitoring systems, which comprises an FPGA master control module used for processing and analyzing monitoring data of each partition to obtain a partition state and an environment parameter change trend of the partition in the next one hour, and selecting a corresponding processing strategy according to the partition state; the partition management module is used for setting the type of each partition and judging and associating similar partitions; the control module is used for controlling related equipment in each partition to execute a preset processing strategy; the data acquisition module is used for data acquisition of each independent partition; the self-adaptive processing module is used for adjusting the range of the basic threshold value, the scene threshold value and the alarm threshold value; and the abnormity evaluation module is used for evaluating the abnormity probability according to the environment change trend and the threshold range, and the system can associate similar areas by monitoring the environment parameters of each area in real time and comprehensively evaluating the similarity of the areas so as to realize efficient environment monitoring and management.

The invention discloses an intelligent robot access management and control system for an unmanned archive, and the system comprises a central controller which is used for coordinating the functions of all modules, and a high-precision positioning module which is used for calculating the real-time position of a robot through a fusion positioning algorithm; the dynamic path planning module is used for outputting the optimal access path of the robot; the intelligent storage distribution module is used for optimizing storage rack space based on a greedy algorithm, inputting a file size parameter set and outputting three-dimensional coordinates and shelf numbers; the multi-robot cooperation module is used for distributing transportation tasks by applying an improved contract network protocol; the self-calibration mechanical arm module is used for controlling a mechanical arm to accurately execute a grabbing task; the state detection module is used for detecting a system state; and the environment monitoring module is used for monitoring the environment. According to the invention, intelligent access and management of archives in a full-automatic unmanned archive are realized, the problem of inaccurate positioning is solved, the storage efficiency is improved, and the safety and stability of the system are enhanced.

The invention relates to the technical field of cold-chain logistics and information processing, and provides a cold-chain logistics information distribution and tracing system for data management, which comprises a server, a distributed verification module, a node sampling prediction module, a logistics data push module and an environment monitoring module, the distributed verification module is used for collecting data port states of a plurality of logistics nodes and performing consistency verification on node data so as to form an inter-node trusted data set; the node sampling prediction module is used for carrying out periodic sampling on a freight vehicle, storage equipment and a temperature control device, calculating a freight priority index Freight Priority Index and generating prediction data; the logistics data pushing module is used for dynamically pushing node data according to a freight transport priority index and a system load index (Network Load), and generating a delivery feedback index (Delivery Feedback) on the basis of feedback information; the environment monitoring module is used for monitoring cold chain transportation and storage environment parameters in real time, and recording and tracing temperature control states and safety alarm information of all nodes.

The invention discloses a cross-border logistics intelligent tracking and anti-counterfeiting system based on a block chain, and relates to the field of cross-border logistics intelligent tracking and anti-counterfeiting, and the method comprises the steps: collecting logistics package feature information, generating a feature identifier, submitting the feature identifier to a block chain network, obtaining a digital anti-counterfeiting code through segmented encryption processing, and transmitting the digital anti-counterfeiting code to the block chain network; and in the transportation process, parcel feature information is collected for comparison and verification. Meanwhile, in-transit environment data are collected, an environment monitoring threshold value is determined according to the parcel feature identifier, and an adjustment strategy is executed. And carrying out fusion analysis on the anti-counterfeiting verification result and the environment regulation result to obtain a logistics risk level, and determining an optimal logistics path according to the logistics risk level. And planning a node verification strategy according to the optimal logistics path, collecting verification data to generate node proof, and updating the logistics track in the smart contract after block chain network verification. According to the invention, credible tracking and intelligent anti-counterfeiting of cross-border logistics are realized, and the logistics safety is improved.

The application discloses a kind of server fault monitoring systems related to server technical field, and the data acquisition terminal of deployment in computer room gathers the environmental monitoring data and software monitoring data of server, and as server monitoring data is sent to corresponding edge server.Edge server detects that software / hardware monitoring data exists exception, then from corresponding server monitoring data extraction relevant exception data, and generate exception report log.Central server determines that server exists fault according to exception report log and relevant exception data, then generate fault data information.Monitoring terminal locates the graphic object of fault server corresponding according to equipment identification in three-dimensional computer room virtual model, and the display state of server graphic object is updated to fault state, simultaneously generate fault data interaction label according to fault data information.The application can solve the problem that related technical fault response delay is larger, and can effectively improve server fault monitoring efficiency.

The invention, which relates to the technical field of data monitoring, discloses a wireless multi-sensing data monitoring terminal system for smart rice and fishery, comprising a data setting module for setting an initial monitoring frequency; the environment monitoring module monitors the growth condition of rice and fish, soil data and the state of aquatic animals in real time, and captures the growth environment change of rice and fish in time; the data processing module is used for quantifying the change degree of the rice and fish growth environment according to the characteristic data related to the change of the rice and fish growth environment and the abnormality of the cultured object extracted by the environment monitoring module; the early warning module is used for predicting the growth environment change through a machine learning model, and automatically sending out an early warning signal when the rice and fish growth environment change is predicted to be abnormal; and the dynamic adjustment module dynamically adjusts the monitoring frequency of the monitoring equipment so as to cope with the change of the growth environment of rice and fish. According to the method, the environmental change rate is dynamically adapted by adjusting the monitoring frequency, so that the robustness, timeliness and decision accuracy of the system can be remarkably improved.

The invention discloses an intelligent control method and system for air purification and environment monitoring of a radiotherapy machine room, and relates to the technical field of industrial control. The intelligent control method and system for air purification and environment monitoring of the radiotherapy machine room comprises the following steps: S1, collecting original environment data of a plurality of key positions in the radiotherapy machine room, and preprocessing the original environment data; s2, monitoring the state and interference characteristics of radiotherapy equipment, marking a high interference period in real time, and adding a label structure to original environment data; s3, performing stability and reliability evaluation on the original environment data; s4, performing prediction correction compensation on the low-credibility original environment data; and S5, wind pressure intensity control is started by integrating the interference intensity grade, the stable and reliable evaluation result and the prediction correction compensation result. The problem that the data quality is unstable due to the fact that the sensor is prone to jumping and failure in the strong electromagnetic and irradiation environment is solved.

The invention discloses a monitoring method and device for an intelligent digital air conditioner system, and belongs to the technical field of intelligent air conditioner control and environment monitoring. Triggering the environment data collaborative awareness protocol layer to perform composite sampling on the target area, writing sampling data into the first cache area, and analyzing disturbance factor weights corresponding to the monitoring indexes; when the weight accumulated value reaches a dynamic threshold value, a response event identification signal is generated, and a response model corresponding to the control level is selected; loading the model to a decision scheduling layer, and generating a fine tuning instruction; after the instruction is issued, feedback information is collected to a second cache region; when the feedback deviation exceeds a correction threshold value, the sampling process is restarted, and the disturbance weight distribution matrix is updated; quick recognition and response control of multi-parameter coupling disturbance can be achieved, and the environmental adaptability and control precision of the air conditioning system are improved.

The utility model discloses an intelligent storehouse environment monitoring collection terminal relates to environment monitoring technical field, include: collection terminal body and terminal seal cover, and terminal seal cover fixes through bolt and collection terminal body, and the inner wall surface of terminal seal cover is installed heat exchange structure, and the lower wall surface of collection terminal body is installed cooling structure, and the lateral wall surface of collection terminal body is installed collection fixed structure, and the inside movable mounting of collection fixed structure has collection structure, the utility model discloses a sealing structure, to the whole closed processing of collection terminal, can make collection terminal and external environment insulate, guarantee its working environment's temperature normal at the same time, still can avoid the influence of collection terminal by external environment, and then guarantee its working stability. And the utility model adopts magnetic attraction fixed and contact connection to sensor, and convenient operating personnel replace sensor, that is, convenient operating personnel collect different data of warehouse environment.

The invention provides a blue space degradation diagnosis method and system, computer equipment and a medium, and belongs to the field of ecological environment monitoring, and the method comprises the steps: obtaining a remote sensing image, climate data and human activity data of a to-be-diagnosed blue space, and extracting water body images of the to-be-diagnosed blue space at a plurality of time points through the remote sensing image; calculating a multi-class landscape form index of each grid in the water body image; clustering the water body image based on the multi-class landscape form index of each grid to obtain a blue space combination mode corresponding to each grid; inputting the climate data, the human activity data and the landscape form index into a random forest model to obtain a contribution degree; and based on the contribution degree, screening from the climate data, the human activity data and the landscape form index to obtain a water body change driving factor, and determining a degradation diagnosis result of the blue space to be diagnosed. The blue space combination mode constructed by the method can reflect the structural difference of the blue space, and the accuracy of degradation diagnosis of the blue space is guaranteed.

This invention relates to the field of integrated driver-trailer technology for heavy-duty commercial vehicles, specifically to a 360° surround view system for integrated driver-trailer heavy-duty trucks. The system includes an environmental monitoring controller, with its input linearly connected to cameras and its output linearly connected to a multimedia screen. The environmental monitoring controller receives image information from four cameras on the driver vehicle and three cameras on the trailer, processes the image information, and sends it to the multimedia screen. A corner recognition calibration ball is located at the front of the tanker truck, used to identify the hinge angle between the driver and trailer in real time and send the acquired data to the environmental monitoring controller. This system solves the problem of drivers being unable to observe the 360° field of vision around the driver and trailer in real time from inside the cab, resulting in blind spots during vehicle movement, turning, and reversing, which can easily lead to safety accidents. It improves the safety of people, vehicles, and goods during train transportation and effectively reduces the incidence of safety accidents caused by blind spots during transportation.

1. The name of the design product: monitor. 2. The use of the design product: the design product is used for environmental monitoring. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The application discloses a wireless sensor network distributed guaranteed probability estimation method under a deception attack, and specifically comprises the following steps: a nonlinear system mathematical model under the condition that innovation is deceived is established; a neural network-based distributed state estimator structure model is established according to the nonlinear system mathematical model under the condition that innovation is deceived; a neural network weight matrix adaptive updating strategy is designed; a distributed guaranteed probability state estimator gain is designed; and estimator parameters are optimized to achieve local optimal estimation performance; the application comprehensively considers the nonlinear characteristics and the influence of malicious attacks existing in actual engineering, can be widely applied to military monitoring systems and environmental monitoring systems, estimates the state of a monitoring or monitoring object, is more in line with engineering application, and is high in practicality.

The utility model discloses a bridge hanging basket monitoring and alarming integrated system and a construction system. The integrated system comprises a data processing module, a main beam stress sensor, a frame body stress sensor, a truss tilt angle sensor, a frame rail distance measuring sensor, a video monitor, an environment monitoring sensor and an alarm terminal. The construction system comprises the integrated system. The system has the beneficial effects that through multi-dimensional real-time monitoring and accurate alarm, the stress, displacement or inclination angle abnormity of the hanging basket can be found in time, and the safety in the construction process is ensured; due to the second-level response capability and real-time data transmission of the system, constructors can quickly take measures when abnormity occurs, and the risk of accidents is effectively reduced; in addition, through wireless data transmission and a remote monitoring platform, the system reduces the pressure of on-site manual inspection, and improves the efficiency and precision of construction management.

1. Name of the product in this design: Intelligent Marker Post (DS-C11). 2. Application of this design: for use as a path indicator for underground pipelines in the power, communication, gas, water supply, and railway sectors, and for monitoring the surrounding environment. 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.