Description:FIELD OF INVENTION
[0001] Embodiments of the present disclosure relate to the field of safety training in a manufacturing industry, and more particularly, a system and a method for safety hazard identification training with real-time assessment.
BACKGROUND
[0002] In a manufacturing industry, workers are unaware of potential hazards in their daily task and often fail to follow safety protocols due to lack of awareness and training, which increases risk of workplace accidents.
[0003] Traditionally, safety training programs such as Kiken Yochi Training (KYT), aim to help the workers recognize and predict the potential hazards, improving their ability to sense unsafe conditions. However, conventional KYT is conducted manually on a paper and typically in a single language, making it outdated, difficult to scale, and ineffective for real-time learning, record management and result analysis. Further, absence of interactive and accessible training methods leads to poor engagement, minimal retention of safety practices, and inefficient record-keeping. As the manufacturing industry moves towards automation and digital transformation, there is a growing need for an improved safety training system that enhances hazard recognition, provides real-time feedback, and ensures wider accessibility for the workers in diverse environments.
[0004] Hence, there is a need for an improved system for identifying safety hazards which addresses the aforementioned issue(s).
OBJECTIVE OF THE INVENTION
[0005] An objective of the present invention is to provide two distinct operational modes to a user via a user interface: a learning mode and a basic mode. In the learning mode, the user acquires knowledge, practices, or gain familiarity with a potential risk areas within a factory environment, thereby enabling the user to understand safety protocols, hazard identification and practices for risk mitigation related to factory operations, equipment handling, and workplace hazards. In the basic mode, the user demonstrates his/her understanding by participating in an assessment based on a learned concept.
[0006] Another objective of the invention is to track a performance metrics of the user to ensure effective learning outcomes, identify gaps in knowledge, and enhance workplace safety.
[0007] Yet, another objective of the invention is to store an identified risk areas in a repository, wherein the stored identified risk areas can be accessed, managed, and updated across multiple devices, ensuring seamless availability and synchronization of critical safety information.
BRIEF DESCRIPTION
[0008] In accordance with an embodiment of the present disclosure, a system for safety hazard identification training with real-time assessment is provided. The system includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a user interface module configured to allow an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment. The user interface module is also configured to enable the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment., wherein the one or more scenario-based images are stored in a repository. Further, the processing subsystem includes an evaluation module operatively coupled to the user interface module, wherein the evaluation module is configured to evaluate the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository. The processing subsystem also includes a feedback module operatively coupled to the evaluation module, wherein the feedback module is configured to provide a feedback to the user upon completion of the training session, wherein the feedback module comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks. Further, the processing subsystem includes a report generation module operatively coupled to the evaluation module, wherein the report module is configured to generate an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment. Furthermore, the processing subsystem includes an analytics module operatively coupled to the evaluation module, wherein the analytics module is configured to generate a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels.
[0009] In accordance with another embodiment of the present disclosure, a method for safety hazard identification training with real-time assessment is provided. The method includes allowing, by a user interface module, an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images that align with a region-specific safety regulation corresponding to a workplace within a factory environment. The method also includes enabling, by the user interface module, the user to interact with the one or more scenario-based images upon identifying one or more risk areas in the one or more scenario-based images based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment, wherein the one or more scenario-based images are stored in a repository. Further, the method includes evaluating, by an evaluation module, the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository. Furthermore, the method includes providing, by a feedback module, a feedback to the user upon completion of the training session, wherein the feedback module comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks. Moreover, the method includes generating, by a report generation module, an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment. Additionally, the method includes generating, by an analytics module, a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels.
[0010] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0012] FIG. 1 is a block diagram representation of a system for safety hazard identification training with real-time assessment in accordance with an embodiment of the present disclosure;
[0013] FIG. 2 is a block diagram of an exemplary embodiment of the system for safety hazard identification training with real-time assessment of FIG. 1 in accordance with an embodiment of the present disclosure;
[0014] FIG. 3 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure;
[0015] FIG. 4 (a) illustrates a flow chart representing the steps involved in a method for safety hazard identification training with real-time assessment in accordance with an embodiment of the present disclosure; and
[0016] FIG. 4 (b) illustrates continued steps of the method of FIG. 4 (a) in accordance with an embodiment of the present disclosure.
[0017] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[0018] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[0019] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or subsystems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0021] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0022] Embodiments of the present disclosure relate to a system for safety hazard identification training with real-time assessment is provided. The system includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a user interface module configured to allow an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment. The user interface module is also configured to enable the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images or videos based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment, wherein the one or more scenario-based images videos are stored in a repository. Further, the processing subsystem includes an evaluation module operatively coupled to the user interface module, wherein the evaluation module is configured to evaluate the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository. The processing subsystem also includes a feedback module operatively coupled to the evaluation module, wherein the feedback module is configured to provide a feedback to the user upon completion of the training session, wherein the feedback module comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks. Further, the processing subsystem includes a report generation module operatively coupled to the evaluation module, wherein the report module is configured to generate an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment. Furthermore, the processing subsystem includes an analytics module operatively coupled to the evaluation module, wherein the analytics module is configured to generate a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels.
[0023] FIG. 1 is a block diagram representation of a system for safety hazard identification training with real-time assessment in accordance with an embodiment of the present disclosure. The system (100) includes a processing subsystem (110) hosted on a server (120). In one embodiment, the server (120) may include a cloud-based server. In another embodiment, parts of the server (120) may be a local server coupled to a user device. The processing subsystem (110) is configured to execute on a network (130) to control bidirectional communications among a plurality of modules. In one example, the network (130) may be a private or public local area network (LAN) or Wide Area Network (WAN), such as the Internet. In another embodiment, the network (130) may include both wired and wireless communications according to one or more standards and/or via one or more transport mediums. In one example, the network (130) may include wireless communications according to one of the 802.11 or Bluetooth specification sets, or another standard or proprietary wireless communication protocol. In yet another embodiment, the network (130) may also include communications over a terrestrial cellular network, including, a global system for mobile communications (GSM), code division multiple access (CDMA), and/or enhanced data for global evolution (EDGE) network.
[0024] The system (100) includes a user interface module (140), an evaluation module (150), a feedback module (160), a report generation module (170), and an analytics module (180).
[0025] The user interface module (140) is configured to allow an administrator to select an at least one mode from a plurality of modes via a user interface. Typically, the administrator is responsible for monitoring safety protocols in a workplace and the administrator ensures that a plurality of workers follow safety guidelines while working. As used herein, the workplace is an industrial area, such as manufacturing unit, factory unit, warehouse, and a construction unit that includes heavy machines, hazardous material handling, and high-risk tasks performed by the plurality of workers such as welding, and electrical work.
[0026] Further, the user interface module (140) is configured to support a plurality of languages facilitating accessibility for a diverse workforce across multiple geographical regions.
[0027] Furthermore, the plurality of modes includes a learning mode and a basic mode. In the learning mode, a training session is presented to a user. As used herein, the user may be a machine operator in the workplace. In the basic mode, an assessment is presented to the user. Typically, the assessment is an evaluation process to test understanding of the user regarding potential hazard within the factory environment.
[0028] Typically, the training session and the assessment includes one or more scenario-based images or videos related to hazard identification, emergency response, usage of personal protective equipment (PPE), and safe machinery handling that align with a region-specific safety regulation corresponding to the workplace within a factory environment. As used herein, the one or more scenario-based images or videos visually represent workplace scenarios. Examples of the one or more scenario-based images or videos include the following:
• A worker operates a machine without using safety guards, leading to potential injury risk.
• Incorrect usage of gloves while handling hazardous chemicals.
• Usage of damaged electrical cable to plug into a socket, increasing risk of fire.

[0029] Typically, the one or more scenario-based images or videos are captured by an individual within the factory environment and deploy in a repository for use in the training session and the assessment. Further, the repository provides a centralized storage for the one or more scenario-based images or videos and enable the user to instantly access the training session across multiple user device, ensuring data security and allow the users to participate in the training session from any location.

[0030] In one embodiment, a camera unit (195) is positioned in the factory environment, wherein the camera unit (195) includes an artificial intelligence model configured to capture and analyze the one or more scenario-based images or videos within the factory environment. Typically, the artificial intelligence model is configured to process the one or more scenario-based images or videos and transmits it to a user device. It is to be noted that the user device may include, but is not limited to, a mobile phone, desktop computer, portable digital assistant (PDA), smart phone, tablet, ultra-book, netbook, laptop, multi-processor system, microprocessor-based or programmable consumer electronic system, or any other communication device that a user may use. In some embodiments, the user device may comprise a display module (not shown) to display information (for example, in the form of user interfaces). In further embodiments, the user device may comprise one or more of touch screens, accelerometers, gyroscopes, cameras, microphones, global positioning system (GPS) devices, and so forth.

[0031] The user interface module (140) is also configured to enable the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images or videos based on real-time factory scenarios. Typically, the user marks the one or more risk areas by interacting with the user interface through one or more methods. The one or more methods includes but is not limited to clicking or tapping on the user interface, drawing or highlighting, and voice commands.

[0032] The one or more risk areas include at least one of an unsafe condition, a hazardous action, and a risk-prone environment. Typically, the one or more scenario-based images or videos are stored in a repository.
[0033] The evaluation module (150) is operatively coupled to the user interface module (140). The evaluation module (150) is configured to evaluate the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository. The pre-configured risk areas are identified and uploaded by the administrator to the repository. For example, in a manufacturing plant, the pre-configured risk areas such as unguarded machinery, exposed electrical wiring, improper stacking of materials in a storage, and incorrect usage of personal protective equipment (PPE). When the user participates in the assessment, the user is required to identify the one or more risk areas. If the user correctly marks an unguarded machine part as a risk, the evaluation module (150) verifies selection by comparing it with the pre-configured risk areas and assigns a score of 1. Conversely, if the user incorrectly marks a non-hazardous area, the evaluation module (150) identifies an incorrect response and assigns a score of 0.
[0034] The feedback module (160) is operatively coupled to the evaluation module (150). The feedback module (160) is configured to provide a feedback to the user upon completion of the training session. Typically, the feedback includes one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks. For example, in the factory environment, upon completion of the training session, the user correctly marks exposed electrical wiring and improperly stored chemicals but fails to identify a slippery floor due to an oil spill in the training session. Further, the feedback module (160) provides detailed feedback highlighting a missed hazard (the oil spill). The feedback module (160) may provide the feedback to the user “ the oil spill on a floor creates a slippery floor increasing risk of slips and falls”.
[0035] Further, the feedback is tailored to each user, providing specific guidance on improving hazard identification and developing effective response strategies, thereby enhancing the user's ability to identify the one or more risk areas and take appropriate preventive measures in real-world scenarios.
[0036] The report generation module (170) is operatively coupled to the evaluation module (150). The report generation module (170) is configured to generate an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment. For example, if the user correctly identifies three risk areas out of a total of five possible risk areas. The report generation module (170) assigns a score of 3/5, reflecting number of correctly identified risks. The generated report provides a numerical assessment score, which is utilized by the administrator to track performance of the plurality of users.
[0037] The analytics module (180) is operatively coupled to the evaluation module (150). The analytics module (180) is configured to generate a plurality of performance metrics of a plurality of users based on the assessment score and the training session. The plurality of performance metrics comprises a training progress (percentage of the training session completed by the user), success rates in hazard identification, areas requiring improvement (Specific hazard types or safety concepts where the user shows lower accuracy), and overall compliance levels (percentage of the users completed the training session and the assessment).
[0001] It must be noted that, in the learning mode, the user receives instant feedback related on the one or more unidentified risk areas and correct them immediately in real-time. Further, in the basic mode, only an assessment score is generated upon completion of the assessment, without providing immediate feedback on the one or more unidentified risk areas.
[0002] FIG. 2 is a block diagram of an exemplary embodiment of a system for safety hazard identification training with real-time assessment in accordance with an embodiment of the present disclosure. The processing subsystem (110) includes a customization module (190). The customization module (190) is operatively coupled to the user interface module (140). Typically, the customization module (190) is configured to allow an administrator to modify and update the one or more scenario-based images or videos upon highlighting additional risk areas to reflect evolving workplace hazards, operational workflows, safety concerns and equipment, ensuring that the updated one or more scenario-based images or videos aligns directly with on-ground realities. For example, in a factory environment, if a new robotic arm is introduced, it may create new safety risks. The administrator updates the new safety risks, ensuring that workers are trained on latest safety concerns. Similarly, if a new chemical storage area is added, the administrator highlights spill risks or proper handling procedures to keep the training content relevant and effective.
[0003] Typically, the administrator utilizes a drag-and-drop scenario editor on the user interface to update the one or more scenario-based images or videos as hazards evolve or new equipment and processes are introduced. The one or more scenario-based images or videos that are updated and configurable by the user ensure that the users are exposed to relevant and realistic hazard identification exercises, enhancing retention and practical application.
[0004] Further, the system (100) includes a camera unit (195) configured to capture a live video of the user while undergoing the training session and the assessment to prevent impersonation, ensuring only assigned user completes the training session and the assessment. Typically, the camera unit (195) utilizes a facial recognition and an artificial intelligence-based activity detection to monitor user engagement. The facial recognition verifies identity of the user, thereby reducing risk of fraudulent activities.
[0005] The artificial intelligence-based activity detection is configured to monitor engagement of the user, ensuring that the user remains actively engaged throughout the training session and the assessment.
[0006] In one embodiment, the camera unit (195) is adapted to track facial expressions of the user to determine level of attentiveness.
[0007] In a non-limiting example, consider a scenario, where user X is a worker in a manufacturing industry, logs into a user device (100) via a user interface module (140). The administrator has pre-configured one or more scenario-based images or videos and deployed them in a repository. Upon logging in, the user X chooses a learning mode. Opting for the learning mode, the User X engages in a training session where the one or more scenario-based images or videos are displayed on the user interface module (140) such as unguarded machinery and exposed electrical wiring. As the User X identifies and marks one or more risk areas, the evaluation module (150) instantly assesses the identified one or more risk areas against the pre-configured one or more scenario-based images or videos stored in the repository. If the User X misses to identify risk areas, the feedback module (160) highlights the unidentified risk areas and provides real-time corrective guidance.
[0008] In an another example, an administrator is allowed to view, access and select a plurality of features via the user interface. The plurality of features includes location selection, test, section, and login functionality. Upon selecting the plurality of features, the administrator allows the user to take the assessment in a basic mode. Upon completion of the assessment, an assessment score is generated via a report generation module (170). Meanwhile, the camera unit (195) records a live video of the user while undergoing the assessment, using a facial recognition and AI-based activity detection to verify engagement and prevent impersonation. Furthermore, the analytics module (180) then compiles performance metrics, analyzing User X’s progress, hazard identification accuracy, and areas requiring improvement. Further, the administrator is allowed to configure and customize the one or more scenario-based images or videos to reflect evolving workplace hazards and equipment.
[0009] FIG. 3 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (120) includes processor(s) (430), and memory (410) operatively coupled to the bus (420). The processor(s) (430), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.
[0010] The memory (310) includes several subsystems stored in the form of executable program which instructs the processor (330) to perform the method steps illustrated in FIG. 1. The memory (310) includes a processing subsystem (110) of FIG.1. The processing subsystem (110) includes a plurality of modules. The plurality of modules includes a red team simulator module (150) and a blue team simulator module (160).
[0011] The user interface module (140) is configured to allow an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment. The user interface module (140) is also configured to enable the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images or videos based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment, wherein the one or more scenario-based images or videos are stored in a repository. Further, the evaluation module (150) is operatively coupled to the user interface module (140), wherein the evaluation module (150) is configured to evaluate the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository. Furthermore, the feedback module (160) is operatively coupled to the evaluation module (150), wherein the feedback module (160) is configured to provide a feedback to the user upon completion of the training session, wherein the feedback module (160) comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks. Moreover, a report generation module (170) is operatively coupled to the evaluation module (150), wherein the report generation module (170) is configured to generate an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment. Additionally, an analytics module (180) is operatively coupled to the evaluation module (150), wherein the analytics module (180) is configured to generate a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels.
[0012] The bus (320) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (320) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bit-serial format and the parallel bus transmits data across multiple wires. The bus (320) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.
[0013] FIG. 4 (a) illustrates a flow chart representing the steps involved in a method for safety hazard identification training with real-time assessment in accordance with an embodiment of the present disclosure. FIG. 4 (b) illustrates continued steps of the method of FIG. 4 (a) in accordance with an embodiment of the present disclosure.
[0014] The method (300) includes allowing, by a user interface module, an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment in step (310). The one or more scenario-based images or videos are captured by an individual within the factory environment and deploy in the repository for use in the training session and the assessment. Typically, the one or more scenario-based images or videos are fetched from the repository during the assessment and the training session.
[0015] Further, the administrator is allowed to view, access and select a plurality of features via the user interface, wherein the plurality of features comprises a location selection, test, section, and login functionality.
[0016] The method (300) also includes enabling, by the user interface module, the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images or videos based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment, wherein the one or more scenario-based images or videos are stored in a repository in step (320). The user is allowed to view a plurality of features on the user interface module, wherein the plurality of features comprises a training session dashboard, an assessment dashboard, and the report generation module.
[0017] Further, the method (300) includes evaluating, by an evaluation module, the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository in step (330).
[0018] Furthermore, the method (300) includes providing, by a feedback module, a feedback to the user upon completion of the training session, wherein the feedback module comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks in step (340).
[0019] Moreover, the method (300) includes generating, by a report generation module, an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment in step (350).
[0020] Additionally, the method (300) includes generating, by an analytics module, a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels in step (360).
[0021] Various embodiments of the system for safety hazard identification training with real-time assessment above provide various benefits upon allowing an users to interact with one or more scenario-based images or videos seamlessly. The evaluation module (150) ensures accuracy in hazard identification by instantly comparing user responses with pre-configured risk areas stored in a repository, promoting real-time learning in a learning mode. Further, the feedback module (160) improves training effectiveness by providing immediate insights into unidentified risks, helping the user to understand hazard prediction and response strategies in the learning mode. Furthermore, the report generation module (170) facilitates performance tracking by generating an assessment score based on corrective responses in a basic mode. Moreover, the analytics module (180) provides actionable insights by compiling training progress, hazard identification success rates, and compliance levels, helping an administrator to identify areas needing improvement. Additionally, the customization module (190) allows the administrator to update the one or more scenario-based images or videos to reflect evolving workplace hazards. Moreover, the camera unit (195) enhances security and engagement by preventing impersonation and monitoring user activity through facial recognition and AI-based activity detection.
[0022] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing subsystem” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A electronic control unit including hardware may also perform one or more of the techniques of this disclosure.
[0023] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules, or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components.
[0024] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[0025] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0026] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.
, Claims:1. A system (100) for safety hazard identification training with real-time assessment comprising:
characterized in that,
a processing subsystem (110) hosted on a server (120) wherein the processing subsystem (110) is configured to execute on a network (130) to control bidirectional communications among a plurality of modules comprising:
a user interface module (140) configured to:
allow an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode,
wherein, in the learning mode, a training session is presented to a user,
wherein, in the basic mode, an assessment is presented to the user,
wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment; and
enable the user to interact with the one or more scenario-based images upon identifying one or more risk areas in the one or more scenario-based images or videos based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment,
wherein the one or more scenario-based images or videos are stored in a repository;
an evaluation module (150) operatively coupled to the user interface module (140), wherein the evaluation module (150) is configured to:
evaluate the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository;
a feedback module (160) operatively coupled to the evaluation module (150), wherein the feedback module (160) is configured to provide a feedback to the user upon completion of the training session, wherein the feedback module (160) comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks; and
a report generation module (170) operatively coupled to the evaluation module (150), wherein the report generation module (170) is configured to generate an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment; and
an analytics module (180) operatively coupled to the evaluation module (150), wherein the analytics module (180) is configured to generate a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels.

2. The system (100) as claimed in claim 1, wherein the repository is configured to store the assessment score, and the identified one or more risk areas.

3. The system (100) as claimed in claim 1, wherein the one or more scenario-based images or videos are captured by an individual within the factory environment and deploy in the repository for use in the training session and the assessment.

4. The system (100) as claimed in claim 1, wherein the one or more scenario-based images or videos are fetched from the repository during the assessment and the training session.

5. The system (100) as claimed in claim 1, comprising a customization module (190) operatively coupled to the user interface module (140), wherein the customization module (190) is configured to allow the administrator to modify, and update the one or more scenario-based images or videos upon highlighting additional risk areas to reflect evolving workplace hazards and equipment.

6. The system (100) as claimed in claim 1, wherein the user is allowed to view a plurality of features on the user interface module (140), wherein the plurality of features comprises a training session dashboard, an assessment dashboard, and the report generation module (170).

7. The system (100) as claimed in claim 1, comprising a camera unit (195) operatively coupled to the user interface module (140), wherein the camera unit (195) is adapted to:

capture a live video of the user while undergoing the training session and the assessment to prevent impersonation,
wherein the camera unit (195) utilizes a facial recognition and an artificial intelligence-based activity detection to monitor user engagement.

8. The system (100) as claimed in claim 1, wherein the administrator is allowed to view, access and select a plurality of features via the user interface, wherein the plurality of features comprises a location selection, test, section, and login functionality.

9. A method (300) for safety hazard identification training with real-time assessment comprising:
characterized in that,
allowing, by a user interface module, an administrator to select an at least one mode from a plurality of modes via a user interface, wherein the plurality of modes comprises a learning mode and a basic mode, wherein, in the learning mode, a training session is presented to a user, wherein, in the basic mode, an assessment is presented to the user, wherein the training session and the assessment comprises one or more scenario-based images or videos that align with a region-specific safety regulation corresponding to a workplace within a factory environment; (310)

enabling, by the user interface module, the user to interact with the one or more scenario-based images or videos upon identifying one or more risk areas in the one or more scenario-based images or videos based on a real-time factory scenarios, wherein the one or more risk areas comprises an at least one unsafe condition, a hazardous action, and a risk-prone environment, wherein the one or more scenario-based images or videos are stored in a repository; (320)

evaluating, by an evaluation module, the identified one or more risk areas in real-time upon comparing the identified one or more risks areas to a pre-configured risk areas stored in the repository, wherein the pre-configured risk areas are identified and uploaded by the administrator to the repository; (330)

providing, by a feedback module, a feedback to the user upon completion of the training session, wherein the feedback module comprises one or more unidentified risks to enhance a training outcome, thereby enabling the user to interpret and learn the unidentified risks; (340)

generating, by a report generation module, an assessment score upon completion of the assessment based on a corrective response provided by the user during the assessment; (350) and

generating, by an analytics module, a plurality of performance metrics of a plurality of users based on the assessment score and the training session, wherein the plurality of performance metrics comprises a training progress, success rates in hazard identification, areas requiring improvement, and overall compliance levels. (360)
Dated this 06th day of May 2025
Signature

Manish Kumar
Patent Agent (IN/PA-5059)
Agent for the Applicant