181 results about "Safety condition" patented technology

The invention discloses a mountainous area high pier cast-in-place safety detection method based on multi-source data fusion, and relates to the technical field of intelligent building safety monitoring, and the method comprises the steps: deploying a sensor network, a multi-angle holder video monitor and an unmanned aerial vehicle, covering a mountainous area high pier for comprehensive monitoring, and collecting multi-source data; transmitting the multi-source data to an edge computing node in real time through a wireless network, and preprocessing the multi-source data to form a standardized multi-source data set; applying a spatio-temporal data fusion method, combining historical data and a comprehensive data model to predict a security risk, and generating a risk factor; threshold and rule abnormity identification is carried out on the risk factors, the safety condition is evaluated in real time, early warning is triggered in real time, and disposal suggestions are provided. According to the method, the safety detection efficiency and accuracy in the mountainous area high pier cast-in-place process are remarkably improved through multi-source data fusion and a quantum enhancement multi-modal algorithm, the triggering speed of safety early warning is effectively increased, and the safety guarantee of a construction site is remarkably enhanced.

The invention discloses a quality safety optimization method and system based on a multi-modal vertical large model technology, and relates to the technical field of quality safety optimization systems.The method comprises the steps that quality safety related data are collected from a multi-modal data source and preprocessed; fusing data through features and decision levels; a vertical large model of an improved Transform architecture is constructed by using fusion data, a quality feature extraction layer and a safety rule embedding layer are provided, and adaptive learning rate and gradient clipping training are used; inputting the new data into the large model to analyze the quality safety condition, including defect prediction, risk assessment and problem early warning; and according to an analysis result, generating an optimization suggestion through rule reasoning and reinforcement learning. According to the invention, multi-modal quality safety data can be comprehensively collected and preprocessed. The vertical large model is high in pertinence, quality defects, safety risks and potential problems are accurately analyzed, the optimization suggestion module is combined with rules and reinforcement learning, suggestions with expected effects and priorities are generated, and the quality safety level and the resource utilization efficiency are improved.

The invention relates to a coal mine potential safety hazard characterization method and system based on a knowledge graph, and belongs to the technical field of coal mine safety. The method comprises the following steps: data collection: collecting coal mine daily safety inspection records including hidden danger types, occurrence places, time and related descriptions; data preprocessing: cleaning, classifying and standardizing the collected data so as to facilitate subsequent knowledge extraction and graph construction; and knowledge graph construction: based on the preprocessed data, identifying key entities, extracting relationships among the entities, and constructing a coal mine potential safety hazard knowledge graph. Through the hidden danger correlation analysis and risk assessment module in the knowledge graph, the system can assess the risk degrees of different hidden dangers in real time and generate corresponding early warning information according to the assessment result, and the dynamic early warning mechanism enables managers to master the safety condition of a coal mine in time and quickly respond to potential safety threats.

The invention provides a bridge structure risk prediction method and system based on digital twinning, and relates to the technical field of bridge structure risk prediction, and the method comprises the steps: obtaining bridge stress node displacement data, environment humidity data, and bridge visual and acoustic monitoring data through the system; the system constructs a digital twinborn model, simulates stress and deformation of a bridge under different load conditions, and calculates a stress deformation potential risk coefficient according to a maximum stress value and an average deformation value. The monitoring risk coefficient is calculated by extracting the total crack length in the visual monitoring data and the frequency characteristics of the acoustic data. And calculating a final risk coefficient by combining the stress deformation potential risk coefficient, the monitoring risk coefficient and the humidity data so as to judge the safety condition of the bridge. According to the method, the accuracy and reliability of bridge safety assessment in a complex environment are enhanced.

The invention provides a stadium intelligent security and protection system based on a digital twin technology, and aims to improve the intelligent level and response speed of stadium safety monitoring. The system collects audience behavior data through the data acquisition unit, and creates a virtual model of the venue by using the digital twin mapping unit. The personalized safety early warning module analyzes audience behaviors and predicts potential risks. And the emergency evacuation simulation and optimization module improves the evacuation efficiency and safety. And the environmental factor analysis module evaluates the influence of the environment on the security performance. And the special event response strategy module simulates and optimizes emergency response. The system further comprises a regulation compliance analysis module, an intelligent inspection assistance module, a self-adaptive learning module and the like, operation compliance is ensured, and continuous optimization is performed according to real-time data. According to the system, comprehensive monitoring, early warning, analysis and optimization of the safety condition of the stadium are realized, and the safety management capability of the stadium is effectively improved.

The invention relates to the technical field of network security, in particular to a network security evaluation information processing method and system, and the method comprises the following steps: collecting configuration information and operation logs of a target computer system based on network security evaluation information, sorting data according to time information, and executing formatting and standardization processing, and generating an operation data processing result. According to the method, time sorting and formatting processing are carried out on data, data quality is optimized, security events are classified according to time information and severity, event frequency analysis is combined, threat identification accuracy is improved, damage risk levels of multiple security threat types are analyzed, and weights of security assessment indexes are adjusted, so that threat identification accuracy is improved. The response sensitivity and prediction capability of the evaluation model are enhanced, the risk of misjudgment is reduced, the adaptability and foresight of safety measures are improved, and it is ensured that the safety level evaluation accurately reflects the actual safety condition.

The invention relates to the technical field of mine environment control, and discloses an intelligent environment monitoring and control method in a mine laneway. The method comprises the steps that a real-time environment parameter set of a mine laneway is collected, the set contains gas concentration data, dust concentration data and temperature and humidity data, and real-time capture of laneway environment multi-dimensional parameters is achieved; then, based on the collected real-time environment parameter set, calculating an environment safety evaluation index so as to scientifically and objectively reflect the roadway environment safety condition; a dynamic control strategy is generated according to the environmental safety evaluation indexes, and the strategy comprises ventilation equipment regulation and control parameters and early warning level parameters and can be flexibly adjusted according to environmental changes; and finally, the ventilation equipment regulation and control parameters are sent to a mine ventilation system, and roadway environment regulation and control are executed. According to the method, environmental parameters can be comprehensively monitored, safety risks can be accurately evaluated, ventilation equipment can be flexibly regulated and controlled, the early warning function can be perfected, energy waste can be reduced, labor intensity can be reduced, and underground operation safety and mining efficiency can be guaranteed.

The invention discloses a hydraulic engineering data intelligent monitoring method and system based on digital twinning, and the method comprises the steps: comprehensively considering the actual physical structure, operation parameters and surrounding environment information of a hydraulic engineering when a hydraulic engineering digital twinning model is constructed, and breaking through the limitation that a conventional monitoring means only pays attention to a single parameter or a few parameters; model association data is utilized and visualized display is carried out, management personnel can visually check states and parameter changes of all parts, the monitoring efficiency and comprehensiveness are improved, and the limitation that a traditional monitoring means lacks effective analysis and mining is solved. A risk assessment formula is adopted to convert data into risk indexes, so that managers can visually know the safety condition, when a risk assessment value exceeds a threshold value, the risk development trend and consequences are simulated and analyzed in combination with a model, problems and risks are found in advance, early warning is triggered, and related personnel can formulate response measures such as flood discharge flow adjustment and structure reinforcement according to simulation results. Disaster loss is reduced, and the safety and reliability of hydraulic engineering are improved.

The invention relates to the technical field of security detection and situation analysis, discloses a security detection and situation analysis system for a software supply chain, and solves the problems that vulnerabilities in the software supply chain may be maliciously utilized, a security detection system of the system has certain limitation in the aspect of vulnerability detection, early warning and alarm mechanisms are not timely and accurate enough, and the security of the software supply chain is influenced. In order to solve the problems in the prior art that high requirements for software supply chain security are difficult to meet, an early warning and alarm module monitors output results of modules for vulnerability detection, malicious software detection, supply chain relation analysis and the like in real time, when security risks or abnormal conditions are detected, graded evaluation is performed according to preset rules and severity, and the security risk or abnormal conditions are detected. The early-warning and alarming module can quickly send out early-warning and alarming information, so that related personnel can timely know the early-warning and alarming module, the information can be timely and accurately transmitted by establishing interfaces of various notification channels, and an automatic analysis algorithm is adopted to quickly judge the safety condition and determine the early-warning level.

The invention discloses an active management and control method and device for high-risk operation, electronic equipment and a storage medium. The method comprises the following steps: enabling operators related to high-risk operation to carry out operation according to related requirements of construction safeguard measures and risk processing plans in a mode of automatically acquiring videos or images and an active management mode, and carrying out biological feature recognition and identity recognition on the operators so as to ensure that the operators can carry out risk processing according to the related requirements of the construction safeguard measures and the risk processing plans; the system can more intuitively assist enterprise safety management personnel to comprehensively master the safety condition of a working site, form an effective management means, supervise and urge management and execution personnel at all levels to consciously practice three-notice management, namely the management principle of site, notice and reality, and actively go deep into the site, so that the safety management efficiency is improved to the greatest extent, and the safety management efficiency is improved. The safety of a high-risk operation site and the periphery is strictly ensured, the effectiveness of safety management is improved, and a better operation environment is provided for operators.

Methods and / or systems are described for identifying hazards. The method may include (1) receiving user visual data and hazard data, the hazard data including a hazardous condition associated with one or more of: (i) a hazard or (ii) an environmental condition associated with the hazard; (2) training a machine learning algorithm to classify at least part of the user visual data; (3) classifying at least part of the user visual data to generate a classification of a detected hazardous condition in the at least part of the user visual data; (4) generating a hazard notification corresponding to the classification of the detected hazardous condition in the at least part of the user visual data; and / or (5) causing a user device to provide the hazard notification based upon the classification of the detected hazardous condition in the at least part of the user visual data.

The invention relates to the technical field of safety protection, and provides a high-place operation safety belt failure early warning device and method.The real-time state of a safety rope can be evaluated through cooperation of a monitoring main machine and a monitoring auxiliary machine, and the real-time state of the safety rope is divided into a normal state, a low-hanging high-use state, a virtual-hanging state and a straightening state; the real-time state of the safety rope is sent to the handheld monitoring terminal and the supervision terminal through the monitoring host by using the Lora communication technology, so that safety supervision personnel can quickly master the safety condition of a construction site, timely take necessary safety measures and timely find potential safety hazards; by monitoring and feeding back the real-time state of the safety rope in real time, the occurrence rate of falling accidents in high-altitude operation is remarkably reduced, and the safety of constructors is improved; the handheld monitoring terminal has the function of monitoring the plurality of monitoring hosts at the same time, so that the safety supervision efficiency is enhanced, and the safety personnel can better manage the safety states of the plurality of construction personnel.

The invention relates to the field of aquatic product safety monitoring and early warning, in particular to an aquatic product safety monitoring and early warning system and method, which comprises a data acquisition module, a data transportation module, a data analysis module, a data early warning processing module and an information management module, through real-time acquisition of related data in links of aquatic product production, processing, storage, transportation and the like, water quality parameters, temperature and humidity are analyzed, the safety condition of aquatic products and a potential risk early warning processing module are evaluated, and when a data analysis result shows that potential safety hazards exist or exceed a set standard, early warning signals of different levels are sent out. Therefore, equipment and related personnel can take measures in time. And the information management module effectively manages and stores various data, thereby facilitating query and tracing. And related reports are generated to provide a basis for decision making.

The invention discloses a coal mine underground safety detection method and system based on face image recognition, and relates to the technical field of coal mine safety detection. The method comprises the following specific implementation steps: through a video target recognition technology and a self-adaptive face recognition method, recognizing the identity of a miner and the wearing condition of safety equipment in each working area, and obtaining a miner number and a first danger index; secondly, according to the motion trail matching and behavior analysis technology, analyzing the danger degree of various behaviors of the miner to obtain a second danger index; then, according to the environmental parameters, evaluating the danger level of the miner working environment, and calculating a third danger index; finally, in combination with the danger index of the miner and the danger degree of the working area, the working safety condition of the miner is comprehensively evaluated, the comprehensive danger index is obtained, danger grading is carried out, early warning information can be sent out in time, the safety risk of underground operation of the coal mine can be effectively reduced, the safety of operators is ensured, and safety accidents are reduced.

The invention relates to the technical field of energy storage power station safety monitoring, and discloses an energy storage power station safety assessment method and system, and the method comprises the steps: collecting historical operation data and regular sampling inspection sample data of an energy storage power station, and carrying out the data preprocessing and feature extraction; and respectively constructing a security evaluation model A based on a decision tree algorithm and a security prediction model B based on a long short-term memory (LSTM) network algorithm. A model A learns a safety mode and a fault mode in historical data, and a model B predicts a future safety state change trend. Sampling inspection data are input into the two models to obtain evaluation and prediction results, and a preliminary fusion evaluation result is obtained through comprehensive analysis of a fusion algorithm. And according to a set safety threshold, determining a power station safety level and a potential risk point. And finally generating a safety assessment report including the overall safety condition, the potential risk points and the suggested measures. According to the invention, the accuracy and timeliness of safety assessment of the energy storage power station are effectively improved.

The invention relates to the technical field of power distribution cabinet safety monitoring, in particular to a power distribution cabinet safety early warning method and device based on a progressive early warning mode, computer equipment and a storage medium. The operation cycle of the power distribution cabinet is divided into a starting stage, a normal operation stage and a shutdown stage, and sensors are deployed in each stage to collect specific parameters. Calculating initial risk indexes in the starting and stopping stages through a dynamic weighted summation algorithm, and calculating and fusing different load risk indexes in the normal operation stage by using nonlinear calculation and a risk matrix. And then calculating a progressive factor correction risk index, finally dividing into four risk levels of normal, attention, warning and emergency, and formulating an early warning strategy according to the levels. By collecting and analyzing various operation parameters of different operation stages of the power distribution cabinet, the risk index of each stage is accurately calculated, and the corresponding early warning strategy is formulated according to the risk level, so that comprehensive monitoring and effective early warning of the safety condition of the power distribution cabinet are realized, and the risk of power accidents is reduced.

An emergency door release device for a vehicle may include a first sensor to detect a collision and provide a collision indication. A door sensor may detect if a door remains closed after the collision and provide a door indication. A receiver may receive a secondary detonation trigger indication from another device. A processor may analyze the indications to determine if they meet time constraints. A detonator may cause detonation of an explosive to separate the door from the vehicle body if the constraints are met. The device may include additional sensors to detect unsafe conditions. A method and system for releasing a vehicle door using similar components and steps may also be provided.

A framework includes a system and associated computer-implemented methods for detecting behavioral changes in a dynamical system that can lead to unsafe conditions before an output of the dynamical system violates a safety threshold, especially for dynamical systems with unmodeled inputs and unmodeled dynamics. In particular, the framework aims to detect “unknown-unknown” errors that may be present in a post-deployment model of the dynamical system that may not be anticipated or modellable by its designers, and are often not directly observable through input-output traces. This is achieved by evaluating conformance of post-deployment model coefficients of the post-deployment model with respect to a set of pre-deployment (ideal) model coefficients. The framework can estimate a future time step where the output of the dynamical system is expected to violate a safety violation based on the post-deployment model.

The invention relates to the technical field of building safety detection, and discloses a building element comprehensive information application method and system.The building element comprehensive information application method comprises the steps that building information collection is conducted on a target building to construct a building information model, building element data collection is conducted according to preset building elements to form an element building model; real-time monitoring is carried out through a sensor group and AR equipment to obtain real-time monitoring data, the real-time monitoring data are substituted into an element building model to analyze element actual characteristics and safety characteristics of a building, and the safety condition of the building is evaluated by carrying out fire detection and positioning, fire fighting access occupation and blockage detection, emergency exit recognition, emergency evacuation sign recognition and the like on the building. By collecting the building information and the building element data and combining the real-time monitoring information, the real-time condition of each part of the building is accurately described so as to detect potential safety hazards, the building disaster response capability and the management efficiency are improved, and the problem that in the prior art, potential safety hazards are likely to be missed due to manual building safety inspection is solved.

The invention particularly relates to a slope safety monitoring and acquisition system based on big data of the Internet of Things, and the system comprises the following parts: a multi-modal sensing module which is used for arranging sensors on a slope to collect all parameter data of the slope; the edge calculation module is used for analyzing various parameter data of the side slope to obtain a side slope evaluation value, and carrying out risk grading on the safety of the side slope according to the side slope evaluation value; and a cloud service module. According to the invention, the edge calculation module carries out deep analysis on data collected by the multi-modal sensing module, obtains a slope evaluation value through a series of scientific calculation methods, and carries out risk grading; abnormal conditions of various parameters can be comprehensively considered, and the safety condition of the slope can be accurately evaluated; the early warning module adopts early warning measures with different intensities and modes according to different risk levels, daily monitoring reminding of first-level risks is changed into emergency linkage emergency response of third-level risks, and it is ensured that related personnel can be timely notified under different risk levels and effective response measures are adopted.

The invention discloses an energy storage system safety evaluation method and system. The method comprises the following steps: constructing an energy storage system safety risk evaluation index system according to a to-be-evaluated energy storage system, and calculating the weight of each index; obtaining a cloud feature value of each index according to the calculated weight value of each index, and calculating a comprehensive cloud feature value of each index according to the cloud feature value of each index; and generating a comprehensive evaluation cloud atlas and a secondary index evaluation cloud atlas based on the obtained comprehensive cloud feature values of the indexes, and calculating the membership degree of the comprehensive evaluation cloud to each safety evaluation grade based on the comprehensive evaluation cloud atlas, so that various factors influencing the safety of the energy storage system can be comprehensively considered, multi-dimensional evaluation is performed on the energy storage system, and the safety of the energy storage system is improved. The one-sidedness of single-factor evaluation is avoided, qualitative safety evaluation is converted into quantitative analysis, the evaluation result is more accurate and scientific, interference of human factors is reduced, the evaluation result is displayed in a visual graphic mode, related personnel can understand and analyze the safety condition of the energy storage system conveniently, and the safety of the energy storage system is improved. And even non-professionals can roughly know the security risk level of the system through the cloud atlas.

The invention discloses a safety production virtual training method and system for a mine underground scene, and the method comprises the steps: creating a model library, and storing a preset part model through the model library; based on the mine underground mine hole excavation design drawing, the spatial orientation of each component model is obtained, and a virtual practical training scene of the mine underground is generated; based on a received practical training instruction, a virtual practical training scene is obtained from the scene library according to the practical training instruction, and the virtual practical training scene is displayed on the interaction module; adjusting and transforming the virtual practical training scene based on an operation feedback signal of a practical training miner, labeling the component model with a high danger coefficient in the virtual practical training scene, judging the safety condition of each component model under the mine, calculating the average labeling number in the virtual practical training scene, and comprehensively judging the safety coefficient of the mine. The system has the advantages that the mine underground environment is simulated through the virtual reality technology, miners are helped to carry out safety operation training under the risk-free condition, and the safety consciousness and the emergency response capacity of the miners are improved.

The invention discloses a construction site safety management system based on an intelligent construction site, which relates to the technical field of construction site safety management and comprises a cloud server, a data acquisition module, a data transmission module, a data processing module, a safety management module and a user interaction module. Through the arrangement of the data acquisition module, the system can acquire personnel information, environment information and equipment information of the construction site, data analysis requirements of subsequent safety monitoring and management of the construction site are guaranteed, and the system can comprehensively analyze the safety condition of the construction site. Through the arrangement of the safety management module, the system can establish a complete personnel management and equipment management system, ensures that workers have corresponding skills and reasonably use equipment, and improves the emergency response capability at the same time, thereby preventing and avoiding the occurrence of safety accidents to a certain extent, and guaranteeing the safety of a construction site.

The invention relates to the technical field of bridge safety operation, in particular to a bridge line anomaly detection and alarm method and system, and the method comprises the following steps: obtaining bridge line monitoring information through a line anomaly monitoring system; setting a line abnormity positioning judgment mechanism and a back-end processing model, and obtaining a line positioning judgment result based on the line abnormity positioning judgment mechanism, the back-end processing model and the bridge line monitoring information; analyzing the bridge line monitoring information and the line positioning judgment result by using a back-end processing model to obtain a line anomaly detection result, a response level condition and a bridge structure condition; and realizing detection and warning of a bridge line interruption event by combining bridge line monitoring information, a line positioning judgment result, a line anomaly detection result, a response level condition and a bridge structure condition. The bridge safety condition is monitored for a long time, abnormal events are judged, a warning signal is sent out according to the judgment result, and casualties and losses caused by disasters are reduced.

The invention discloses a fire safety early warning method and system based on wireless networking, and relates to the technical field of fire safety early warning. According to the fire safety early warning method based on the wireless networking, electric power and environment monitoring data of a plurality of areas in the wireless networking of a shopping mall are acquired in real time, and an electric fire danger induction index and a fire danger environment disturbance index are analyzed; meanwhile, shopping mall monitoring image angle sequence data of each area is obtained, a visual potential safety hazard index is analyzed based on a pre-trained fire safety identification model, the safety condition of each area is comprehensively evaluated according to an electrical fire danger induction index and a fire danger environment disturbance index, and finally a comprehensive safety perception index of each area is generated. According to the invention, fire safety early warning is carried out on the corresponding area through the comprehensive safety perception index of each area, so that fire hazards in multi-area and complex layout environments such as shopping malls and the like are identified and positioned in real time, the accuracy of fire safety early warning is effectively improved, and the overall fire safety level is improved.

The invention relates to the field of slope safety assessment, in particular to a highway slope construction safety assessment method and system. The highway slope construction safety evaluation system comprises a slope region division module, a data acquisition module, a correlation analysis module, an anomaly judgment module, a safety evaluation module and an anomaly prediction module. According to the method, the normal limit value and the weight of the monitoring index are dynamically adjusted by combining real-time monitoring data, construction operation types and environmental factors, so that the assessment is more flexible and accurate; in the construction process, the safety condition of the side slope possibly fluctuates greatly under the influence of construction activities and environmental changes; by automatically adjusting the weight and the limit value of the monitoring index according to the actual construction state, false alarm and missing alarm caused by construction activities can be reduced, so that the accuracy and the timeliness of a safety assessment result are improved.

The invention discloses a system for monitoring the safety of a construction site through a dome camera, and the system comprises a dome camera module which is disposed in a key region of the construction site, and is used for collecting the video image data of the site; the visual identification module is used for identifying key objects, figures and abnormal events on the construction site; the AI large model analysis module is used for performing efficient data processing and analysis by utilizing a pre-trained large-scale AI language vision model, and identifying and predicting potential safety hazards; the natural language generation module is used for converting a visual recognition result into understandable voice information and feeding back the voice information to safety supervision personnel in real time, so that timely response is facilitated; and the intelligent alarm module is used for automatically triggering an alarm mechanism through real-time analysis of the safety condition of the construction site when dangerous behaviors or abnormal conditions are found. According to the system for monitoring the safety of the construction site through the dome camera, real-time safety monitoring, risk prediction, anomaly detection and intelligent alarm of the construction site are achieved.

The invention discloses a group safety prevention and control management system and method and a computer program, and the system comprises a data collection module which is used for collecting the related data of a wharf, including operation information and monitoring data; the data management module is used for managing the data collected by the data collection module; the early warning analysis module is used for performing mining and analysis by comprehensively utilizing a preset rule engine and the trained multi-task neural network model to generate early warning information; and the visualization module is used for displaying the data managed by the data management module and the early warning information generated by the early warning analysis module to a user by utilizing a visualization technology. According to the technical scheme provided by the invention, key data, early warning information and the like of each wharf are displayed to group management personnel in a visual and understandable form, so that the efficiency and the effect of safety management in the group are improved; the safety condition in the group can be monitored in real time, the potential safety risk can be pre-warned and analyzed, and a response can be quickly made when a safety accident occurs.

The invention belongs to the technical field of safety protection, and provides an intelligent safety risk prediction, early warning, prevention and control system, which comprises a data acquisition module for monitoring the safety condition of a key area in real time through video monitoring and sensor data; the data processing module preprocesses the collected data and performs feature extraction; the risk prediction module constructs a safety risk prediction model, and identifies and predicts potential safety risk factors by analyzing historical data and real-time data; the early warning module automatically gives out early warning by setting an early warning rule when a prediction result exceeds a safety threshold value; the emergency response module generates corresponding early warning information and prevention and control strategies according to different types of risk early warning; the adjustment and optimization module continuously monitors the safety risk condition and adjusts the early warning level and the prevention and control strategy according to the real-time data; according to the invention, through efficient risk identification and prediction, potential safety hazards are found in advance, the possibility of accident occurrence is reduced, and the efficiency and accuracy of safety prevention and control are improved.

An apparatus, including a controller, camera, display, speaker, global positioning system, and sensor or detector which senses or detects a dangerous, hazardous, or unsafe, condition at or in a vicinity of the apparatus. The sensor or detector senses or detects the dangerous, hazardous, or unsafe, condition, and the apparatus provides, via the speaker, an audible alarm, siren blare, or verbal message, containing information regarding the dangerous, hazardous, or unsafe, condition. The apparatus or the controller generates an alert message containing information regarding the dangerous, hazardous, or unsafe, condition. The apparatus transmits the alert message to a central processing computer, to a communication device of a parent, relative, or friend, or other authorized individual, or to a police or law enforcement communication device.