Description:FIELD OF THE INVENTION

[0001] The present invention relates to a verification conducting system that is designed for the validation and verification of individuals' identity, for ensuring accurate recognition through multiple methods, thereby provide secure and efficient identity verification in contexts such as telephonic interviews, written examinations, and other secure environments, and ensuring that only authorized individuals are granted access or are validated during the process.

BACKGROUND OF THE INVENTION

[0002] In job interviews, verifying the identity and credentials of candidates is crucial to ensure authenticity and reduce fraud. Traditionally, identity verification was carried out manually through physical document checks and in-person assessments. Voice recognition, a natural method of identifying individuals, was sometimes used but required manual input and interpretation. Document verification was limited to visually inspecting IDs, resumes, and certificates, which is easily manipulated or forged. The drawbacks of these traditional methods included human error, time consumption, and the risk of false verification, leading to inefficiency and security concerns in the hiring process.

[0003] Traditional approaches focusing on manual checks for identity and credentials. Initially, identity verification relied on physical documents, such as birth certificates, ID cards, and written letters of recommendation. Verification often involved human judgment to authenticate the document's authenticity, with additional manual steps such as calling references or inspecting signatures. Similarly, for job interviews, verification methods such as handwritten resumes and personal interviews served as the primary means of validating a candidate's identity, qualifications, and credibility. However, these are time consuming process and there are chances of occurrence of human error. So, people also access digital verification system, as incorporating sophisticated biometrics (such as fingerprints and facial recognition) and machine learning module for more accurate identification. Despite advancements, these systems can still be hacked or spoofed using high-quality replicas, making them vulnerable. Also, these present challenges for individuals with physical conditions, such as injured fingers or face blindness. Privacy issues remain a concern regarding the collection and storage of biometric data.

[0004] WO2001003077A1 discloses about an invention that includes a method of generating documents and verifying their authenticity firstly requires controller access to a document creation system so that only authorised users can create documents. User data which identifies a user of the system is recorded, and verification data is generated from both the user data and data corresponding to documents generated using the system. Authentication data corresponding to the verification data is recorded, and the document is then printed with a machine-readable portion containing the verification data. The machine-readable portion is typically a two-dimensional bar code or symbol. When the document is presented, the verification data is read from it, for example by optical scanning, and compared with retrieved authentication data to indicate whether or not the document is authentic.

[0005] WO2017136879A1 discloses about an invention that includes a system and method for document information authenticity verification for applications including verifying the authenticity of information of statements of attainment of course documentation issued by registered training organisations, verification of travel documents and other sensitive documents requiring authenticity verification such as documents issued by law firms, accountancy firms, governmental institutions and the like. The method may comprise a verification record creation stage comprising: receiving document content metadata from a document; generating a metadata hash using the document content metadata; creating a blockchain transaction comprising the metadata hash; and generating computer readable data encoding the metadata hash; updating the document with the computer readable data and a document verification stage comprising: receiving the document; extracting the metadata hash from the computer readable data; and identifying the metadata hash within blockchain transactions of the blockchain to verify the authenticity of the document metadata.

[0006] Conventionally, many systems have been developed that are capable of verifying documents and other aspects during the interview. However, these systems are incapable of using multiple biometric and data validation methods, to authenticate individuals during high-security processes. Additionally, these existing systems also lack in ensuring that any discrepancies or anomalies in the verification process are promptly detected and addressed automatically.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a system that uses multiple biometric and data validation methods, to authenticate individuals during high-security processes, such as telephonic interviews and written examinations. In addition, the developed system also allows a concerned authority to monitor, manage, and control the verification process, for ensuring efficiency and accuracy in identity validation while maintaining user privacy and security.

OBJECTS OF THE INVENTION

[0008] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0009] An object of the present invention is to develop a system that uses multiple biometric and data validation methods, to authenticate individuals during high-security processes, such as telephonic interviews and written examinations.

[0010] Another object of the present invention is to develop a system that allows a concerned authority to monitor, manage, and control the verification process, for ensuring efficiency and accuracy in identity validation while maintaining user privacy and security.

[0011] Yet another object of the present invention is to develop a system that ensure that any discrepancies or anomalies in the verification process are promptly detected and addressed automatically, and simultaneously provide alert to the concerned authority regarding the falls of rating below a predefined threshold.

[0012] The foregoing and other objects, features, and advantages of the present invention will become readily apparent upon further review of the following detailed description of the preferred embodiment as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION

[0013] The present invention relates to a verification conducting system that is able to implement a multi-layered authentication process that reduces the risk of identity fraud by combining facial recognition, biometric data, voice recognition, and document analysis into a single system.

[0014] According to an embodiment of the present invention, a verification conducting system comprises of, a user interface accessed by a concerned authority to input voice recording, signatures, facial features, verification documents and biometrics of various individuals recorded during written examination and telephonic interview of the individuals , that is saved in an associated cloud database, an enclosure configured a motorized slidable door attached with an entrance of the enclosure, a PIR (passive infrared sensor) sensor installed over the entrance to determine presence an individual in proximity to the entrance, based on which the slidable door open and enable the user to enter the enclosure, an artificial intelligence based imaging unit installed within the enclosure to determine presence of the user, a laser projection unit installed within the enclosure to project a marking over ground surface of the enclosure to guide the user to stand over the marking, a facial feature recognition module integrated with the imaging unit to determine facial features of the individual, a biometric sensor mapped within the enclosure to enable the user to provide biometrics, an OCR (Optical Character Recognition) module is integrated with the imaging unit to determine text written over verification and signature documents positioned on a table arranged proximity to the imaging unit by the individual, and based on output of the OCR module, the database is accessed by the microcontroller for matching text written over the positioned documents with pre-saved verification documents and signatures provided by the determined individual during the examination.

[0015] According to another embodiment of the present invention, the proposed system further comprises of, a touch interactive display panel mapped within the enclosure to display answers spoken by the individual in the telephonic interview, a microphone is installed within the enclosure to capture answers spoken by the individual that is analyzed for matching with the pre-saved voice recording of the telephonic interview to determine authentication of the voice recording, an analyzing module including a Recurrent Neural Networks (RNNs), Artificial Neural Networks (ANNs), and Convolutional Neural Networks (CNNs), is integrated with the microcontroller to analyse voice of the answers spoken by the individual, the microcontroller based on output of the facial feature recognition module, the biometric sensor, the OCR (Optical Character Recognition) module and the analyzing module evaluates verification rating for the individual and accordingly display over the display panel and in case the monitored rating recedes a threshold value, the microcontroller sends an alert notification to the concerned authority to enable the authority to take necessary actions accordingly.

[0016] While the invention has been described and shown with particular reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0017] These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
Figure 1 illustrates a perspective view of a verification conducting system

DETAILED DESCRIPTION OF THE INVENTION

[0018] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

[0019] In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

[0020] As used herein, the singular forms “a,” “an,” and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.

[0021] The present invention relates to a verification conducting system that employs a variety of biometric and data validation techniques to verify individuals during critical processes, such as telephonic interviews and written exams. Additionally, the system enables the responsible authority to oversee, administer, and regulate the verification procedure, for ensuring both precision and effectiveness in confirming identities while safeguarding user privacy and security.

[0022] Referring to Figure 1, a perspective view of a verification conducting system is illustrated, respectively, comprising an enclosure 101 configured a motorized slidable door 102 attached with an entrance of the enclosure 101, an artificial intelligence based imaging unit 103 installed within the enclosure 101, a laser projection unit 104 installed within the enclosure 101, a biometric sensor 105 mapped within the enclosure 101, a touch interactive display panel 106 mapped within the enclosure 101, a microphone 107 is installed within the enclosure 101, a table 108 arranged proximity to the imaging unit 103.

[0023] The system disclosed herein comprising a user interface, that is accessible by an authorized authority, facilitates the input and storage of critical verification data, including voice recordings, signatures, facial features, biometric information, and other relevant documents of individuals recorded during written examinations and telephonic interviews. This data is securely stored in a cloud-based database, ensuring proper organization and protection of sensitive information.

[0024] The cloud database is designed to maintain the integrity, privacy, and accessibility of the data, in compliance with applicable data protection and security regulations. The stored information serves as a reliable reference for verification and authentication purposes, thereby ensuring the accuracy and legitimacy of the examination process while preventing fraud and unauthorized access.

[0025] An enclosure 101 is configured with a motorized slidable door 102, which is attached to the entrance of the enclosure 101. Prior actuation of the door 102, the microcontroller determine presence an individual in proximity to the entrance via a PIR (passive infrared sensor) sensor installed over the entrance. The PIR (Passive Infrared) sensor detects presence of the individual by sensing changes in infrared radiation. The sensor consists of a pyroelectric sensor that measures the infrared energy emitted by user within its field of view. When the user, moves across the sensor’s range, it alters the infrared radiation patterns. The sensor’s circuitry converts these changes into an electrical signal, triggering an output response, to determine presence an individual in proximity to the entrance.

[0026] As the presence of individual is determined, the microcontroller actuates the door 102. The door 102 operates through a sliding unit integrated within it. The sliding unit consists of a pair of sliding rails fabricated with grooves in which the wheel of a slider is positioned that is further connected with a bi-directional motor via a shaft. The microcontroller actuates the bi-directional motor to rotate in clockwise and anti-clockwise direction that aids in rotation of shaft, wherein the shaft converts the electrical energy into rotational energy for allowing movement of the wheel to translate over the sliding rail by a firm grip on the grooves. The movement of the slider results in translation of the door 102, result in opening/closing of the door 102 to enable the user to enter the enclosure 101.

[0027] Inside the enclosure 101 an artificial intelligence based imaging unit 103 is installed which on actuation determines presence of the user. The imaging unit 103 disclosed herein comprises of an image capturing arrangement including a set of lenses that captures multiple images of the individual and the captured images are stored within memory of the imaging unit 103 in form of an optical data. The imaging unit 103 also comprises of the processor which processes the captured images.

[0028] This pre-processing involves tasks such as noise reduction, image stabilization, or color correction. The processed data is fed into AI protocols for analysis which utilizes machine learning techniques, such as deep learning neural networks, to extract meaningful information from the visual data which are processed by the microcontroller to determine presence of the user.

[0029] Synchronously, the microcontroller actuates a laser projection unit 104 installed within the enclosure 101. The laser projection unit 104 comprises of a laser light source, a set of mirrors and lens integrated with the microcontroller. The laser light source generates a focused beam of light, which is directed towards the mirrors. These mirrors, controlled by the microcontroller, rapidly adjust their angles to steer the laser beam in precise patterns. The lens focuses the beam onto the desired area, ensuring sharp and accurate projections. The microcontroller, in sync with the imaging unit 103, processes the user-specified design and converts it into control signals for the mirrors. As the mirrors move, the projection unit 104 project a marking over ground surface of the enclosure 101 to guide the user to stand over the marking.

[0030] The imaging unit 103 mentioned above is linked with a facial feature recognition module, wherein the facial feature recognition module accesses images captured by the imaging unit 103. The facial recognition module then processes this data using protocols to detect and analyze facial features, such as the size and shape of the eyes, nose, and mouth, as well as the overall facial structure. Next, the module compares these features with a database of known faces to identify or verify the individual's identity. Advanced modules may utilize deep learning techniques to improve accuracy and adaptability over time. The result is a reliable method for recognizing individuals for security, authentication, or personalized experiences in various applications.

[0031] After the facial features of the individual is determined, the microcontroller enable the user to provide biometrics through a biometric sensor 105 that is mapped within the enclosure 101. The biometric sensor 105 works by examining finger's ridges and valleys that are pressed, and a series of distinct points, where ridges and valleys end or meet, are called minutiae are scanned. These minutiae are the points the biometric sensor 105 uses for comparing the input biometric impressions with a pre-stored data present in a server via the microcontroller in order to perform authentication of the user.

[0032] An Optical Character Recognition (OCR) module is integrated with the imaging unit 103 to accurately detect and interpret text written on verification and signature documents placed on a table 108 in close proximity to the imaging unit 103. The OCR technology works by capturing images of the documents and analyzing the text, converting it into machine-readable data. This allows for efficient extraction of information such as names, dates, signatures, and other relevant details from the documents. The integration of the OCR module with the imaging unit 103 ensures precise and automated processing of the verification documents, improving the speed and accuracy of document verification during the identification process

[0033] Based on the output generated by the OCR module, the microcontroller accesses the associated database to compare the extracted text from the verification and signature documents with the pre-saved documents and signatures provided by the individual during the examination. The microcontroller processes the extracted text data and performs a matching operation against the stored records in the database. If the text from the positioned documents aligns with the pre-saved information, the microcontroller verifies the authenticity of the individual’s documents and signatures. This process ensures that the identity of the individual is accurately confirmed, thereby maintaining the integrity of the examination and verification procedure.

[0034] A touch interactive display panel 106 mapped within the enclosure 101 to display answers spoken by the individual in the telephonic interview. The display panel 106 comprises an LED or LCD screen, a control board, a backlight system, and input connectors. The LED/LCD screen serves as the main visual output, while the control board manages data input and image processing. The backlight system, often made of LEDs, illuminates the screen, ensuring visibility. When information is sent to the display, the control board processes the data and directs the LED/LCD pixels to show specific colors, creating images or text. The backlight adjusts brightness for optimal clarity. This combined functionality enables the panel 106 to display answers spoken by the individual in the telephonic interview.

[0035] A microphone 107 is installed within the enclosure 101 to capture the answers spoken by the individual during the examination. The microphone 107 captures sound by converting sound waves into electrical signals. When a sound wave reaches the microphone 107, it causes a diaphragm within the microphone 107 to vibrate. These vibrations are converted into corresponding electrical signals, through an electromagnetic process. The resulting electrical signals are then transmitted to an amplifier or processing unit for further analysis. The amplitude and frequency of the electrical signals correlate with the intensity and pitch of the sound wave, allowing the microcontroller to process and interpret the captured audio data.

[0036] The microcontroller compares the recorded voice with pre-saved voice recordings from the individual's telephonic interview. The microcontroller uses voice recognition module to analyze the audio patterns, such as pitch, tone, and speech patterns, and matches these characteristics with the stored voice data. This process ensures the authentication of the individual by confirming that the spoken answers match the pre-recorded voice, thereby validating the individual's identity and ensuring the integrity of the verification process.

[0037] An analyzing module comprising Recurrent Neural Networks (RNNs), Artificial Neural Networks (ANNs), and Convolutional Neural Networks (CNNs) is integrated with the microcontroller to process and analyze the voice responses provided by the individual. The RNNs are used to handle sequential data such as speech patterns, enabling the microcontroller to recognize temporal dependencies and detect context within the spoken answers. ANNs are employed to capture non-linear relationships in the data, enhancing the accuracy of voice feature extraction and classification. CNNs are utilized for their ability to detect spatial patterns in audio spectrograms, improving the microcontroller capacity to distinguish unique speech features, ensuring an effective comparison with the pre-recorded voice data for authentication.

[0038] Recurrent Neural Networks (RNNs) are essential for analyzing sequential audio data, such as voice patterns, to detect irregularities or unnatural sequences indicative of synthetic or altered voices. These networks process speech in sequences, where each audio frame is dependent on its predecessor, enabling the microcontroller to remember past information. This capability allows RNNs to identify natural speech patterns, including pitch, tone, and rhythm. RNNs classify voices as real or fake based on how closely the voice matches learned patterns and can detect playback or pre-recorded audio by recognizing unnatural timing or repetitions.

[0039] Artificial Neural Networks (ANNs) assist in general feature extraction and classification, enabling the microcontroller to discern complex relationships within voice data. They help differentiate between real and fake voices by analyzing various audio characteristics, further enhancing voice verification.

[0040] Convolutional Neural Networks (CNNs) are employed to analyze audio spectrograms, which are visual representations of sound. CNNs detect high-level patterns or anomalies within the voice, which signal manipulation. By combining RNNs, ANNs, and CNNs, the system creates a multi-layered approach to voice authentication. This fusion significantly enhances the system's ability to identify fake voices, providing robust security for voice-based authentication processes, especially in sensitive scenarios like interviews.

[0041] The microcontroller evaluates a verification rating for the individual based on the output from the facial feature recognition module, biometric sensor 105, Optical Character Recognition (OCR) module, and analyzing module. The microcontroller consolidates data from these various modules to assess the authenticity of the individual. The resulting verification rating is then displayed on the display panel 106, providing the concerned authority with a comprehensive and clear assessment of the individual's identity verification status. This process ensures accurate and efficient verification by utilizing multiple data points and advanced technologies.

[0042] If the monitored verification rating falls below a predefined threshold value, the microcontroller triggers an alert notification to the concerned authority. This alert enables the authority to take appropriate actions in response, ensuring that any discrepancies or potential security concerns are promptly addressed. The notification acts as a prompt for further investigation or corrective measures, maintaining the integrity and security of the verification process.

[0043] Moreover, a battery is associated with the system for powering up electrical and electronically operated components associated with the system and supplying a voltage to the components. The battery used herein is preferably a Lithium-ion battery which is a rechargeable unit that demands power supply after getting drained. The battery stores the electric current derived from an external source in the form of chemical energy, which when required by the electronic component of the system, derives the required power from the battery for proper functioning of the system.

[0044] Although the field of the invention has been described herein with limited reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternate embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention. , Claims:1) A verification conducting system, comprising a user interface accessed by a concerned authority to input voice recording, signatures, facial features, verification documents and biometrics of various individuals recorded during written examination and telephonic interview of said individuals, that is saved in an associated cloud database, characterized in that:

i) an enclosure 101 configured a motorized slidable door 102 attached with an entrance of said enclosure 101, wherein a PIR (passive infrared sensor) sensor installed over said entrance to determine presence an individual in proximity to said entrance based on which a microcontroller linked with said PIR sensor actuates said slidable door 102 to open and enable said user to enter said enclosure 101;

ii) an artificial intelligence based imaging unit 103 installed within said enclosure 101 and integrated with a processor for capturing and processing images of said individual, wherein based on said captured images, said microcontroller determines presence of said user and accordingly actuates a laser projection unit 104 installed within said enclosure 101 to project a marking over ground surface of said enclosure 101 to guide said user to stand over said marking;

iii) a facial feature recognition module integrated with said imaging unit 103 to determine facial features of said individual, wherein said captured facial features are matched by said microcontroller with pre-saved facial features saved in said database to determine said individual;

iv) a biometric sensor 105 mapped within said enclosure 101 to enable said user to provide biometrics, wherein said microcontroller access said database to match said received biometric with pre-saved biometrics of said individual for verifying said user;

v) an OCR (Optical Character Recognition) module is integrated with said imaging unit 103 to determine text written over verification and signature documents positioned on a table 108 arranged proximity to said imaging unit 103 by said individual, wherein based on output of said OCR module, said microcontroller access said database for matching text written over said positioned documents with pre-saved verification documents and signatures provided by said determined individual during said examination; and

vi) a touch interactive display panel 106 mapped within said enclosure 101 and actuated by said microcontroller to display answers spoken by said individual in said telephonic interview, wherein a microphone 107 is installed within said enclosure 101 to capture answers spoken by said individual that is analyzed by said microcontroller by matching with said pre-saved voice recording of said telephonic interview to determine authentication of said voice recording.

2) The system as claimed in claim 1, wherein an analyzing module including a Recurrent Neural Networks (RNNs), Artificial Neural Networks (ANNs), and Convolutional Neural Networks (CNNs), is integrated with said microcontroller to analyse voice of said answers spoken by said individual.

3) The system as claimed in claim 1, wherein said microcontroller based on output of said facial feature recognition module, said biometric sensor 105, said OCR (Optical Character Recognition) module and said analyzing module evaluates verification rating for said individual and accordingly display over said display panel 106.

4) The system as claimed in claim 1, wherein in case said monitored rating recedes a threshold value, said microcontroller sends an alert notification to said concerned authority to enable said authority to take necessary actions accordingly.