Smart restroom access with device authentication and payment integration

Abstract

The present disclosure relates to a system for smart restroom access with device authentication and payment integration is disclosed The system includes a user device having a circuitry configured to perform set of operations. A user input associated with a target object may be received. A prompt may be further prepared based on the user input. The target object may be identified as an identification result based on application of a neural image model on the prompt. It may be further determined whether the target object corresponds to the restroom. In response to the determination of the target object corresponding to the restroom as a positive identification result, the locking mechanism associated with the restroom door may be unlocked automatically, or unlocked after receiving confirmation of a payment transaction corresponding to the payment code display. A control signal may be transmitted to the locking mechanism to grant restroom access to the user.

Description

SMART RESTROOM ACCESS WITH DEVICE AUTHENTICATION AND PAYMENT INTEGRATIONFIELD OF THE INVENTION

[0001] The embodiments discussed in the present disclosure are related to the field of electronic access control systems and methods, and particularly relates to an authentication system and method for managing restroom access, and more particularly relates to a system and method for smart restroom access with device authentication and payment integration.BACKGROUND OF THE INVENTION

[0002] Public restrooms, particularly in restaurants, cafes, gas stations, and other commercial establishments, often face issues related to uncontrolled access, poor hygiene, and maintenance challenges. Traditionally, access to these restrooms is managed through physical keys, keypad locks, or token-based entry systems. However, these systems may have significant drawbacks. These significant drawbacks may include hygiene concerns, operational inefficiencies, uncontrolled access and overuse, and lack of revenue generation. For example, restroom keys may be frequently handled by multiple users, increasing the risk of bacterial and viral transmission. In environments such as restaurants and cafes, where hygiene is a priority, this may pose health risks to both customers and staff. Further, in many establishments, customers must request a key or access code from an employee, such as a bartender or cashier, to use the restroom. This process may disrupt business operations, creates inconvenience for staff, and may lead to long wait times for customers. Furthermore, publicly accessible restrooms may attract excessive use by non-customers, leading to overcrowding, higher maintenance costs, and sanitary concerns. Due to this, the establishments may struggle to regulate restroom access efficiently, which negatively impacts customer satisfaction. Additionally, many restroom proprietors, especially in high-traffic areas, may bear the financial burden of restroom maintenance without any direct means to offset these costs. For example, many of the coin-operated or token-based systems are often cumbersome, requiring regular maintenance and supervision. Hence, there is a need for improved restroom access system that enhances hygiene, streamlines access to restroom, enables controlled usage, and supports revenue generation.

[0003] The subject matter claimed in the present disclosure is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one example technology area where some embodiments described in the present disclosure may be practiced.

[0004] Limitations and disadvantages of conventional and traditional approaches will become apparent to one skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.OBJECTS AND FEATURES OF THE INVENTION

[0005] Accordingly, several objects and advantages of the present disclosure are to provide a system which incorporates use of a neural image model (NIM) for controlling access to a restroom based on image-based identification. Further, the system incorporates use of a user device with image capture capabilities to capture image of a target object. It is a further object of the present disclosure to provide the system which may be configured to receive, from the user device, a user input associated with the target object. The user input may be indicative of an image of the target object. It is another object and feature of the present disclosure to provide the system which incorporates use of the NIM to identify or classify the target object as an identification result on a real-time basis. It is yet another objective and feature of the present disclosure to provide the system which incorporates use of the machine learning capabilities (for e.g., the NIM) to ensure that only authorized individuals may access the restroom by verifying the target object through image recognition. It is a further objective and feature of the present disclosure to provide the system which incorporates use of the NIM to enable automatic or conditional unlocking of a door lock based on a verified identification result. It is a further objective and feature of the present disclosure to provide the system which enables contactless authentication by eliminating need for physical keys, keycards, or manual input by utilizing a mobile camera for identification. It is a further objective and feature of the present disclosure to provide the system which facilitates seamless payment integration by allowing access to be granted either for free or upon successful payment of a predefined fee. It is a further objective and feature of the present disclosure to provide the system which improves user convenience by providing a fast and user-friendly experience by integrating authentication, payment processing,and door unlocking in a single workflow. Another objective and feature of the present disclosure is to provide the system which enhances process of monitoring and security logging by effectively recording access attempts (for e.g., user access or restroom access), authentication results, and payment transactions to improve security management. Yet another objective and feature of the present disclosure is to provide the system which supports multiple communication protocols to ensure compatibility with various wireless communication methods, such as Bluetooth, Wireless Fidelity (Wi-Fi), or Near Field Communication (NFC), to trigger the unlocking mechanism. Likewise, another object and feature of the present disclosure is to provide the system which backup authentication mechanisms such as Personal Identification Number (PIN) codes or biometric verification, in an event of image recognition failure. Further objects and features of the present disclosure will become apparent from a consideration of the drawings and ensuing description.SUMMARY OF THE INVENTION

[0006] According to one aspect of an embodiment, a system may be provided for smart restroom access with device authentication and payment integration to perform a set of operations which may include receiving, from a user device, a user input associated with a target object. The user input may be indicative of an image of the target object. The set of operations may further include preparing a prompt based on the user input. The set of operations may further include identifying the target object as an identification result based on application of a neural image model (NIM) on the prompt. The set of operations may further include determining whether the target object corresponds to the restroom. The set of operations may further include selectively unlocking the locking mechanism associated with the restroom as a positive identification result, or unlocking the locking mechanism after receiving confirmation of a payment transaction corresponding to the payment code display, in response to determination of the target object corresponding to the restroom as a positive identification result. The set of operations may further include transmitting a control signal to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition.

[0007] According to another aspect of the embodiment, a method for smart restroom access with device authentication and payment integration may include the set of operations which may include receiving, from the user device, the user input associated with the target object. The userinput may be indicative of the image of the target object. The set of operations may further include preparing a prompt based on the user input. The set of operations may further include identifying the target object as an identification result based on the application of the NIM on the prompt. The set of operations may further include determining whether the target object corresponds to the restroom. The set of operations may further include selectively unlocking the locking mechanism associated with the restroom as the positive identification result, or unlocking the locking mechanism after receiving the confirmation of the payment transaction corresponding to the payment code display, in response to the determination of the target object corresponding to the restroom as the positive identification result. The set of operations may further include transmitting the control signal to the locking mechanism to grant the restroom access to the user upon satisfying the unlocking condition.

[0008] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. The objects and advantages of the embodiments will be realized and achieved at least by the elements, features, and combinations particularly pointed out in the claims.

[0009] Both the foregoing general description and the following detailed description are given as examples and are explanatory and are not restrictive of the disclosure, as claimed.BRIEF DESCRIPTION OF THE FIGURES

[0010] The inventive concepts are illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the various figures. Example embodiments will be described and explained with additional specificity and detail through the use of accompanying drawings, in which:

[0011] FIG. 1 is a diagram representing an exemplary network environment related to smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure.

[0012] FIG. 2 is a block diagram that illustrates an exemplary user device of FIG. 1 for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure.

[0013] FIG. 3 is a diagram that illustrates an exemplary execution pipeline for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure.

[0014] FIGs. 4A-4D are diagrams that collectively illustrate exemplary scenario for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure;.

[0015] FIG. 5 is a flowchart that illustrates an exemplary processing pipeline for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure; and

[0016] FIG. 6 is a flowchart that illustrates exemplary operations for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure.DETAILED DESCRIPTION

[0017] Some embodiments described in the present disclosure may relate to methods and systems for smart restroom access with device authentication and payment integration. In the present disclosure, a user input associated with a target object may be received. The user input may be indicative of an image of the target object. A prompt may be prepared based on the user input. Further, based on application of a neural image model (NIM) on the prompt, the target object may be identified as an identification result. Thereafter, it may be determined whether the target object corresponds to the restroom. In response to the determination of the target object corresponding to the restroom as a positive identification result, a locking mechanism associated with a restroom door may be automatically unlocked in a selective way if access to the restroom door is free, or the locking mechanism may be unlocked after receiving confirmation of a payment transaction corresponding to a payment code display. A control signal may be transmitted to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition. The payment code display may correspond to a digital wallet, a credit card, a near field communication (NFC), cryptocurrency, or application-based payment platform.

[0018] The technological field of smart restroom access may be improved by configuring a system to train the neural image model on user data (for example, the user input), user access data and restroom usage data. The system may receive, from a user device, the user inputassociated with the target object. The system may prepare the prompt based on the user input. The system may identify the target object as the identification result based on the application of the NIM on the prompt. The NIM may be trained on the user input, the user access data, and the restroom usage data. The system may determine whether the target object corresponds to the restroom. Thereafter, in response to the determination of the target object corresponding to the restroom as the positive identification result, the system may selectively unlock the locking mechanism associated with the restroom door automatically if access to the restroom door is free, or unlock the locking mechanism after receiving confirmation of the payment transaction corresponding to the payment code display. The system may transmit the control signal to the locking mechanism to grant access to the user upon satisfying the unlocking condition.

[0019] The disclosed approach may offer several advantages. Determination of restroom access eligibility based on the verification of user access data and restroom data may be achieved using techniques like image-based identification technique. Due to successful verification of the user access data and the restroom data, the image of a target object (for example, the restroom) may be captured and processed to determine the restroom access eligibility. Dual access modes associated with the restroom may be provided using techniques like user verification and authentication. For example, both free access and paid access to the restroom may be provided to the user or multiple users based on authentication result associated with multiple users. Effective identification of the restroom as the target object may be achieved using the machine learning (ML) technique. For example, a prompt may be prepared based on the user input (for example, an image of the target object) and a neural image model (NFM) may be applied on the prompt to determine the identification result. Image identification accuracy associated with the target object may be enhanced based on artificial intelligence (Al) or ML algorithms using techniques like Al-powered image recognition techniques. Successful recording and monitoring of each attempt to access the restroom and storing of the user access data and the restroom data may be achieved using techniques like access logging and monitoring techniques. Effective detection of unauthorized access on a real-time basis may be achieved by generating notifications and alerts related to unauthorized access by the user / (s) using techniques like real-time notifications and alerts generation technique. The proposed technique involves successful user authentication using alternative methods like such as a Personal Identification (PIN) code, facial recognition, or fingerprint scanning in case of failure of image identification, using backuppayment mechanisms. The proposed technique completely eliminates need for physical keys, cards, or keypads to provide a completely touch-free experience. This reduces risk of spreading germs, which is especially valuable in public restrooms. Further, the proposed technique may utilize wireless technologies like Bluetooth, Wireless Fidelity (Wi-Fi), or Near Field Communication (NFC) to transmit signals to the door lock, ensuring smooth integration with various environments. Further, the proposed technique may provide very useful insights into peak usage times and potential maintenance needs, thereby enhancing operational efficiency associated with the restroom. Further, the proposed technique may eliminate need for human oversight at entrance of the restroom to provide the user a more private and autonomous experience. Additionally, this approach may be used across diverse applications such as office restrooms, paid public facilities, hotel rooms, or private event spaces, and also may integrate with existing infrastructure like hotel management systems or corporate access control.

[0020] Embodiments of the present disclosure are explained with reference to the accompanying drawings.

[0021] FIG. 1 is a block diagram that illustrates an example network environment related to smart restroom access with device authentication and payment integration, arranged in accordance with at least one embodiment described in the present disclosure. With reference to FIG. 1, there is shown an environment 100. The environment 100 may include a system 102, a user device 104, a server 106, a database 108, a neural image model (NIM) 120, a restroom 122, and a communication network 130. Further, the system 102 may be communicatively coupled to the server 106, via the communication network 130. The environment 100 may further include a restroom door 124 having a locking mechanism 126 and a payment code display 128. In FIG. 1, there is further shown a user 110 associated with the user device 104. There may be further shown a user input 112 associated with a target object 118 that may be stored in the database 108. The target object 118 may be identified as an identification result 116.

[0022] The user device 104 may be an electronic device used by the user 110 to capture an image of the target object 118. The user device 104 or the system 102 may further include suitable logic, circuitry, interfaces, and / or code that may be configured to receive the user input 112 associated with the target object 118. The user input 112 may be indicative of the image of the target object 118. The user device 104 may further prepare a prompt 114 based on the user input 112. The user device 104 may further identify the target object 118 as the identification result 116 based onapplication of the NIM 120 on the prompt 114. The user device 104 may further determine whether the target object 118 corresponds to the restroom 122 based on the identification result 116. The user device 104 may further selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free, in response to the determination that the target object 118 corresponds to the restroom 122 as a positive identification result. The user device 104 may further optionally unlock the locking mechanism 126 after receiving confirmation of a payment transaction corresponding to the payment code display 128, in response to the determination that the target object 118 corresponds to the restroom 122 as the positive identification result. The user device 104 may further transmit a control signal to the locking mechanism 126 to grant restroom access to the user 110 upon satisfying the unlocking condition. Examples of the system 102 or the user device 104 may include, but are not limited to, a computing device, a smartphone, a cellular phone, a mobile phone, a mainframe machine, a server, a computer workstation, a machine learning device (enabled with or hosting, for example, a computing resource, a memory resource, and a networking resource), and / or a consumer electronic (CE) device.

[0023] In an embodiment, the user device 104 may retrieve a prompt template (shown in FIG.4B) that includes a base instruction and context associated with the user input 112. Further, the user device 104 may extract, from the user input 112, target object information comprising at least one of a Quick Response (QR) code, a barcode, or a machine-readable identifier associated with the restroom 122. Further, the user device 104 may update the prompt template to include the target object information as the context. Further, the user device 104 may modify the base instruction in the updated prompt template to prepare the prompt 114.

[0024] In an embodiment, the user device 104 may capture a second image of the target object 118 in response to the determination that the target object 118 corresponds to the restroom 122 as a negative identification result. Further, the user device 104 may verify user access based on the captured second image. Further, the user device 104 may transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110, based on the verification of the user access.

[0025] In an embodiment, the user device 104 may control a display device (e.g., a display device 206A of FIG. 2). The display device 206A may be communicatively coupled to the system 102 and the user device 104 or may be a standalone device configured to render the user input 112 orthe identification result 116 associated with the target object 118. The display device 206A may be further configured to render the target object 118 (for example, the restroom 122) as the identification result 116. The user device 104 may further control the display device 206A to display a backup authentication mechanism for the restroom access, in an event of unsuccessful verification of the user access based on the captured second image. The backup authentication mechanism may correspond to, but not limited to, a personal identification (PIN) number or a biometric scan.

[0026] In one or more embodiments, the user device 104 may be configured to generate an alert to a proprietor in an event of unauthorized access. The user device 104 may further determine a predetermined number of users associated with the restroom usage. In an event of number of users associated with the restroom usage exceeding the predetermined number of users, the user device 104 may further send an alert notification to the proprietor for restroom cleaning based on the determination.

[0027] In some embodiments, the user device 104 may further store logs associated the user access to monitor the restroom usage. The user device 104 may further generate a report associated with the restroom usage for the proprietor.

[0028] The server 106 may include suitable logic, circuitry, and interfaces, and / or code that may be configured to receive, from the user device 104, the user input 112 associated with the target object 118. The user input 112 may be indicative of the image of the target object 118. The server 106 may further prepare the prompt 114 based on the user input 112. Thereafter, the server 106 may identify the target object 118 as the identification result 116 based on the application of the neural image model 120 on the prompt 114. The server 106 may further determine whether the target object 118 corresponds to the restroom 122. The server 106 may further in response to determination of the target object 118 corresponding to the restroom 122 as the positive identification result, selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free. Optionally, the server 106 may unlock the locking mechanism 126 after receiving confirmation of the payment transaction corresponding to the payment code display 128. The server 106 may further transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition.

[0029] The server 106 may be implemented as a cloud server and may execute operations through web applications, cloud applications, Hypertext transfer protocol (HTTP) requests, repository operations, file transfer, and the like. Other example implementations of the server 106 may include, but are not limited to, a database server, a file server, a web server, a media server, a mainframe server, a machine learning server (enabled with or hosting, for example, a computing resource, a memory resource, and a networking resource), or a cloud computing server.

[0030] In at least one embodiment, the server 106 may be implemented as a plurality of distributed cloud-based resources by use of several technologies that are well known to those ordinary skilled in the art. A person with ordinary skill in the art will understand that the scope of the disclosure may not be limited to the implementation of the server 106 and the user device 104 or the system 102, as two separate entities. In certain embodiments, the functionalities of the server 106 can be incorporated in its entirety or at least partially in the system 102 or the user device 104 without a departure from the scope of the disclosure. In certain embodiments, the server 106 may host the database 108. Alternatively, the server 106 may be separate from the database 108 and may be communicatively coupled to the database 108.

[0031] The database 108 may include suitable logic, interfaces, and / or code that may be configured to store the user input 112 associated with the target object 118. The database 108 may further store the image of the target object 118. The database 108 may further store the target object 118 identified as the identification result 116. The database 108 may further store user access data associated with the restroom 122. The database 108 may further store restroom usage data and restroom access data associated with the user 110. The database 108 may be derived from data of a relational or non-relational database, or a set of comma-separated values (csv) files in conventional or big-data storage. The database 108 may be stored or cached on a device, such as a server (e.g., the server 106) of the user device 104. The device storing the database 108 may be configured to receive a query for the user input 112 from the user device 104 or the server 106. In response, the device of the database 108 may be configured to retrieve and provide the queried user input 112 to the user device 104 or the server 106, based on the received query.

[0032] In some embodiments, the database 108 may be hosted on a plurality of servers stored at the same or different locations. The operations of the database 108 may be executed using hardware including a processor, a microprocessor (e.g., to perform or control performance of one or more operations), a field-programmable gate array (FPGA), or an application-specificintegrated circuit (ASIC). In some other instances, the database 108 may be implemented using software.

[0033] A person with ordinary skill in the art will understand that the scope of the disclosure may not be limited to the implementation of the server (or the user device 104) and the database 108 as two separate entities. In certain embodiments, the functionalities of the database 108 can be incorporated in its entirety or at least partially in the server 106 or the user device 104, without a departure from the scope of the disclosure.

[0034] The prompt 114 may be an input in form of a natural language text to instruct an artificial intelligence (Al) model (for example, the neural image model 120) to perform a specific task and generate a desired output. The prompt 114 may serve as a starting point for operation of the Al model to provide the context and instructions for generating a response. For example, a well-crafted prompt may clearly define the task the Al model should perform, like generating text, answering questions, translating languages, or creating images. The prompt 114 may be a classified as different types of prompts. These different types of prompts may be supported by only a particular Al model. For example, while the prompt 114 as text prompts are common, some of Al models may support non-text prompts, such as images or audio, depending on capabilities of the particular Al model for analyzing a particular type of prompt (for example, different modalities like the text, the images, or the audio).

[0035] In one or more embodiments, the prompt 114 may be prepared based on the user input 112. For example, the prompt 114 may be prepared based on the user input 112 associated with the target object 118. Further, the prompt 114 may be prepared based on the image of the target object 118.

[0036] The neural image model (NIM) 118 may be a language model that include suitable logic, circuitry, interfaces, and / or code configured to be applied on the prompt 114 to identify the target obj ect 118 as the identification result 116. The NIM 120 may receive the user input 112 associated with the target object 118. The NIM 120 may further analyze the prepared prompt 114 based on the user input 112. The NIM 120 may further identify the target object 118 as the identification result 116, based on application of the NIM 120 on the prompt 114. The NIM 120 may further determine whether the target object 118 corresponds to the restroom 122. In response to the determination that the target object 118 corresponds to the restroom 122 as a positive identification result, the NIM 120 may selectively unlock the locking mechanism 126 associatedwith the restroom door 124 automatically if access to the restroom door 124 is free. Further, in response to the determination of the target object 118 corresponding to the restroom 122 as the positive identification result, the NIM 120 may unlock the locking mechanism 126 after receiving confirmation of the payment transaction corresponding to the payment code display 128. The NIM 120 may further transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition.

[0037] The NIM 120 may be trained on vast amounts of textual descriptions and images, enabling the NIM 120 to perform a wide range of natural language processing tasks, such as translation, summarization, image generation, and text generation. The NIM 120 may analyze the user input 112 (for example, image) associated with the target object 118 and a textual description defining the activity (for example, granting the restroom access to the user 110) associated with the user input 112. The NIM 120 may be trained on a large dataset of question-answer pairs or images to interpret human language, or other types of complex data. In certain instances, the dataset may be particular to the user input 112, the target object 118, the user access data, or the restroom access data.

[0038] In an embodiment, the NIM 120 may be type of an artificial intelligence (Al) system (also referred to as an artificial deep neural network) configured to process and understand multiple types of data modalities, such as text, images, audio, 3D data, and video, simultaneously. The NIM 120 may extend the capabilities of traditional large language models (LLMs) by integrating various forms of data, enabling a more comprehensive understanding and generation of information across different media types. In some embodiments, the NIM 120 may be a large language model, such as a transformer-based decoder-only model, an encoder-decoder model that uses transformers), or a model that uses neural networks other than transformers. In these or other embodiments, the NIM 120 may include multiple encoders specialized for processing different modalities of data (such as image and text). The NIM 120 may include a fusion mechanism to integrate outputs from various encoders.

[0039] Techniques like cross-attention mechanisms or multimodal transformers may be used to combine the different data types (such as text and image of a prompt) into a unified representation. In some embodiments, the NIM 120 may include decoders to generate outputs in various modalities. For example, a text decoder generates textual responses, while an image encoder may create visual content. During training, the NIM 120 may use large-scale datasetsthat include paired data from multiple modalities (e.g., image-caption pairs, video with subtitles). The training may involve techniques like supervised learning, reinforcement learning with human feedback (RLHF), and fine-tuning to ensure that the model performs well across different tasks. For applications like text generation and image understanding or video understanding, the NIM 120 may include specialized heads that may be fine-tuned for specific tasks.

[0040] The NIM 120 may correspond to at least one of a convolutional neural network (CNN) model, Generative Adversarial Network (GAN), a Multilayer Perceptron (MLP), or a Large Language Models (LLMs).

[0041] As an artificial deep neural network, the NIM 120 may be referred to as a computational network or a system of artificial neurons, arranged in a plurality of layers, as nodes that may be configured to receive the user input 112 associated with the target object 118. The plurality of layers of the neural network may include an input layer, one or more hidden layers, and an output layer. Each layer of the plurality of layers may include one or more nodes (or artificial neurons, represented by circles, for example). Outputs of all nodes in the input layer may be coupled to at least one node of hidden layer(s). Similarly, inputs of each hidden layer may be coupled to outputs of at least one node in other layers of the neural network. Outputs of each hidden layer may be coupled to inputs of at least one node in other layers of the neural network. Node(s) in the final layer may receive inputs from at least one hidden layer to output a result. The number of layers and the number of nodes in each layer may be determined from hyper-parameters of the neural network. Such hyper-parameters may be set before, while training, or after training the neural network on a training dataset.

[0042] Each node of the NIM 120 may correspond to a variable function (e.g., a sigmoid function or a rectified linear unit) with a set of parameters, tunable during training of the network. The set of parameters may include, for example, a weight parameter, a regularization parameter, and the like. Each node may use the variable function to compute an output based on one or more inputs from nodes in other layer(s) (e.g., previous layer(s)) of the neural network. All or some of the nodes of the neural network may correspond to same or a different variable function.

[0043] In training of the NIM 120, one or more parameters of each node of the neural network may be updated based on whether an output of the final layer for a given input (from the training dataset) matches a correct result based on a loss function for the neural network. The above process may be repeated for same or a different input until minima of loss function may beachieved and a training error may be minimized. Several methods for training are known in art, for example, gradient descent, stochastic gradient descent, batch gradient descent, gradient boost, meta-heuristics, and the like.

[0044] The NIM 120 may include electronic data, which may be implemented as, for example, a software component of an application executable on the system 102 or the user device 104. The NIM 120 may rely on libraries, external scripts, or other logic / instructions for execution by a processing device. The NIM 120 may include code and routines configured to enable a computing device to perform one or more operations. Additionally, or alternatively, the NIM 120 may be implemented using hardware including a processor, a microprocessor (e.g., to perform or control performance of one or more operations), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). Alternatively, in some embodiments, the neural network may be implemented using a combination of hardware and software.

[0045] In an embodiment, the NIM 120 may be a scalable deep-leaming model comprising an encoder model, a decoder model, and a set of convolution neural network layers. The NIM 118 may correspond to at least one of the CNN model or a Deep Reinforcement Learning model. The deep reinforcement learning model or scalable deep-learning model may take un-processed dataset such as, an unprocessed user input indicative of the image of the target object 118. The encoder model of the present disclosure may receive the user input 112 indicative of the image of the target object 118. The decoder model may identify the target object 118 as the identification result 116 based on the application of the decoder model on the prompt 114 associated with the user input 112. The NIM 120 may be trained based on the user input 112, and configured to automatically identify the target object 118 as the identification result 116, based on application of the NIM 120 on the prompt 114. Further, based on the application of the NIM 120 to automatically identify the target object 118, the encoder model may determine a compressed feature vector associated with the image of the target object 118. An encoded version (i.e., the compressed feature vector) of the received image of the target object 118 may be transmitted to the decoder model. The decoder model may reconstruct an input dataset such as, an image dataset back from the encoded version. Thus, the decoder model may decompress the compressed feature vector associated with the image dataset. Each of the set of convolution neural network layers may perform a dot product between two matrices. Herein, a first matrix also known as a kernel, may include a set of learnable parameters and a second matrix may be a portion of a receptivefield associated with the corresponding convolution neural network layer. In an embodiment, a kernel size associated with each of the set of convolution neural network layers may be even. That is, the kernel size may be “2”, “4”, “6”, “8”, and so on.

[0046] In an embodiment, the scalable deep-learning model may be a deep learning machine learning (ML) model or the NIM 120. The NIM 120 may be trained to identify a relationship between inputs, such as, features in the image dataset, and output labels, such as, the user input 112. The NIM 120 may be defined by its hyper- parameters, for example, number of weights, cost function, input size, number of layers, and the like. The parameters of the NIM 120 may be tuned and weights may be updated so as to move towards global minima of a cost function for the NIM 120. After several epochs of the training on the user input 112, the user access data, and the restroom access data in the training dataset, the NIM 120 may be trained to output, through the user device 104, the control signal to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition.

[0047] The NIM 120 may include electronic data, which may be implemented as, for example, a software component of an application executable on the user device 104. The NIM 120 may rely on libraries, external scripts, or other logic / instructions for execution by a processing device. The NIM 120 may include code and routines configured to enable a computing device, such as the user device 104 to perform one or more operations such as, the reception of the user input 112, the preparation of the prompt 114, the identification of the target object 118, the determination of the target object 118 as the restroom 122, the selective unlocking of the locking mechanism 126 or the general unlocking of the locking mechanism 126, and the transmission of the control signal to grant the restroom access to the user 110. Additionally, or alternatively, the NIM 120 may be implemented using hardware including a processor, a microprocessor (e.g., to perform or control performance of one or more operations), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). Alternatively, in some embodiments, the neural network may be implemented using a combination of hardware and software.

[0048] The payment code display 128 may refer to payment information window displayed to allow the user 110 to scan and initiate a payment transaction using the user device 104. For example, the payment code display 128 may corresponds to a digital wallet, a credit card, a near field communication (NFC), cryptocurrency, or application-based platforms.

[0049] The communication network 130 may include various communication media through which the system 102 or the user device 104 and the server 106 may communicate with one another. The communication network 130 may be one of a wired connection or a wireless connection. Examples of the communication network 130 may include, but are not limited to, the Internet, a cloud network, Cellular or Wireless Mobile Network (such as Long-Term Evolution and 5thGeneration (5G) New Radio (NR)), satellite communication system (using, for example, low earth orbit satellites), a Wireless Fidelity (Wi-Fi) network, a Personal Area Network (PAN), a Local Area Network (LAN), or a Metropolitan Area Network (MAN). Various devices in the network environment 100 may be configured to connect to the communication network 130 in accordance with various wired and wireless communication protocols. Examples of such wired and wireless communication protocols may include, but not limited to, at least one of a Transmission Control Protocol and Internet Protocol (TCP / IP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Zig Bee, EDGE, IEEE 802.11, Light Fidelity (Li-Fi), 802.16, IEEE 802.11g, multi-hop communication, wireless access point (AP), device to device communication, cellular communication protocols, and Bluetooth (BT) communication protocols.

[0050] In operation, the system 102 may be configured to receive the user input 112 associated with the target object 118. The user input 110 may be indicative of the image of the target object 118. The reception of the user input 112 associated with the target object 118 is described further, for example, with reference to FIG. 3, FIG. 4A, and FIG. 5.

[0051] The system 102 may be configured to prepare the prompt 114 based on the user input 112. The prompt 114 may be an input in form of a natural language text to instruct an artificial intelligence (Al) model (for example, the NIM 120) to perform a specific task and generate a desired output. The preparation of the prompt 114 is described further, for example, with reference to FIG. 3, FIG. 4B, and FIG. 5.

[0052] The system 102 may be configured to identify the target object 118 as the identification result 116 based on application of the NIM 120 on the prompt 114. The NIM 120 may corresponds to the CNN model, the GAN, the MLP, or the LLMs. The identification of the target object 118 is described further, for example, with reference to FIG. 3, FIG. 4C, and FIG. 5.

[0053] The system 102 may be configured to determine whether the target object 118 corresponds to the restroom 122. The determination of whether the target object 118 correspondsto the restroom 122 is described further, for example, with reference to FIG. 3, FIG. 4C, and FIG.5.

[0054] The system 102 may be configured to selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free, in response to the determination that the target object 118 corresponds to the restroom 122 as the positive identification result. The system 102 may be further configured to unlock the locking mechanism 126 after receiving confirmation of the payment transaction corresponding to the payment code display 128. The unlocking of the locking mechanism 126 associated with the restroom door 124 is described further, for example, with reference to FIG. 3, FIG. 4D, and FIG.5.

[0055] The system 102 may be configured to transmit the control signal to the locking mechanism 126 to grant the restroom access to the user upon satisfying the unlocking condition. The transmission of the control signal to the locking mechanism 126 is described further, for example, with reference to FIG. 3 and FIG. 4D.

[0056] Modifications, additions, or omissions may be made to FIG. 1 without departing from the scope of the present disclosure. For example, the environment 100 may include more or fewer elements than those illustrated and described in the present disclosure. For instance, in some embodiments, the environment 100 may include the system 102 or the user device 104, but not the database 108. In addition, in some embodiments, the functionality of each of the database 108 may be incorporated into the system 102 or the user device 104, without a deviation from the scope of the disclosure.

[0057] FIG. 2 is a block diagram that illustrates an exemplary user device of FIG. 1 for smart restroom access with device authentication and payment integration, in accordance with at least one embodiment described in the present disclosure. FIG. 2 is explained in conjunction with elements from FIG. 1. With reference to FIG. 2, there is shown a block diagram 200 of the user device 104. The user device 104 may include a memory 202, the NIM 120, a circuitry 204, an input / output (VO) device 206, and a network interface 208. The VO device 206 may include a display device 206A. The memory 202 may include the user input 112 associated with the target object 118. The memory 202 may store the dataset associated with the image of the target object 118. The memory 202 may further store the target object 118 identified as the identification result 116. The memory 202 may further store user access data associated with the restroom 122. Thememory 202 may further store restroom usage data and restroom access data associated with the user 110.

[0058] The memory 202 may include suitable logic, circuitry, interfaces, and / or code that may be configured to store one or more instructions to be executed by the circuitry 204. The one or more instructions stored in the memory 202 may be configured to execute the different operations of the circuitry 204 (and / or the user device 104). Examples of implementation of the memory 202 may include, but are not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Hard Disk Drive (HDD), a Solid-State Drive (SSD), a CPU cache, and / or a Secure Digital (SD) card.

[0059] The circuitry 204 may include suitable logic, circuitry, and / or interfaces that may be configured to execute program instructions associated with different operations to be executed by the user device 104. The operations may include, but not limited to, the reception of the user input 112, the preparation of the prompt 114, the identification of the target object 118, the determination of the target object 118 as the restroom 122, the selective unlocking of the locking mechanism 126 or the general unlocking of the locking mechanism 126, and the transmission of the control signal to grant the restroom access to the user 110. The circuitry 204 may include any suitable special-purpose or general-purpose computer, computing entity, or processing device, including various computer hardware or software modules, and may be configured to execute instructions stored on any applicable computer-readable storage media. For example, the processing circuitry 204 may include a microprocessor, a microcontroller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a Field-Programmable Gate Array (FPGA), or any other digital or analog circuitry configured to interpret and / or to execute program instructions and / or to process data.

[0060] Although illustrated as a single processor in FIG. 2, the circuitry 204 may include any number of processors configured to, individually or collectively, perform or direct performance of any number of operations of the user device 104, as described in the present disclosure. Additionally, one or more processors may be present on one or more different loT devices, such as different servers.

[0061] In some embodiments, the circuitry 204 may be configured to interpret and / or execute program instructions and / or process data stored in the memory 202. The processing circuitry 204 may include one or more processing units, which may be implemented as a separate processor.The one or more processing units may be implemented as an integrated processor or a cluster of processors that perform the functions of the one or more specialized processing units, collectively. In some embodiments, the circuitry 204 may fetch program instructions from the NIM 120 and load the program instructions in the memory 204. After the program instructions are loaded into the memory 202, the circuitry 204 may execute the program instructions. The circuitry 204 may be implemented based on a number of processor technologies known in the art. Examples of implementations of the processing circuitry 204 may be an X86-based processor, a Graphics Processing Unit (GPU), a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, an Application-Specific Integrated Circuit (ASIC) processor, a Complex Instruction Set Computing (CISC) processor, a co-processor, a microcontroller, a control circuit, and / or a combination thereof.

[0062] The VO device 206 may include suitable logic, circuitry, interfaces, and / or code that may be configured to receive the user input 112 associated with the target object 118. For example, the VO device 206 may receive the image of the target object 118 as the user input 112. The VO device 206 may be further configured to provide an output in response to the reception of the user input 112. For example, the output may correspond to the permissions granted to the user 110 for the restroom access based on the user input 112 (for example, the image of the target object 118) and the prompt 114 (for example, the textual description) analyzed to identify the target object 118 as the restroom 122. The I / O device 206 may include various input and output devices, which may be configured to communicate with the circuitry 204 and other components, such as the network interface 208. The I / O device 206 may further include the display device 206A. Examples of the VO device 206 may include, but are not limited to, a display (e.g., a touch screen), a keyboard, a mouse, a joystick, a microphone, or a speaker. The I / O device 206 may be within the user device 104 or outside of the user device 104.

[0063] The display device 206A may include suitable logic, circuitry, interfaces, and / or code that may be configured to display the user input 112 associated with the target object 118, the target object 118 identified as the identification result 116, the user access data associated with the restroom 122, the restroom usage data, and the restroom access data. The display device 206 A may be a touch screen which may enable the user (e.g., the at least one user trying to access the restroom 122) to provide user-inputs via the display device 206A. The touch screen may be at least one of a resistive touch screen, a capacitive touch screen, or a thermal touch screen. Thedisplay device 206A may be realized through several known technologies such as, but not limited to, at least one of a Liquid Crystal Display (LCD) display, a Light Emitting Diode (LED) display, a plasma display, or an Organic LED (OLED) display technology, or other display devices. In accordance with an embodiment, the display device 206A may refer to a display screen of a head mounted device (HMD), a smart-glass device, a see-through display, a projection-based display, an electro-chromic display, or a transparent display.

[0064] The network interface 208 may include suitable logic, circuitry, interfaces, and / or code that may be configured to facilitate communication between the circuitry 204 (i.e., the user device 104) and the server 106, via the communication network 130. The network interface 208 may be implemented by use of various known technologies to support wired or wireless communication of the user device 104 with the communication network 130. The network interface 208 may include, but is not limited to, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, or a local buffer circuitry.

[0065] The network interface 208 may be configured to communicate via wireless communication with networks, such as the Internet, an Intranet, or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and a metropolitan area network (MAN). The wireless communication may be configured to use one or more of a plurality of communication standards, protocols and technologies, such as Global System for Mobile Communication (GSM), Enhanced Data GSM Environment (EDGE), wideband code division multiple access (W-CDMA), Long Term Evolution (LTE), 5thGeneration (5G) New Radio (NR), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wireless Fidelity (Wi-Fi) (such as IEEE 802.11a, IEEE 802.11b, IEEE 802.11g or IEEE 802.1 In), voice over Internet Protocol (VoIP), light fidelity (Li-Fi), Worldwide Interoperability for Microwave Access (Wi-MAX), a protocol for email, instant messaging, and a Short Message Service (SMS).

[0066] In certain embodiments, the user device 104 may be divided into a front-end subsystem and a backend subsystem. The front-end subsystem may be solely configured to receive requests / instructions from a user device (for example, the user device 104), one or more of third-party servers, web servers, client machine, and the backend subsystem. These requests may be communicated back to the backend subsystem, which may be configured to act upon thesesrequests. For example, in case the user device 104 is in communication with multiple servers, few of the servers may be front-end servers configured to relay the requests / instructions to remaining servers associated with the backend subsystem.

[0067] Modifications, additions, or omissions may be made to the example user device 104 without departing from the scope of the present disclosure. For example, in some embodiments, the example user device 104 may include any number of other components that may not be explicitly illustrated or described for the sake of brevity.

[0068] FIG. 3 is a diagram that illustrates an exemplary execution pipeline for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure. FIG. 3 is explained in conjunction with elements from FIG. 1 and FIG. 2. With reference to FIG. 3, there is shown an exemplary processing pipeline 300. The execution pipeline 300 may include a sequence of operations that may be executed by the circuitry 204 of the user device 104 of FIG. 1 for smart access to the restroom by utilizing device authentication and payment integration capabilities of the system 102.

[0069] The execution pipeline 300 includes an operation for user input reception, an operation for prompt preparation, an operation for target object identification, an operation for target object determination, an operation for locking mechanism unlocking, and an operation for control signal transmission. Though only the operations associated with the user input 112 and the target object 118 is shown in FIG. 3, the scope of the disclosure may not be so limited. There may be operations associated with other data inputs received or identified by the circuitry 204, without departure from the scope of the disclosure.

[0070] At 302, an operation for user input reception may be executed. The circuitry 204 may be configured to receive a user input 302A associated with the target object 118. In one or more embodiments, the circuitry 204 may be configured to receive the user input 302A indicative of the image of the target object 118. Herein, the user input 302A may include, but not limited to, a text, a 2D image, or a 3D video representation. An exemplary implementation of the system 102 for receiving the user input 302A associated with the target object 118 is provided, for example, in FIG. 4 A and FIG. 5.

[0071] At 304, an operation for prompt preparation may be executed. The circuitry 204 may be configured to prepare the prompt 114 based on the user input 302A. The prompt 114 may be an input in form of a natural language text to instruct the NIM 120 to perform a specific task andgenerate a desired output. The prompt 114 may serve as a starting point for operation of the NIM 120 to provide the context and instructions for generating a response. An exemplary implementation of the system 102 for preparation of the prompt 114 is provided, for example, in FIG. 4B and FIG. 5.

[0072] In an instance, the circuitry 204 may be configured to retrieve a prompt template (shown in FIG. 4B) that includes a base instruction and a context associated with the user input 302A. The circuitry 204 may be further configured to extract, from the user input 302A, target object information corresponding to the image of the target object. For example, the target object information may comprise at least one of a Quick Response (QR) code, a barcode, or a machine-readable identifier associated with the restroom access. The circuitry 204 may be further configured to update the prompt template to include the target object information as the context. The circuitry 204 may be further configured to modify the base instruction in the updated prompt template to prepare the prompt 114.

[0073] At 306, an operation for target object identification may be executed. The circuitry 204 may be configured to identify the target object 118 as the identification result 116 based on the application of the NIM 120 on the prompt 114. Herein, the NIM 120 may correspond to at least one of the Convolutional Neural Network (CNN) Model, the Generative Adversarial Network (GAN), or the Multilayer Perceptron (MLP). An exemplary implementation of the system 100 for the identification of the target object 118 is provided, for example, in FIG. 4C and FIG. 5.

[0074] At 308, an operation for target object determination may be executed. The circuitry 204 may be configured to determine a target object 308A as the restroom 122. For example, the circuitry 204 may determine whether the target object 308 A corresponds to the restroom 122. In one embodiment, the circuitry 204 may be configured to determine whether the target object 308A corresponds to the restroom 122 as the positive identification result or the negative identification result. An exemplary implementation of an electronic UI for the determination of the target object 308 A as the restroom 122 is provided, for example, at FIG. 4C and FIG. 5.

[0075] At 310, an operation for locking mechanism unlocking may be executed. The circuitry 204 may be configured to selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free, in response to the determination of the target object 308 A corresponding to the restroom 122 as the positive identification result. Further, the circuitry 204 may be configured to unlock the locking1mechanism 126 after receiving the confirmation of the payment transaction corresponding to the payment code display 128, in response to the determination of the target object 308 A corresponding to the restroom 122 as the positive identification result. Herein, the payment code display 128 may corresponds to at least one of a digital wallet, a credit card, a near field communication, cryptocurrency, or application-based payment platforms. An exemplary implementation of the electronic UI for unlocking of the locking mechanism is provided, for example, at FIG. 4C and FIG. 5.

[0076] In a first instance, the circuitry 204 may be further configured to capture, from the user device 102, a second image of the target object 308A, in response to the determination of the target object 308 A corresponding to the restroom 122 as the negative identification result. The circuitry 204 may be further configured to verify user access based on the captured second image. The circuitry 204 may be further configured to transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110, based on the verification of the user access. The circuitry 204 may be further configured to control the display device 206A to display a backup authentication mechanism for the restroom access, in an event of unsuccessful verification of the user access based on the captured second image. The backup authentication mechanism may correspond to a personal identification number (PIN) or a biometric scan. The circuitry 204 may be further configured to generate an alert message in an event of unauthorized user access.

[0077] In a second instance, the circuitry 204 may be further configured to store logs associated with the user access to monitor restroom usage. The circuitry 204 may be further configured to generate a report associated with the restroom usage for a proprietor. The circuitry 204 may be further configured to estimate a predetermined number of users associated with the restroom usage. The circuitry 204 may be further configured to send a notification to the proprietor for restroom cleaning, based on a determination that number of users associated with the restroom usage exceeds the predetermined number of users.

[0078] At 312, an operation for control signal transmission may be executed. The circuitry 204 may be configured to transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition. Herein, the approach for transmission of the control signal to the locking mechanism 126 to grant the restroom access to the user 110 may corresponds to a protocol-based communication technique or approach.

[0079] The disclosed approach may offer several advantages. Determination of restroom access eligibility based on the verification of user access data and restroom data may be achieved using techniques like image-based identification technique. Due to successful verification of the user access data and the restroom data, the image of a target object (for example, the restroom) may be captured and processed to determine the restroom access eligibility. Dual access modes associated with the restroom may be provided using techniques like user verification and authentication. For example, both free access and paid access to the restroom may be provided to the user or multiple users based on authentication result associated with multiple users. Effective identification of the restroom as the target object may be achieved using the machine learning (ML) technique. For example, a prompt may be prepared based on the user input (for example, an image of the target object) and a neural image model (NFM) may be applied on the prompt to determine the identification result. Image identification accuracy associated with the target object may be enhanced based on artificial intelligence (Al) or ML algorithms using techniques like Al-powered image recognition techniques. Successful recording and monitoring of each attempt to access the restroom and storing of the user access data and the restroom data may be achieved using techniques like access logging and monitoring techniques. Effective detection of unauthorized access on a real-time basis may be achieved by generating notifications and alerts related to unauthorized access by the user / (s) using techniques like real-time notifications and alerts generation technique. The proposed technique involves successful user authentication using alternative methods like such as a Personal Identification (PIN) code, facial recognition, or fingerprint scanning in case of failure of image identification, using backup payment mechanisms. The proposed technique completely eliminates need for physical keys, cards, or keypads to provide a completely touch-free experience. This reduces risk of spreading germs, which is especially valuable in public restrooms. Further, the proposed technique may utilize wireless technologies like Bluetooth, Wireless Fidelity (Wi-Fi), or Near Field Communication (NFC) to transmit signals to the door lock, ensuring smooth integration with various environments. Further, the proposed technique may provide very useful insights into peak usage times and potential maintenance needs, thereby enhancing operational efficiency associated with the restroom. Further, the proposed technique may eliminate need for human oversight at entrance of the restroom to provide the user a more private and autonomous experience. Additionally, this approach may be used across diverse applications such as officerestrooms, paid public facilities, hotel rooms, or private event spaces, and also may integrate with existing infrastructure like hotel management systems or corporate access control.

[0080] FIGs. 4A-4D are diagrams that collectively illustrate exemplary scenario for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure. FIGs. 4A-4D are described in conjunction with elements from FIG. 1, FIG. 2, and FIG. 3. With reference to FIG. 4A, there is shown an exemplary scenario 400A for smart restroom access with device authentication and payment integration. The exemplary scenario 400 A may include a user input 402, a target object 404, and a first image 406.

[0081] The circuitry 204 of the user device 104 may be configured to receive the user input 402 associated with the target object 404. The user input 402 may be indicative of the first image 406 of the target object 404. For example, the image of the restroom 122 as the user input 402 may be received. The image of the restroom 122 may be the first image 406. In an embodiment, the restroom 122 may comprise the restroom door 124 having the locking mechanism 126 and the payment code display 128. The locking mechanism may be installed on the restroom door 124. The payment code display 128 may be positioned adjacent to the restroom door 124. Further, the payment code display 128 may correspond to the digital wallet, the credit card, the near field communication (NFC), the cryptocurrency, or the application-based platforms.

[0082] The prompt 114 may be prepared based on the user input 402. For example, the circuitry 204 may be configured to prepare the prompt 114 based on the user input 402. The preparation of the prompt 114 may be described further in FIG. 4B. is described in conjunction with elements from FIG. 1 , FIG. 2, FIG. 3, and FIG. 4A. With reference to FIG. 4B, there is shown an exemplary scenario 400B. The exemplary scenario 400B may include a prompt template 408, a prompt 412, and a target object information 414. In an example, the circuitry 204 may be configured to prepare the prompt 412 based on the user input 402. For example, based on the first image 406 of the restroom as the user input 402, the prompt 412 may be prepared. In one instance, the circuitry 204 may be configured to retrieve the prompt template 408 that includes the base instruction and the context associated with the user input 402. The base instruction and the context information may be inserted in an insert display 410 of the prompt template. The target object information 414 may be extracted from the user input 402. The target object information 414 may correspond to at least one of the QR code, the barcode, or the machine-readable identifier associated with therestroom access. The prompt template 408 may be further updated to include the target object information 414 as the context.

[0083] In another instance, the base instruction may be modified in the updated prompt template 414 to prepare the prompt 412. For example, the base instruction may be modified in the updated prompt template 414 to prepare the prompt 412 by including a text instruction as: “Analyze captured image of a door by identifying symbol, door characteristics, environmental cues, access control indicators, and validation criteria if applicable”. The context may be the target object information 414 associated with the restroom access. For example, the context may be a Wireless Fidelity (Wi-Fi) code as the target object information or an identifier associated with the restroom access.

[0084] The circuitry 204 may be configured to identify the target object 404 as the identification result based on the application of the NIM 120 on the prompt 412. The identification of the target object 404 as the identification result based on the application of the NIM 120 on the prompt 412 may be described further in FIG. 4C. FIG. 4C is described in conjunction with elements from FIG. 1, FIG. 2, FIG. 3, FIG. 4A, and FIG. 4B. With reference to FIG. 4C, there is shown an exemplary scenario 400C. In an example as shown in FIG. 4C, the NIM 120 may be applied on the prompt 412 to identify the target object 404 as either a positive identification result or a negative identification result. Further, the circuitry 204 may be configured to determine whether the target object 404 corresponds to the restroom 122 after the application of the NIM on the prompt 412. The NIM 120 may correspond to the CNN model, the GAN, the MLP, or the LLMs. In an instance, the NIM 120 may analyze the prompt 412 to determine that the target object 404 corresponds to the restroom 122 as the positive identification result. If the identification result 116 is a negative identification result, a determination may be made that the target object 404 does not correspond to the restroom 122.

[0085] Based on the analysis of the prompt 412 by the NIM 120, it may be determined that the target object 404 corresponds to the restroom 122 as a positive identification result 416. The positive identification result 416 may be displayed on the display device 206A of the user device 104. For example, based on the determination that the target object 404 corresponds to the restroom 122, the positive identification result 416 may be displayed on the display device 206A as: “Restroom Door and QR code near door handle of the lock”. This implies that the target object404 corresponds to an image associated with the restroom door 124 of the restroom 122 to be unlocked, based on the QR code as the target object information 414.

[0086] In one instance, the circuitry 204 may be configured to capture, from the user device 104, a second image of the target object 404 in response to the determination that the target object 404 corresponds to the restroom 122 as the negative identification result. Based on the captured second image, user access may be verified. For example, the user access may include the user credentials or user information trying to access the restroom 122. The control signal may be transmitted to the locking mechanism 126 to grant the restroom access to the user, based on the verification of the user access.

[0087] In another instance, if the verification of the user access based on the captured second image is unsuccessful, the circuitry 204 may be configured to control the display device 206A to display a backup authentication mechanism for the restroom access. The backup authentication mechanism may correspond to the PIN or the biometric scan associated with the restroom access for the user 110. In an embodiment, the circuitry 204 may be configured to generate an alert message in an event of unauthorized user access.

[0088] The circuitry 204 may be configured to selectively unlock the locking mechanism 126. Further, the control signal may be transmitted to the locking mechanism 126 to grant the restroom access to the user 110. The unlocking of the locking mechanism 126 and transmission of the control signal may be described further in FIG. 4D. FIG. 4D is described in conjunction with elements from FIG. 1, FIG. 2, FIG. 3, FIG. 4A, FIG. 4B, and FIG. 4C. With reference to FIG.4D, there is shown an exemplary scenario 400D. The exemplary scenario 400D comprises of an electronic user interface (UI) 418 and a UI element 420. In an example, the circuitry 204 may be configured to selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free, in response to the determination of the target object 404 corresponding to the restroom 122 as the positive identification result 416. Further, the circuitry 204 may be configured to unlock the locking mechanism 126 after receiving confirmation of the payment transaction corresponding to the payment code display 128, in response to the determination of the target object 404 corresponding to the restroom 122 as the positive identification result 416.

[0089] In an instance, with reference to FIG. 4D, there is further shown the electronic UI 418, which may be rendered by the system 102 or the user device 104 of FIG. 1 on the display device206A based on user request, received via application software. The application software may correspond to, for example, a software development kit (SDK), a cloud server-based application, a web-based application, an operation system (OS)-based application / application suite, an enterprise application, or a mobile application for remote workforce monitoring. The circuitry 204 of the user device 104 may be configured to selectively unlock the locking mechanism 126. For example, the UI element 420 may display the unlocking condition as: “User Access Detected. The User Name is Peter and User Id is X5467T”. Based on the display of the verified user access implying that the unlocking condition is satisfied, the control signal may be transmitted to the locking mechanism 126 to grant the restroom access to the user 110. For example, the permissions to be provided by the user to access the restroom 122 may be displayed as the UI window on the UI element 420 as: “Grant Restroom Access?”. The user 110 may select the option accordingly to access the restroom 122 and able to access the restroom 122, if the restroom 122 is not occupied.

[0090] It should be noted that the electronic UI 418 is merely provided as an exemplary implementation of user interface of the user device 102 of FIG. 1 and should not be construed as limiting for the scope of the disclosure. The present disclosure may also be applicable to other modifications, deletions, or additions to the client device 102, without a deviation from the scope of the present disclosure.

[0091] FIG. 5 is a flowchart that illustrates an exemplary processing pipeline for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure. FIG. 5 is described in conjunction with elements from FIG. 1, FIG. 2, FIG. 3, FIG. 4A, FIG. 4B, FIG. 4C, and FIG. 4D. With reference to FIG. 5, there is shown an exemplary processing pipeline 500 for the smart restroom access with device authentication and payment integration. The exemplary processing pipeline 500 may include various operational and decision blocks that illustrate operations involved in facilitating smart restroom access by the user 110.

[0092] At block 502, the user input 402 associated with the target object 404 may be received. For example, the system 102 may be configured to receive the user input 402 indicative of the image of the target object 404. The user input 402 may further comprise different data modalities like a text, a 3D video, or a 2D image associated with the target object 404.

[0093] At block 504, the prompt 412 may be prepared based on the user input 402 for identification of the target object 404. The prompt 412 may be a textual description such as anatural language text to instruct an artificial intelligence (Al) model (for example, the neural image model 120) to perform a specific task and generate a desired output. The prompt 412 may serve as a starting point for operation of the Al model to provide the context and instructions for generating a response.

[0094] At decision block 506, it may be determined if the target object 404 is identified as the restroom 122. If the target object is not identified as the restroom 122 (for example, the negative identification result), the second image of the target object 404 may be captured to verify the user access, and the control signal may be transmitted to the locking mechanism 126 to grant the restroom access to the user 110 if the user access verification is successful.

[0095] In an embodiment, if the target object is not identified as the restroom 122, the processing pipeline 500 may jump at block 508. At block 508 if the target object 404 is not identified as the restroom 122, an unauthorized user access is detected and the restroom access is denied. An alert message may be generated in case of the unauthorized user access and the alert message may be sent to the proprietor.

[0096] At block 510, if the target object 404 is identified as the restroom 122, user credentials associated with the user access and the restroom usage may be identified to grant access to the user 110 for the restroom access. Further, at decision block 512, it may be determined that if the user credentials are autosaved in the system 102. If the user credentials are autosaved in the system 102, the processing pipeline proceeds to block 514. At block 514, the locking mechanism 126 associated with the restroom door 124 may be unlocked automatically if access to the restroom door 124 is free.

[0097] In one embodiment, if it is being determined at the decision block 512 that the user credentials are not autosaved, the payment code display 126 may appear on the screen of the user device 104 (for example, the electronic user interface 418) which is scanned by the user 110 to complete payment transaction corresponding to the restroom usage. Further, the processing pipeline proceeds at block 518. At block 518, the user completes the payment transaction corresponding to the payment code display 126. Upon receiving the confirmation of the payment transaction, the system 102 or the user device (for example, the circuitry 204 of the user device 104) may directly unlock the locking mechanism 126. The control signal may then be transmitted to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition.

[0098] FIG. 6 is a flowchart that illustrates exemplary operations for smart restroom access with device authentication and payment integration, in accordance with an embodiment of the disclosure. FIG. 7 is described in conjunction with elements from FIG. 1, FIG. 2, FIG. 3, FIG.4A, FIG. 4B, FIG. 4C, FIG. 4D, and FIG. 5. With reference to FIG. 6, there is shown a flowchart 600. The flowchart 600 may include operations from 602 to 614 and may be implemented by the system 102 or the user device 104 of FIG. 1 or by the circuitry 204 of FIG. 2. The flowchart 600 may start at 602 and proceed to 604.

[0099] At 604, the user input 112 associated with the target object 118 may be received. The user input 112 may be indicative of the image of the target object 118. The circuitry 204 may be configured to receive the user input 112 associated with the target object 118. The reception of the user input 112 is described further, for example, in FIG. 3 (at 302 in FIG. 3).

[0100] At 606, the prompt 114 may be prepared based on the user input 112. The circuitry 204 may be configured to prepare the prompt 114 based on the user input 112. The preparation of the prompt 114 is described further, for example, in FIG. 3 (at 304 in FIG. 3).

[0101] At 608, the target object 118 may be identified as the identification result 116 based on application of the NIM 120 on the prompt 114. The circuitry 204 may be configured to identify the target object 118 as the identification result 116, based on the application of the NIM 120 on the prompt 114. The identification of the target object 118 as the identification result 116 is described further, for example, in FIG. 3 (at 306 in FIG. 3).

[0102] At 610, it may be automatically determined whether the target object 118 corresponds to the restroom 122. The circuitry 204 may be configured to automatically determine whether the target object 118 corresponds to the restroom 122. The automatic determination of the target object 118 as the restroom 122 is described further, for example, in FIG. 3 (at 308 in FIG. 3).

[0103] At 612, if the target object 118 corresponds to the restroom 122, the locking mechanism 126 may be selectively unlocked in response to the identification of the target object 118 as the positive identification result 416 (for example, the restroom 118). Further, in response to the determination of the target object 118 as the positive identification result 416, the locking mechanism 126 may be unlocked after receiving confirmation of the payment transaction corresponding to the payment code display 128. The circuitry may be configured to selectively unlock the locking mechanism 126 associated with the restroom door 124 automatically if access to the restroom door 124 is free, or unlock the locking mechanism 126 after receiving the paymenttransaction. The unlocking of the locking mechanism 126 is described further, for example, in FIG. 3 (at 310 in FIG. 3).

[0104] At 614, the control signal may be transmitted to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition. The circuitry 204 may be configured to transmit the control signal to the locking mechanism 126 to grant the restroom access to the user 110 upon satisfying the unlocking condition. The transmission of the control signal is described further, for example, in FIG. 3 (at 312 in FIG. 3) Control may pass to end.

[0105] Although the flowchart 600 is illustrated as discrete operations, such as 602, 604, 606, 608, 610, 612, and 614 the disclosure is not so limited. Accordingly, in certain embodiments, such discrete operations may be further divided into additional operations, combined into fewer operations, or eliminated, depending on the implementation without detracting from the essence of the disclosed embodiments.

[0106] Various embodiments of the disclosure may provide one or more non-transitory computer-readable storage medium configured to store instructions that, in response to being executed, cause a system (such as the system 102 or the user device 102 of the system 100) to perform a set of operations. The set of operations may include receiving, from a user device, a user input associated with a target object. The user input may be indicative of an image of the target object. The set of operations may further include preparing a prompt based on the user input. The set of operations may further include identifying the target object as an identification result based on application of a neural image model (NIM) on the prompt. The set of operations may further include determining whether the target object corresponds to the restroom. The set of operations may further include selectively unlocking the locking mechanism associated with the restroom door automatically if access to the restroom door is free, or unlocking the locking mechanism after receiving confirmation of a payment transaction corresponding to the payment code display, in response to the determining of the target object corresponding to the restroom as a positive identification result. The set of operations may further include transmitting a control signal to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition.

[0107] The various actions, acts, blocks, steps, or the like in the flow diagrams may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments,some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the disclosure.

[0108] The present disclosure may also be positioned in a computer program product, which comprises all the features that enable the implementation of the methods described herein, and which when loaded in a computer program is able to carry out these methods. Computer program, in the present context, means any expression, in any language, code or notation, of a set of instructions intended to cause a system with information processing capability to perform a particular function either directly, or after either or both of the following: a) conversion to another language, code or notation; b) reproduction in a different material form.

[0109] The embodiments disclosed herein can be implemented using at least one software program running on at least one hardware device and performing network management functions to control the elements.

[0110] While the present disclosure is described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made, any equivalents may be substituted without departure from the scope of the present disclosure. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present disclosure without departure from its scope. Therefore, it is intended that the present disclosure is not limited to the embodiment disclosed, but that the present disclosure will include all embodiments that fall within the scope of the appended claims.

Claims

CLAIMS1. A smart restroom access system, comprising:a locking mechanism installed on a restroom door;a payment code display positioned adjacent to the restroom door;a circuitry operatively coupled with the locking mechanism and the payment code display, the circuitry configured to:receive, from a user device, a user input associated with a target object, the user input indicative of an image of the target object;prepare a prompt based on the user input;identify the target object as an identification result based on application of a neural image model (NIM) on the prompt;determine whether the target object corresponds to the restroom;in response to determination of the target object corresponding to the restroom as a positive identification result:selectively unlock the locking mechanism associated with the restroom door automatically if access to the restroom door is free; orunlock the locking mechanism after receiving confirmation of a payment transaction corresponding to the payment code display, andtransmit a control signal to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition.

2. The system according to claim 1, wherein the circuitry is further configured to:retrieve a prompt template that includes a base instruction and context associated with the user input;extract, from the user input, target object information comprising at least one of a Quick Response (QR) code, a barcode, or a machine-readable identifier associated with the restroom access;update the prompt template to include the target object information as the context; andmodify the base instruction in the updated prompt template to prepare the prompt.

3. The system according to claim 1, wherein the neural image model (NIM) corresponds to a Convolutional Neural Network (CNN) Model, Generative Adversarial Network (GAN), or a Multilayer Perceptron (MLP).

4. The system according to claim 1, wherein the payment code display corresponds to a digital wallet, a credit card, a near field communication (NFC), crypto currency, or application-based payment platforms.

5. The system according to claim 1, wherein the circuitry is further configured to:in response to determination of the target object corresponding to the restroom as a negative identification result:capture, from the user device, a second image of the target object;verify user access based on the captured second image; andtransmit the control signal to the locking mechanism to grant the restroom access to the user, based on the verification of the user access.

6. The system according to claim 1, wherein the circuitry is further configured to:store logs associated with the user access to monitor restroom usage; andgenerate a report associated with the restroom usage for a proprietor.

7. The system according to claim 5, wherein the circuitry is further configured to:in an event of unsuccessful verification of the user access based on the captured second image:control a display device to display a backup authentication mechanism for the restroom access, wherein the backup authentication mechanism corresponds to a personal identification number (PIN) or a biometric scan.

8. The system according to claim 5, wherein the circuitry is further configured to generate an alert message in an event of unauthorized user access.

9. The system according to claim 1, wherein the transmission of the control signal to the locking mechanism to grant the restroom access to the user corresponds to a protocol-based communication technique.

10. The system according to claim 6, wherein the circuitry is further configured to:estimate a predetermined number of users associated with the restroom usage; and in an event of determination that number of users associated with the restroom usage exceeds the predetermined number of users:send a notification to the proprietor for restroom cleaning based on the determination.

11. A method, comprising:a circuitry configured to perform set of operations, the set of operations comprising: receiving, from a user device, a user input associated with a target object, the user input indicative of an image of the target object;preparing a prompt based on the user input;identifying the target object as an identification result based on application of a neural image model (NIM) on the prompt;determining whether the target object corresponds to the restroom; in response to the determining of the target object corresponding to the restroom as a positive identification result:selectively unlocking the locking mechanism associated with the restroom door automatically if access to the restroom door is free; orunlocking the locking mechanism after receiving confirmation of a payment transaction corresponding to the payment code display, and transmitting a control signal to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition.

12. The method according to claim 11, further comprising:retrieving a prompt template that includes a base instruction and context associated with the user input;extracting, from the user input, target object information comprising at least one of a Quick Response (QR) code, a barcode, or a machine-readable identifier associated with the restroom access;update the prompt template to include the target object information as the context; and modify the base instruction in the updated prompt template to prepare the prompt.

13. The method according to claim 11, further comprising:in response to determining of the target object corresponding to the restroom as a negative identification result:capturing, from the user device, a second image of the target object;verifying user access based on the captured second image; andtransmitting the control signal to the locking mechanism to grant the restroom access to the user, based on the verification of the user access.

14. The method according to claim 11, further comprising:storing logs associated with the user access to monitor restroom usage; and generating a report associated with the restroom usage for a proprietor.

15. The method according to claim 13, further comprising:in an event of unsuccessful verification of the user access based on the captured second image:controlling a display device to display a backup authentication mechanism for the restroom access, wherein the backup authentication mechanism corresponds to a personal identification number (PIN) or a biometric scan.

16. The method according to claim 13, further comprising:generating an alert message in an event of unauthorized user access.

17. The method according to claim 11, wherein the transmitting of the control signal to the locking mechanism to grant the restroom access to the user corresponds to a protocol-based communication technique.

18. The method according to claim 14, further comprising:estimating a predetermined number of users associated with the restroom usage; and in an event of determining that number of users associated with the restroom usage exceeds the predetermined number of users:sending a notification to the proprietor for restroom cleaning based on the determination.

19. The method according to claim 11, wherein the payment code display corresponds to a digital wallet, a credit card, a near field communication (NFC), crypto currency, or application-based payment platforms.

20. One or more non-transitory computer-readable storage medium configured to store instructions that, in response to being executed by a system, cause the system to perform a set of operations by a circuitry, the set of operations comprising:receiving, from a user device, a user input associated with a target object, the user input indicative of an image of the target object;preparing a prompt based on the user input;identifying the target object as an identification result based on application of a neural image model (NIM) on the prompt;determining whether the target object corresponds to the restroom; in response to the determining of the target object corresponding to the restroom as a positive identification result:selectively unlocking the locking mechanism associated with the restroom door automatically if access to the restroom door is free; orunlocking the locking mechanism after receiving confirmation of a payment transaction corresponding to the payment code display, and transmitting a control signal to the locking mechanism to grant restroom access to the user upon satisfying the unlocking condition.

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