A UNIFIED COMMAND AND SECURITY SYSTEM THAT PROCESSES WEARABLE DEVICE, ENVIRONMENTAL SENSOR NETWORK, AND COMPUTER VISION DATA USING MULTI-MODEL ARTIFICIAL INTELLIGENCE ANALYSIS.

Abstract

The invention relates to a unified command and safety system used in high-risk work environments. The system includes wearable smart devices that collect biometric data from employees, an Internet of Things-based environmental sensor network that collects measurement data of the work environment, a computer vision camera system that collects image data from the work area, and a central command and control structure that receives this data along with equipment status and operational data. The data is processed in five separate artificial intelligence models structured for health analysis, environmental risk analysis, image processing, predictive maintenance, and operational decision support. The analysis outputs from the different models are correlated with employee, work area, equipment, and time information to create a safety status.Using the established safety status, the digital twin of the work environment is updated, a predictive risk map of work areas is created, and shift data is generated that correlates the health status of employees with the risk levels of the work areas. Emergency data determined by the emergency management structure is transmitted to the mobile application and notification system, the autonomous unmanned aerial vehicle system, and external emergency units.

Description

1 TARIFF WEARABLE DEVICE, ENVIRONMENTAL SENSOR NETWORK AND COMPUTER VISION A combined system that processes data using multi-model artificial intelligence analysis. COMMAND AND SECURITY SYSTEM TECHNICAL FIELD The invention concerns occupational health and safety in high-risk work environments. It relates to unified command and security systems for monitoring. Specifically; Biometric data from wearable devices, obtained from an environmental sensor network measurement data, image data from camera systems and study 10 operational data relating to the environment are combined in a common data processing infrastructure It was analyzed with multiple artificial intelligence models; the analysis data was used to create digital twins and make predictions. risk mapping, shift optimization and emergency management units based on It relates to a system through which the information is transferred and the way that system works. STATE OF THE ART In known practices for monitoring occupational health and safety; work Fixed camera systems monitoring the area provide information about the employee's physiological condition. wearable health tracking devices that generate data, environmental devices that measure ambient conditions sensors, internet of things-based monitoring systems, and image data are used in artificial intelligence. Analysis solutions that operate using intelligence models are used. These applications through which the health status of employees, environmental conditions in the working environment, regarding the use of personal protective equipment and risky situations in the workplace Data can be obtained. However, in these applications, biometric data and environmental measurements 25 Data, image data, equipment data, and operational data are mostly different. Data is stored on devices or independent data processing infrastructures. This discrete structure between the sources allows different types of data to coexist. inability to evaluate, multiple and inconsistent reports regarding the same event This can lead to the generation of false alarms and an increase in false alarm rates. Additionally, there are 30 known cases. A significant portion of the systems are for detecting an event that has occurred or for reporting an event. It operates on the principle of generating an alarm afterwards; regarding the employee's health. changes in the situation, environmental hazards, equipment condition and operational conditions 2 It does not offer a preventive security approach based on a combined assessment. The invention notification also covers existing applications in fixed cameras, wearable devices, and peripherals. sensor, internet of things and artificial intelligence-powered image analysis solutions this occurs; however, these solutions mostly operate independently of each other. It is stated. 5 Patent number WO 2017 / 223438 A1 included in the known art. in the document, one or more of the items on a personal protective equipment obtaining data from the sensor indicating equipment usage and organizing this data into a single system. The application of the safety learning model is explained. Safety learning The model is based on previously obtained usage data, personal protective equipment 10 to determine the probability of a safety incident occurring related to the equipment and An action is performed according to the determined probability. Thus, the aforementioned The document is based on the analysis of data from sensor-equipped personal protective equipment. It presents a predictive security approach. However, the document... The explanation is essentially based on data regarding the use of personal protective equipment and these 15 It focuses on determining the probability of a security incident from the data. Another patent included in the known art is KR 2024 / 0079236 A. The document describes imaging that obtains image data related to a work area. the unit has at least one modular system that acquires sensor data according to the work area and type of work. sensor, sensor control unit, image data and sensor data are processed by an artificial intelligence 20 the security risk estimation unit that applies the model, the unit that determines the risk status, and In the event of a detected risk, an alarm is triggered via terminal, speaker, or lighting. An alarm unit that provides information is described in this document. This document includes the display and sensor data. By processing them together, a security risk value is created. With this... together document; employee biometric data, environmental measurement data, equipment 25 Situational data and operational data are analyzed under different analytical structures. processing, numerical representation of the obtained analysis results of the study area combining these results on a digital twin or shifting and emergency an integrated framework for evaluating the situation together with situation management It does not explain. 30 The known technique also includes first aid supplies or medical equipment for emergencies. human-reliant processes for delivering equipment to the scene It can be used and this can prolong the intervention time. Wearable 3 Due to the limited processing capacity of the devices, data is processed on the device. It can become difficult to transfer biometric or operational data to different systems. However, transferring data requires additional technical expertise in terms of data security and communication load. This can create needs. In conclusion, sensor-equipped personal protective equipment in the known technology, wearable 5 devices, camera systems, environmental sensors, and AI-based risk analysis The solutions are known individually. However, the employee's biometric status, environmental conditions, observed field conditions, equipment operating status, and operational data are evaluated together within a common data processing infrastructure; this Simultaneously performing different technical analyses on the data and generating 10 outputs risk mapping, digital twin, shift management and emergency response units It is open to improvement in the known technique in terms of its integrated use. There is an area. PROBLEM THAT THE INVENTION AIMS TO SOLVE 15 The main technical problem that the invention aims to solve is high-risk work. biometric, environmental, and other data obtained from various physical data sources in their environments. visual, equipment and operational data are correlated over time to create a common the evaluation within a data processing structure and the analysis outputs that corroborate each other 20 that ensures the transfer to security management units without delay It is the creation of an integrated technical architecture. Within the scope of this fundamental problem, furthermore;  Different data from the wearable device, environmental sensor network and camera system Data produced in various formats and at different sampling intervals have a common 25 unification under employment status,  the employee's physiological condition and the environmental conditions in the work environment, the displayed field movements, equipment operating statuses and Operational conditions are not independent of each other, but rather mutually reinforcing. processing in a way that will provide 30  Instantaneous or erroneous measurements occurring in a single data source directly affect security. Increasing the reliability of the analysis in a way that will prevent the initiation of intervention, 4  Digital representation and predictive analysis of different analysis results for the study area. Correlation with risk map and shift planning data,  Changes in risk level should only be presented to the user as information. Instead, alarm, mobile notification, emergency coordination and autonomous aerial vehicles. 5 that can direct the physical intervention procedures carried out through converting into technical outputs,  High processing load while maintaining the limited processing capacity of wearable devices the technical aspects of conducting analyses in a central data processing infrastructure The aim is to solve their problems. Thus, the technical problem of the invention is that only one risk class can be addressed software-wise (10). not from determining; but from the physical study of heterogeneous sensor and image data. Relating the results of multiple analyses to a common field situation with its environment transformation and deployment of security and intervention units according to the field situation This is due to their coordinated operation. A BRIEF DESCRIPTION OF THE INVENTION The invention addresses worker health and environmental concerns in high-risk work environments. A common technical framework for data relating to conditions, equipment status, and field activities. It is a unified command and security system for processing within the infrastructure. The system described in the invention consists of a central command and control station and 20 employees. wearable smart devices carried by the user, objects found in the work environment an internet-based environmental sensor network that collects image data from the work area. computer vision camera system and data transmission between the components in question It includes the communication infrastructure that provides this. Biometric data from the wearable smart device is collected from a network of environmental sensors. environmental measurement data obtained, image from computer vision camera system data, equipment and operational data to the central command and control station. The transferred data is used for health analysis, environmental risk analysis, image processing, separate artificial intelligence models for predictive maintenance and operational decision support It is processed within an artificial intelligence analysis and decision support structure that works together. 30 The AI ​​model for health analysis uses data from a wearable smart device. biometric data; artificial intelligence model for environmental risk analysis, environmental Environmental measurement data received from the sensor network; artificial intelligence for image processing. The model uses image data from the camera system for predictive maintenance. artificial intelligence model, equipment status data and operational decision support The artificial intelligence model for this purpose analyzes operational data related to the work environment. It is processing. The analysis outputs produced by these artificial intelligence models, 5 in determining the safety situation regarding the collaborative work environment It is used. The system can also use the analyzed data to determine the study area and the work a digital twin structure representing the current status of equipment and personnel in the field It creates a predictive risk map. The predictive risk map... 10 areas of study and risk levels associated with the analysis results It is shown that the data obtained is used for AI-powered shift optimization and emergency response. It is being transferred to the situation management processes. Biometric data of employees in AI-powered shift optimization. data includes environmental risk levels related to work areas and operational data. By evaluating the situation, the employees' work areas and shift schedules are determined. 15 Thus, the health status of employees and the risk levels of their workplaces are aligned. It is linked within the technical data structure. In emergency management, artificial intelligence analysis and decision support structure The identified risk or emergency data is sent to the central command and control station. transmitted; audible or visual alarm via central command and control station, 20 mobile application notification and data transfer to relevant response units. This is being carried out. Depending on the nature of the emergency, an autonomous unmanned aerial vehicle is used. Directed camera footage acquisition, first aid supplies or medical equipment. Equipment transportation is provided. Additionally, the hospital, Disaster and Emergency Management... Data communication is established with the Presidency and external emergency units such as the fire department. 25 The invention enables high-throughput data integration and artificial intelligence analysis. thanks to the fact that operations are carried out from the central command and control station The processing load on wearable smart devices is reduced. Different physical data Data from various sources are combined by artificial intelligence models. by evaluation, 30 errors or omissions originating from a single data source The impact of measurements on determining the safety status is limited, and The reliability of safety outputs is being increased. In this way, biometric, environmental, visual, equipment and operational data processing on a common technical infrastructure; digital twin and prediction of the resulting analysis outputs. 6 risk mapping based on shift optimization and its correlation with emergency management. and affiliated notification and response units according to the determined security situation This structure is ensured by its operation. The system drawing in the invention declaration also shows this structure; central command and control station, wearable smart device, environmental sensor network, Computer vision camera system, artificial intelligence analysis and decision support structure, Digital 5 twin, risk map, shift optimization, emergency management, autonomous aerial vehicle and This is demonstrated by the data links between external intervention units. LIST OF FIGURES Figure 1 shows the central command and control unit of the unified command and security system, 10 wearable smart device, internet of things-based environmental sensor network, computerized visual camera system, artificial intelligence analysis and decision support module, digital twin module, Predictive risk mapping module, AI-powered shift optimization. module, emergency management module, autonomous unmanned aerial vehicle system, mobile Data exchange between the application and notification system and external emergency units and 15 It is a schematic view showing communication links. BRIEF DESCRIPTION OF THE FIGURE Figure 1 shows the general operational structure of the unified command and security system. This is shown. The system includes 20 wearable smart devices carried by employees. The biometric data obtained, the Internet of Things in the work environment Environmental measurement data and computer vision obtained from a network of environmental sensors based on the system. Image data obtained from the camera system is sent to the central command and control structure. is being transferred. Data transferred to the central command and control structure is analyzed by artificial intelligence and 25 It is processed within the decision support structure. Artificial intelligence analysis and decision support structure. The analysis outputs generated by [the organization / institution] represent the current state of the working environment. the creation or updating of a digital twin, relating to work areas the creation of a predictive risk map and the health status of employees Creating a shift schedule taking into account the risk levels of the workplaces 30 It is used in transactions. Digital twin, predictive risk mapping, and AI-powered shift work. Data regarding optimization is transmitted through the central command and control structure. 7 They are interconnected and fall within the scope of emergency management. is being evaluated. In accordance with the security situation determined within the scope of emergency management Guidance data is being transmitted to the autonomous unmanned aerial vehicle, via mobile application and User notifications are generated through the notification system and the hospital, emergency health 5 services, external response units such as fire departments or disaster and emergency units Data communication is being established. DETAILED DESCRIPTION OF THE INVENTION The invention relates to the physiological condition of workers in high-risk work environments, 10 Environmental conditions in the work environment, images taken from the work area, work data on the condition of equipment and operations carried out are compiled using a common technique. It is a unified command and security system designed for operation within the infrastructure. Centralized command and control structure, at least one wearable smart device, Internet of Things. based environmental sensor network, computer vision camera system, artificial intelligence analysis and 15 decision support structure, digital twin structure, predictive risk mapping structure, artificial intelligence intelligence-supported shift optimization structure and emergency management structure It includes. The system also allows employees or authorized personnel to be alerted to specified security situations. Mobile application and notification system for delivering emergency information to users. autonomous unmanned aerial vehicle system that can be directed to the region and external emergency It may include an integration structure that establishes data communication with its units. Central command and control structure; data transmission between system components. a system that manages data, receives data from different data sources, and artificially manipulates that data. transferring the data to an intelligence analysis and decision support structure and based on the generated analysis outputs, 25 at least one processor and data coordinator that coordinates the work of the affiliated security units It includes a storage unit. The central command and control structure is based on a single physical computing device. as can be accomplished, multiple computing units communicating with each other. It can also be performed on it. High-processing-load image processing, 30 Multiple data analysis, digital twin updating, and risk mapping operations are managed by the central command. and the processing load on wearable smart devices is carried out in the control structure. It is being restricted. 8 A wearable smart device is a device carried by an employee or attached to an employee's clothing or... It is an electronic device found on personal protective equipment. Wearable smart devices. The device obtains at least one biometric data point relating to the employee's physiological condition. or contains multiple sensors. Biometric data includes the employee's heart rate, body temperature, movement... its condition or can be measured by sensors located on the wearable smart device It may include at least one of the data relating to other physiological parameters. Wearable Biometric data obtained by the smart device, wireless communication connection It is transferred to the central command and control structure via this channel. In an application, a wearable smart device can provide employee ID or a link to an employee. It generates data along with the associated device ID. Thus, the following is obtained: Biometric data is processed by associating it with the employee to whom the data belongs. The Internet of Things-based environmental sensor network monitors different aspects of the working environment. It includes one or more environmental sensors placed at various points. Environmental sensors; temperature, humidity, gas density, carbon dioxide level or operation 15 at least one of the other environmental parameters affecting the safety status of the environment It measures. Environmental measurement data generated by the environmental sensor network, the sensor's central location, along with location or area information that defines the work area in which it is located. The environmental measurement data is transferred to the command and control structure. Thus, environmental measurement data is 20 not only as a numerical measurement, but also in relation to the field of study in which the measurement was obtained. It is processed as correlated data. A computer vision camera system obtains image data from the work area. It includes at least one camera. The camera system can be a fixed camera, a movable camera, or... 25 from multiple cameras viewing different parts of the work area It can occur. Image data obtained from the computer vision camera system; employees their positions in the work area, employee movements, work equipment visible situations or safety-related events occurring in the work area It is used in identifying changes. 30 The system also includes equipment status data obtained from work equipment. and operational data relating to workflow are centralized to the command and control structure. 9 Equipment status data is transmitted, indicating the operating status of the work equipment. or data relating to the measurement data produced by the equipment during operation Operational data may include the type of work performed, work area, and shift. information from data relating to employee assignments or the current status of workflows It can include at least one of them. 5 Biometric data from the wearable smart device is transmitted through an environmental sensor network. environmental measurement data obtained, image from computer vision camera system Data, equipment status data, and operational data are centralized by command and control. This data is transferred from its structure to an artificial intelligence analysis and decision support structure. Artificial intelligence analysis and decision support structure; health analysis, environmental risk analysis, 10 diverse solutions for image processing, predictive maintenance, and operational decision support It includes at least five different artificial intelligence models. These artificial intelligence models share the same centralized command and control structure. It can be run on different computing systems that communicate data with each other. They can also be run on other units. The outputs of artificial intelligence models are common 15 together in establishing the safety situation regarding the working environment is being evaluated. The artificial intelligence model structured for health analysis comes from a wearable smart device. It processes the biometric data collected. The health analysis model, with the employee... to identify changes occurring in associated biometric data and the word 20 The subject is to create a health analysis output regarding changes. Health analysis output, changes in employee's health status, measured biometrics the relationship of the parameters with the defined working conditions or from the employee's perspective a numerical or classified information about a health condition that needs to be evaluated It may contain data. 25 The artificial intelligence model structured for environmental risk analysis uses environmental sensors. It processes environmental measurement data received from the network. Environmental risk analysis model, It relates the measurement values ​​to the study area where the measurement was obtained and the study It generates environmental risk analysis output related to the area. The environmental risk analysis output is the environmental condition determined in a study area, 30 The risk level is determined by evaluating environmental measurement values ​​together. or it may include data representing changes in environmental conditions. The artificial intelligence model configured for image processing is used in computer vision. It processes image data received from the camera system. The image processing model, working within image data, related to workspace, equipment or security. It identifies the conditions and generates image analysis output. Image analysis output; employee's location in the workspace, employee 5 movement, the visible operating status of the equipment or determined in the work area It may contain data about a security-related incident. The artificial intelligence model structured for predictive maintenance, study It processes equipment status data obtained from its equipment. Predictive The maintenance model identifies changes in equipment status data and monitors the equipment's condition. It generates predictive maintenance output regarding the operating status. Predictive maintenance output includes changes in equipment condition and information related to the equipment. in assessing maintenance requirements or safety risks associated with equipment It may contain usable data. The artificial intelligence model structured for operational decision support, study 15 area, job type, employee assignment, shift information and workflow status It processes operational data. The operational decision support model processes operational data. by correlating data with analysis outputs obtained from other artificial intelligence models It generates operational decision support output. Health analysis, environmental risk analysis, image processing, predictive maintenance and 20 Outputs generated by operational decision support models, artificial intelligence It is brought together within an analysis and decision support structure. Analysis generated by different artificial intelligence models in an application. Outputs include employee ID, device ID, workspace, equipment ID, and time information. It is linked through. Thus, data obtained from different physical data sources 25 whether the data collected belonged to the same employee, work area, equipment or time period It has been determined that it is not the case. For example, changes in biometric data obtained from a wearable smart device. an incoming change, the environment obtained from the environmental sensor network in the same time interval 30 along with measurement data and image data obtained from the camera system. is being evaluated. 11 In this way, a momentary or erroneous measurement occurring in a single data source can be avoided. Instead of directly initiating emergency action, it uses data obtained from different data sources. The analysis determines whether the results support each other. The artificial intelligence analysis and decision support structure processes different analysis outputs. A safety situation in terms of employee, work area, equipment or operation 5 This constitutes the safety status; normal operating status, and the status that needs to be monitored. the situation is categorized into different levels, such as increased risk or emergency. can be created. Here, the security status is merely abstract information shown to the user. not in the update of the digital twin structure, the predictive risk map 10 in establishing, determining the shift schedule and emergency management It is a technical control data used in the operation of the structure. The digital twin structure allows the work environment, workspaces, employees, and It includes digital representations of work equipment. The digital twin structure is central. 15 from current data and artificial intelligence models transferred to the command and control structure It is updated using the analysis results obtained. In an application, the locations of workspaces within a digital twin structure are related to the relevant employees in the work area, condition of work equipment, environmental factors Measurement values ​​and defined safety levels are kept together. Wearable New data from smart devices, environmental sensor networks, or camera systems 20 If data is collected, the digital data of the employee, workspace, or equipment associated with the collected data. The representation is being updated. This reflects current changes in the physical working environment. It is being transferred to a digital twin structure. Predictive risk mapping structure, artificial intelligence analysis and decision support. Security data obtained from its structure and spatial data found in its digital twin structure 25 They work together. The predictive risk mapping structure takes into account the different working environments. determining risk levels for the areas and implementing the determined risk levels in the relevant studies. It creates a predictive risk map by associating it with related fields. A risk map distinguishes the risk levels of different work areas. It can be created as a numerical or visual data structure. Risk levels; 30 biometric analysis output, environmental risk analysis output, image analysis output, equipment 12 at least two of the situational output and operational decision support output together This can be determined through evaluation. In an application, the risk map is updated at specific time intervals. In another application, it can be derived from sensor, image, equipment, or operational data. Upon receiving new data, the risk level of the relevant study area is reset to 5. is being calculated. AI-powered shift optimization structure; employee health analysis. their outputs, risk levels for their work areas, and operational data together. It is in operation. The shift optimization structure takes into account the health status of employees and working conditions. current risk levels of the areas and operational plans regarding the work to be carried out. by establishing a relationship between the requirements, employees' work areas or It generates shift data regarding the assignment of personnel to shifts. In an application, a health analysis output shows that an employee meets the specified condition. being assigned to a high-risk work area or working It is associated with a work environment that has a lower risk level. 15 In another application, depending on the change in the risk level of the work area Current shift data is being updated and the employee in the relevant work area... Assignments are being reorganized. Shift data generated by the shift optimization structure is centralized. It is transferred to the command and control structure and presented to the authorized user. 20 Shift data also analyzes employee-location relationships within the digital twin structure. It can be used in updating. The emergency management structure includes artificial intelligence analysis and decision support systems, from predictive risk mapping structure, digital twin structure or shift It receives data from the optimization structure. The emergency management structure, 25 the risk level associated with the defined security situation, the work in which the risk occurs emergency regarding the area, employees or equipment associated with the risk, and the type of intervention required. It generates status data. Emergency data is transmitted via a central command and control structure to mobile devices. application and notification system, autonomous unmanned aerial vehicle system or external 30 It is being integrated into a structure with emergency response units. 13 The mobile application and notification system are controlled from a centralized command and control structure. security or emergency data received is shared with employees, occupational safety officers, or It transfers the data to authorized users' mobile devices. The notification should include the type of risk identified, the work area where the risk occurs, and the risk itself. level, relevant employee or equipment and the intervention to be carried out 5 It can include at least one of the following pieces of information: Mobile application and notification system, audio, It can generate visual or vibration notifications. The autonomous unmanned aerial vehicle system receives its information from the emergency management structure. the work area where risk is determined based on location or orientation data. is being redirected. 10 via the camera on the autonomous unmanned aerial vehicle system Image data can be obtained from the incident area and the obtained image data is sent to the center. It can be transferred to the command and control structure. The autonomous unmanned aerial vehicle system can also provide first aid supplies or medical equipment. It may include a cargo compartment that carries the equipment. Emergency management structure 15 According to the guidance data generated by the autonomous unmanned aerial vehicle incident. The material or equipment in question is sent to the designated area for the work. It is delivered to the area. Image data from an autonomous unmanned aerial vehicle is used with computer vision. In addition to the image data received from the camera system, the image processing model is 20 can be transferred and the current status of the emergency situation can be determined. It is available for use. Integration structure with external emergency units, designated emergency situations data from hospitals, emergency medical services, fire departments, or disaster and emergency units, etc. It ensures that it is transferred to external intervention units. 25 Data transmitted to external emergency units includes: type of emergency, location of the incident, number of employees involved, health analysis results for employees, environmental risk information or It may include at least one piece of image data from the incident area. The system described in the invention operates in a prototype form, primarily using wearable smart devices. biometric data from devices, environmental measurement data from the environmental sensor network, 30 Image data from computer vision camera systems, work equipment. 14 Equipment status data and operational data from operational data sources. is being received. The collected data is transferred to the central command and control structure, and the data using information about the source, employee, work area, equipment and time are related. 5 Related data include health analysis, environmental risk analysis, image processing, Artificial intelligence structured for predictive maintenance and operational decision support. They are transferred to the models. Analysis outputs generated by artificial intelligence models together The safety status of the working environment is determined by evaluation. 10 The digital twin structure is being updated using the defined security status. A predictive risk map is being created for workplaces, and employees shift data based on health conditions and risk levels of work areas. It is determined. The determined security situation corresponds to the emergency level of 15. In this case, the emergency management structure is activated; notification regarding the relevant work area. autonomous unmanned aerial vehicles are being created, guided, and if deemed necessary. In this case, data is transferred to external emergency units. The invention includes health analysis, environmental risk analysis, image processing, and predictive maintenance. and models for operational decision support using data from the same work environment 20 By working together, they have improved employee health, environmental conditions, and equipment. The situation and operational processes are integrated under a single security status. Data obtained from different data sources includes employee, work area, Analysis outputs are physically represented thanks to their correlation with equipment and time information. It is associated with a specific entity or location within the work environment. 25 Thanks to this technical structure, the system only captures a camera recording of an event that has already occurred. risk assessment from its image or from data of a single wearable device It is not based on the creation of; biometric, environmental, visual, equipment and a multi-source security management architecture that processes operational data together It consists of 30 The different components of the system depend on the size of the work environment, the number of employees, This can be increased depending on the equipment used and the environmental parameters to be monitored. or can be reduced. In this context, multiple wearable smart devices can be integrated into the system. multiple environmental sensors, multiple cameras, and multiple autonomous drones The aircraft can be connected. 5 The scope of protection for the invention is limited to the example applications described above. not within the scope formed by the technical elements specified in the requests, but different This can be done in various application methods. 15 25

Claims

16 REQUESTS 1. A combined command and safety system used in high-risk work environments. It is a system and its feature is; 5 - carried by an employee, from at least one biometric sensor along with the biometric data it receives, employee ID or device ID. at least one wearable smart device transmitting, - obtaining environmental measurement data from the work environment Internet of Things 10 that transmits information about the field of study along with the information it was used in. a network of environmental sensors based on, - including at least one camera that collects image data from the work area computer vision camera system, - work equipment, equipment associated with equipment ID an equipment data interface that receives status data, 15 - job type, work area, shift information, employee assignment or job an operational data that includes at least one of the flow statuses operational data interface, - wearable smart device, environmental sensor network, computer vision camera the system, equipment data interface and operational data interface with data 20 containing at least one processor that establishes communication and at least one data storage unit central command and control structure, - a health analysis model that processes biometric data, environmental measurement an environmental risk analysis model that processes image data a functioning image processing model, a 25 that processes equipment status data a predictive maintenance model and an operational system that processes operational data five separate artificial intelligence models, including a decision support model artificial intelligence analysis and decision support structure, - the central command and control structure, the employee identity of the received data, device ID, workspace information, equipment ID, and time 30 associating the information with at least one of the data types corresponding to it, transferring the correlated data to the relevant artificial intelligence models and most analysis outputs obtained from at least two different artificial intelligence models 17 working together, work area, equipment or operation creating an associated security situation, - numerical data of work areas, employees and work equipment including their representations and based on current data regarding the security situation. an updated digital twin structure, 5 - security status and spatial data found in the digital twin structure estimating risk levels for work areas by correlating them risk mapping structure based on, - Employee-related analysis derived from a health analysis model. its output, the risk levels established for the work areas and 10 By processing operational data together, employee identity, work area and Generating shift data that includes matching between shift times AI-powered shift optimization structure, - security status, spatial data in the digital twin structure, risk By taking at least two of the levels and shift data, the associated risk is 15 defining the field of study and related to that field emergency management that generates correlated emergency data its structure - mobile application and notification system that receives emergency data, - work area or location information found in emergency data 20 autonomous unmanned aerial vehicle system receiving guidance data according to and transmits emergency data to external emergency units It is characterized by including an integration interface.

2. According to Claim 1, it is a combined command and security system, characterized by being wearable. The smart device must measure at least one of the following: heart rate, body temperature, and activity level, up to 25 minutes. It includes a biometric sensor that measures and transmits biometric data wirelessly. by transferring it to the central command and control structure via the connection It is characteristic.

3. According to Claim 1, it is a unified command and security system, characterized by its environmental features. the sensor network, located at different points in the working environment, and measuring temperature, 30 a single unit that measures at least one of the following: humidity, gas density, and carbon dioxide levels. It includes a large number of environmental sensors and relates each environmental measurement data to the relevant context. It is characterized by its ability to match the sensor's location with information from the working area. 18 4. According to Claim 1, it is a unified command and security system, characterized by its centralized nature. the command and control structure, with the same employee, work area or equipment Biometric data obtained in a related and shared time interval, environmental from measurement data, image data, equipment status data and operational data It must associate at least two of them within the same dataset and add 5 to that dataset. by processing the outputs of at least two different artificial intelligence models together. It is characteristic.

5. According to Claim 4, it is a unified command and security system, characterized by its artificial intelligence. the analysis and decision support structure, analysis obtained from a single data source its output is 10 obtained from a different data source within the same time interval. Comparison with the analysis output and the security status with the analysis in question. It is characterized by its ability to create information that aligns with the outcomes.

6. According to Claim 1, it is a unified command and security system, characterized by its digital twin. the locations of the working areas of the structure, located in the relevant working areas employee identities, condition of work equipment, environmental measurement 15 keeping data and security statuses within the same digital domain representation and upon the acquisition of new biometric, environmental, visual or equipment data the relevant employee, work area or equipment of the digital field representation in question It is characterized by updating its section.

7. According to Claim 1, it is a unified command and security system, characterized by; estimated 20 the risk mapping structure based on the risk level for each study area biometric analysis output, environmental risk analysis output, image analysis output, at least two of the following: predictive maintenance output and operational decision support output. to determine and assess the relevant risk level in the digital twin workspace. It is characterized by its matching with its location. 25 8. It is a unified command and security system according to Claim 1, and its characteristic feature is; - The AI-powered shift optimization structure, previously with an employee ID that matches a specified health condition in advance The same work area identity that matches a defined risk condition The fact that the shift assignment contains a non-matching assignment rule, 30 19 - The type of risk within the emergency management structure and emergency data. work area location, employee ID, equipment ID, and intervention. It must consist of at least two of the following types: - Image data from the incident area by an autonomous unmanned aerial vehicle system. 5 people carrying first aid supplies or medical equipment with a camera in the area it includes a cargo compartment and - Image data obtained from an autonomous unmanned aerial vehicle system It is characterized by its transfer to an image processing model.

9. A unified command and safety system in high-risk work environments. It is a method for its operation, and its characteristic is; 10 - Employee ID from a wearable smart device carried by the employee or Obtaining biometric data associated with device identity, - Internet of Things-based environmental sensor network for workspace Obtaining environmental measurement data associated with the information, - Image of the work area from the computer vision camera system 15 data acquisition, - equipment associated with equipment identifier from work equipment Obtaining status data, - job type, work area, shift information, employee assignment or job Obtaining operational data that includes at least one of the flow statuses, 20 - Biometric data, environmental measurement data, image data, equipment status data and operational data to the central command and control structure transfer, - The transferred data includes employee ID, device ID, and workspace information. At least 25 corresponding to the data type from equipment ID and time information. associating using one, - In the health analysis model of biometric data, environmental measurement data In the environmental risk analysis model, image data is processed using image processing. in the model, equipment condition data in the predictive maintenance model and Processing operational data in the operational decision support model, 30 - Combining the analysis outputs obtained from at least two different models an employee, work area, equipment or operation associated with Establishing a security situation, - Working areas using the security situation and current data received, digital representations of employees and work equipment. Updating the twin structure, - security status and spatial data in the digital twin structure Establishing risk levels for different work areas by correlating them, 5 - health analysis output, risk levels for study areas, and By processing operational data together, employee identity, work area and shift data including matching between shift times creation, - Security status, spatial data in digital twin structure, risk levels 10 and emergency data using at least two of the shift data. creation and - Emergency data to mobile application and notification system, autonomous data with unmanned aerial vehicle systems and external emergency units The steps for transferring the communication to the integration interface are 15. It is characterized by its inclusion.

10. It is a method according to claim 9, and its characteristic is; - Analysis output obtained from a single data source, in common time range and different belonging to the same employee, work area or equipment Comparison with the analysis output obtained from the data source, 20 - Determining the agreement information between the analysis outputs, - using the analysis outputs of the security status and compliance information creation, - if the security situation corresponds to the emergency level Location information in emergency data autonomous unmanned aerial vehicle 25 transfer to the system, - the location information of the autonomous unmanned aerial vehicle system directing to the field of study accordingly, - Obtaining image data from an autonomous unmanned aerial vehicle system reprocessing in the image processing model and 30 - Digital twin with analysis output of reprocessed image data. the relevant field of study in its structure and the relevant risk map based on prediction It is characterized by including steps to update the risk level.

Images