Abstract: An autonomous and adaptable AI-powered robotic workstation system is designed for diverse real-world applications. This includes a configurable workstation seamlessly integrating a dynamic robotic hand, endowed with real-time decision-making capabilities. The workstation features an automatic calibration and self-configuration mechanism utilizing six-axis motion for task execution, ensuring alignment and auto-positioning via cameras. A dynamic and no-code onboarding process with auto-calibration captures and stores product onboarding, optimization of object categorization and prioritizing captures using vision AI. The system also includes a vision-based operations module with AI-driven functionality, integrated hardware, scalable design, calibration capabilities, and unification of specified operations within the same workstation system.

Abstract: The present application provides an AI Bartending System that leverages artificial intelligence, machine learning, and advanced robotics to deliver an unparalleled bartending experience for users. The AI Bartending System integrates a collaborative robot (cobot) and an AI Robotic Hand equipped with advanced sensors for precise and speedy drink preparation tailored to user preferences. In this system, users can interact with the system through an intuitive conversational AI concierge interface, requesting specific drinks or personalized recommendations. The system learns from user interactions and feedback using machine learning algorithms and experiential learning AI, continuously refining its recommendations and adapting to evolving user preferences. Additionally, the system utilizes AI computer vision to perceive its environment, capturing both spatial and contextual information in real-time. This enables it to identify and localize key elements within its operational space, ensuring optimal performance.

Abstract: An AI-driven system crafted for the precise X-ray analysis of a variety of objects and identifying defects with high accuracy. Specifically, the system conducts a thorough X-ray analysis of products, systematically identifying defects part by part (using a co-pilot interface) and categorizing them with precision as either pass (non-defective) or fail (defective). In this system, through an intuitive co-pilot interface, the AI collaborates seamlessly with experts, offering detailed views of identified defects along with reference guides, enhancing the overall defect identification process. This interface fosters active participation of experts in the defect identification process, thereby elevating the system's accuracy and reliability and the system iteratively retrains the AI model via this interface, enhancing its capabilities to surpass human precision and effectiveness.

Abstract: An autonomous and adaptable AI-powered robotic workstation system is designed for diverse real-world applications. This includes a configurable workstation seamlessly integrating a dynamic robotic hand, endowed with real-time decision-making capabilities. The workstation features an automatic calibration and self-configuration mechanism utilizing six-axis motion for task execution, ensuring alignment and auto-positioning via cameras. A dynamic and no-code onboarding process with auto-calibration captures and stores product onboarding, optimization of object categorization and prioritizing captures using vision AI. The system also includes a vision-based operations module with AI-driven functionality, integrated hardware, scalable design, calibration capabilities, and unification of specified operations within the same workstation system.

Abstract: An AI-driven system crafted for the precise X-ray analysis of a variety of objects and identifying defects with high accuracy. Specifically, the system conducts a thorough X-ray analysis of products, systematically identifying defects part by part (using a co-pilot interface) and categorizing them with precision as either pass (non-defective) or fail (defective). In this system, through an intuitive co-pilot interface, the AI collaborates seamlessly with experts, offering detailed views of identified defects along with reference guides, enhancing the overall defect identification process. This interface fosters active participation of experts in the defect identification process, thereby elevating the system's accuracy and reliability and the system iteratively retrains the AI model via this interface, enhancing its capabilities to surpass human precision and effectiveness.

Abstract: The present application relates to an Artificial Intelligence (AI) hand type device that emulates human hand capabilities, delicately to autonomously identify and pick up small and fragile objects, including but not limited to nails, screws, and microchips, with precision. Equipped with advanced sensors, algorithms, and AI, the device accurately locates object positions and angles using computer vision technology and a high-resolution camera. It performs quality inspection analysis, object placement, movement and mechanical operations autonomously, based on AI decisions according to the real time perspective of its surrounding environment. The device's AI-driven robotic arms adapt their grip strength, pressure and temperature for handling tiny delicate items such as eye-glass screws and larger objects such as motorized drill machines. With the ability to learn from domain experts, the present device autonomously executes tasks based on past experiences.

Abstract: The present application relates to an Artificial Intelligence (AI) hand type device that emulates human hand capabilities, delicately to autonomously identify and pick up small and fragile objects, including but not limited to nails, screws, and microchips, with precision. Equipped with advanced sensors, algorithms, and AI, the device accurately locates object positions and angles using computer vision technology and a high-resolution camera. It performs quality inspection analysis, object placement, movement and mechanical operations autonomously, based on AI decisions according to the real time perspective of its surrounding environment. The device's AI-driven robotic arms adapt their grip strength, pressure and temperature for handling tiny delicate items such as eye-glass screws and larger objects such as motorized drill machines. With the ability to learn from domain experts, the present device autonomously executes tasks based on past experiences.

Abstract: The present application relates to an autonomous AI quality inspection system that uses robotics, AI and computer vision technology to measure and inspect various parameters of manufactured objects, including but not limited to fasteners such as nuts, bolts, screws, and nails. The autonomous system uses computer vision to capture raw images of the objects, inspect their key parameters, and display the quality assurance (QA) results on an interactive application dashboard and achieve a consistent precision level of up to 0.01 mm. The system comprises of an edge gateway connected to a high-resolution camera that captures images of the objects and a cloud server that detects the images, removes background of the objects, fetches the edges and points, calculates the key characteristics and thereby displays the computed data on a user dashboard for quality control check. The system can be adapted to different types of manufacturing objects by a one-time onboarding process.

Abstract: The present application relates to a process and system for automating Reinforcement Learning with Expert Feedback (RLEF) in AI training processes. The process provides a user-friendly and automated platform (system) that facilitates the training of AI models and enables continuous learning through Reinforcement Learning with Expert Feedback. The process reduces the time and iterations required to build an autonomous grade AI model that performs with high accuracy and consistently when deployed and operating in real world situations. The autonomous AI system integrates a live feedback loop mechanism that combines an AI model, this is referred to as the “apprentice”, with instructors who are domain experts at the particular job or tasks that the AI is attempting to automate.

Abstract: The present application relates to an autonomous drive through system and method for autonomously detecting the position of the user's face in a vehicle and through AI and robotic technology, calibrating the height, distance, and direction/orientation (x, y, z axis) of the interface associated with the device, bringing the interface closer to the user. The user (driver) either through touch screen and/or voice AI and/or pairing with a mobile device can order and/or pay and/or withdraw cash without coming out of their vehicle(s). The system includes one or more sensors, such as a camera, that provides input for autonomously adjusting height of the device with respect to the user (driver) window. Based on the location of the car window, the device adjusts its position via moving horizontally (x-axis) based on the location of the driver's window and adjusts its position vertically along the y-axis to place itself at the eye level of the user.

Abstract: The present application provides an interactive and predictive autonomous AI system leveraging IoT, AI and computer vision, and allowing a cloud based systems to actively monitor a classified inventory of food items, advising the restaurants/food outlets staff the amount of food products to be prepared and stocked based on a Forecasting AI module, thereby maximizing efficiency with respect to food usage and minimizing food spoilage. The system autonomously captures images of inventory, both incoming and outgoing, classifies (shape/color) the images of the inventory, further trains and corrects the AI model in real time and concurrently with the image capture process, to ensure accuracy via a co-pilot module, which ultimately accurately predicts the exact amount of food products in inventory to be sold within a prescribed time frame, based on several parameters (such as historical usage data, weather data, etc.) using the forecast AI module.

Abstract: The present application relates to an autonomous drive through system and method for autonomously detecting the position of the user's face in a vehicle and through AI and robotic technology, calibrating the height, distance, and direction/orientation (x, y, z axis) of the interface associated with the device, bringing the interface closer to the user. The user (driver) either through touch screen and/or voice AI and/or pairing with a mobile device can order and/or pay and/or withdraw cash without coming out of their vehicle(s). The system includes one or more sensors, such as a camera, that provides input for autonomously adjusting height of the device with respect to the user (driver) window. Based on the location of the car window, the device adjusts its position via moving horizontally (x-axis) based on the location of the driver's window and adjusts its position vertically along the y-axis to place itself at the eye level of the user.

Abstract: The intelligent water network management system and method to intelligently monitor and/or control water parameters and identify and solve real time issues comprising theft, leakages, and quality of water, pressure change and related damages across water networks through an Internet-of-Things (IOT) Gateway connected to a cloud software/platform and components in a water distribution network including but not limited to water meters, water quality sensors, reservoir sensors and actuators connected wired or wirelessly to a local gateway that collects, processes/examines, aggregates, and transfers the real time data or information of sensors/meters at a predefined frequency and pushes it to a cloud platform that receives information from the gateways, analyzes it and identifies the occurrence of real time events (water leakage/theft/water quality issues/water running out) and thereafter alerts the relevant authorities for investigation of water leakage/theft/water quality issues at a specific location, the infor

Abstract: The present application relates to an autonomous drive through system and method for autonomously detecting the position of the user's face in a vehicle and through AI and robotic technology, calibrating the height, distance, and direction/orientation (x, y, z axis) of the interface associated with the device, bringing the interface closer to the user. The user (driver) either through touch screen and/or voice AI and/or pairing with a mobile device can order and/or pay and/or withdraw cash without coming out of their vehicle(s). The system includes one or more sensors, such as a camera, that provides input for autonomously adjusting height of the device with respect to the user (driver) window. Based on the location of the car window, the device adjusts its position via moving horizontally (x-axis) based on the location of the driver's window and adjusts its position vertically along the y-axis to place itself at the eye level of the user.