Description:Field of the Invention
The goal of this proposed innovation is to develop an AI-capable robot that will teach and protect people especially children against unwanted physical interactions. Based on predetermined parameters, the robot uses sensors and object detection technology to distinguish between good touch and bad touch. The robot promotes a safe and friendly environment by teaching users about personal boundaries through interactive scenarios that build awareness and the prevention of dangerous circumstances.
Objective of the Invention
The primary objective of this invention is to develop an innovative and interactive educational robot to empower individuals, especially children, with the ability to recognize and respond to appropriate and inappropriate physical contact. By combining artificial intelligence, sensor technology, and robotics, the project aims to create a robot that can accurately differentiate between good touches and bad touches, providing real-time feedback and guidance. In order to prevent and resolve incidents of abuse or discomfort, this technology-driven strategy aims to increase awareness, improve personal safety, and encourage open discussions about consent, boundaries, and safe interpersonal interactions.
Background of the Invention
Children's protection is of the utmost important in the modern world due to evolving concerns such as harassment and abuse. Protecting children ensures their wellbeing, mental health, and future development, hence raising public awareness of child safety is crucial. A user-friendly robot has been constructed using sensors and object detection technology can teach us whether the touch is good or bad. The robot promotes a safe and friendly environment by teaching users about personal boundaries through interactive scenarios that build awareness and the prevention of dangerous circumstances.
For instance, US20190213498A1 presents a novel method for employing artificial intelligence to classify and understand contextual information. This technology involves processing and analyses the data from various sources, such as sensors and devices, to determine the context in which a user operates. The system recognizes patterns, actions, and environmental indicators to accurately estimate the user's context through the use of machine learning algorithms. The invention has significant implications for personalized user experiences, as well as applications in fields like smart devices, healthcare, and security, where contextual understanding is crucial for providing relevant and timely responses. This system contributes to the evaluation of good touch and bad touch by user-friendly robot which promotes safe environment for children
Similarly, US20080256008A1 relates to a huge step forward in improving safety awareness and education. The project permits the development of a responsive and interactive system capable of discerning between appropriate and inappropriate physical encounters by integrating cutting-edge robotics, AI, and sensor technologies. The robot gives personalized 2 input by combining touch, speech recognition, and emotional intelligence technology, leading to a stronger awareness of human boundaries. This project improves user experiences while simultaneously makes the world a safer place, especially for kids. It opens the door for more educated dialogues about appropriate and inappropriate contact by fusing technology innovation with delicate subjects, empowering people to handle their interactions with confidence and responsibility
US8942849B2 is also related to evaluation of good touch and bad touch by using sensors and object detection technology. This innovation enables seamless communication between humans and robots through speech and gestures, enhancing user interaction. The system employs advanced algorithms and sensors to understand user input and respond appropriately. The system also outlines a method for controlling the robot using this interface, optimizing its movements and actions based on surroundings. A corresponding program supports the implementation of this technology. The invention has wide-ranging applications in robotics, from customer service to education and healthcare, offering a more intuitive and user-friendly human-robot interaction. This system also advances the field by creating a more natural and effective means of communication between humans and humanoid robots.
US8018440B2 provides a system, method for determining good touch and bad touch. This system introduces a humanoid robot with a feature to reject unintentional touches. The innovation employs sensors and algorithms to differentiate between intentional and unintentional physical contact, preventing unwanted interactions. The technology enhances the robot's social and safety aspects, ensuring more accurate and respectful human-robot interactions. By effectively identifying touch intentions, the invention contributes to the development of humanoid robots that can better adapt to human preferences and boundaries while promoting comfortable and secure interactions.
US8577616B2 presents a technology that dynamically interprets touch-sensitive input. Using sensors and algorithms, the system adjusts its response based on factors like touch pressure, speed, and patterns. This adaptive interpretation enhances user interactions with touch-sensitive devices by accurately reflecting the user's intent. The invention finds applications in touchscreens, touchpads, and other input devices, optimizing user experiences. This innovation also contributes to the development of more responsive and intuitive interfaces, improving the accuracy and versatility of touch-based interactions.
This invention in order to effectively recognize and evaluate human actions uses AI. The system recognizes and interprets a range of gestures, movements, and activities that people exhibit by integrating sensors, cameras, and advanced machine learning algorithms. The AI can detect actions like waving, pointing, or suspicious behavior thanks to real-time data processing and pattern recognition. The project improves robot understanding of human intentions and emotions and finds applications in security, healthcare, and human-robot interaction. It adds to better safety measures, user experiences, and human-computer interactions by collecting behavior data. The study demonstrates how AI may be used to develop context-aware technology that fully comprehends human behavior, resulting in safer and more responsive settings across a variety of sectors

Summary of the Invention
The invention aims to utilize robotics and AI technology to differentiate between appropriate and inappropriate physical interactions, promoting safety awareness and education. The system involves equipping a robot with sensors and AI algorithms that enable it to analyze and classify touch interactions. By distinguishing between various gestures and contact types, the robot can identify instances of good touch and bad touch based on pre-defined criteria.
Through machine learning, the robot learns to recognize patterns and characteristics associated with different touch scenarios. It can detect gentle or friendly touches, such as handshakes or pats on the back, as good touch. Conversely, it can identify forceful or uncomfortable touches, like grabs or inappropriate contact, as bad touch. The robot's capabilities facilitate discussions about personal boundaries and safety with users, especially children, in a non-threatening and interactive manner.
This system is applicable to medical facilities as well as educational and child protective programs. A better knowledge of proper physical relationships and personal space is promoted by the robot's honesty and constant evaluation. By incorporating advanced technology into this sensitive topic, the project enhances awareness, communication, and the promotion of respectful behaviors, ultimately creating safer environments and empowering individuals to navigate physical interactions with confidence.
Brief Description of Drawings
The invention will be described in detail with reference to the exemplary embodiments shown in the figures wherein:
Figure-1: Flowgorithm representing the workflow of the robot hardware.
Figure-2: Diagrammatic representation of interaction flow between user and robot response components.
Figure-3: Flow chart representing the basic architecture and workflow of the developed prototype.
Detailed Description of the Invention
The model of the Artificial Intelligence Enabled Machine for Human Behavior Detection is built to employ robot technology for educating users about appropriate touch interactions, promoting safety and awareness. This innovation employs a sophisticated blend of robotics, artificial intelligence, and sensory technology to discern between appropriate and inappropriate physical interactions. Equipped with touch sensors, cameras, and pressure detectors, the robot captures real-time data during interactions with users. Advanced machine learning algorithms process this data, enabling the robot's AI to accurately categorize gestures and touches as either good or bad based on predefined criteria. Through a user interface that includes visual cues and feedback mechanisms, the robot effectively communicates its evaluations to users, promoting awareness of personal boundaries and safety education. This innovative project fosters a safer environment by utilizing technology to engage users, particularly children, in meaningful discussions about respectful touch interactions and enhancing their understanding of appropriate physical boundaries.
The testing model consists of several components. Cameras play a pivotal role in this invention, as they provide the robot with visual input to observe and analyze physical interactions. These cameras capture gestures and actions, allowing the robot to visually process and understand the nature of touch interactions between itself and users. The visual data is then processed using object detection technology, enabling the robot to discern different touch patterns and behaviors. This technology empowers the robot to identify specific gestures associated with good touch and bad touch scenarios. Complementing the visual input, touch and pressure sensors on the robot are employed to physically sense the nature of interactions. These sensors detect the intensity and duration of touches, enabling the robot to differentiate between gentle and forceful interactions. The data collected from these sensors is then integrated into the robot's AI algorithms, which utilize machine learning techniques to classify the touch interactions as either appropriate or inappropriate touch. This classification process is crucial in providing meaningful feedback to users.
The user interface is an essential component designed to bridge the communication gap between the robot and users. Utilizing visual cues, such auditory signals, the user interface conveys the robot's evaluations to users in an accessible manner. For good touches, positive signals are displayed, promoting positive reinforcement. For inappropriate touches, the interface signals concern, emphasizing the importance of personal boundaries. This interactive feedback loop educates users on respectful interactions and reinforces safety awareness, contributing to a better understanding of good and bad touch dynamics. Further enhancing the communication aspect of the innovation, speech recognition technology is integrated into the robot. Users can engage in spoken conversations with the robot to discuss their experiences and concerns related to touch interactions. The robot's AI employs natural language processing to analyze voice tone, emotion, and verbal cues, allowing it to gauge the users' emotional states during these discussions. This emotional intelligence component enhances the robot's ability to provide empathetic responses and personalized feedback that resonate with users' emotions and experiences.
As shown in Figure 2, it is a Diagrammatic representation of interaction flow between user and robot response components. The sequence diagram outlines the interaction between the user and the robot's response components. The User initiates communication with the Robot. The Robot interfaces with the User Input Processing, which applies NLP for input comprehension and communicates with Emotion Recognition for emotional analysis. The processed input is sent to Dialogue Management. Emotion context is generated by Emotion Recognition for Response Generation, producing feedback for conversation flow. Visual and Audio Feedback generates cues using text-to-speech. Response Generation also informs Safety Information to educate on recognizing bad touch and personal boundaries. It empowers users via Empowerment and Support, encouraging reporting. Dialogue Management maintains the dialogue, while Visual and Audio Feedback offers cues. The Safety Information and Empowerment and Support components persist in reinforcing awareness. The diagram illustrates how these elements collaborate for a supportive interaction, educating about good touch and bad touch.
Concerning Figure 3, The flowchart depicts the fundamental architecture and process of the developed prototype for evaluating good touch and bad touch interactions. It involves the identification of individuals, including the person and the robot. The system recognizes emotions through a server-based mechanism. The detection of touch interactions is conducted, leading to subsequent actions taken by guardians or authorities. Feedback is provided for instances of bad touch, while information extraction occurs for good touch scenarios. The prototype's workflow is illustrated through Figure-3, demonstrating how its components 5 collaboratively function to achieve its objectives of distinguishing between appropriate and inappropriate physical interactions, involving the recognition of individuals, emotions, and touch, along with corresponding actions and feedback mechanisms for ensuring safety awareness and education.
This invention represents a significant advancement in promoting safety education and awareness. By integrating cutting-edge robotics, AI, and sensor technologies, the project enables the creation of a responsive and interactive system capable of differentiating between appropriate and inappropriate physical interactions. Through the collaboration of touch, speech recognition, and emotional intelligence technologies, the robot provides tailored feedback, fostering a deeper understanding of personal boundaries. This project not only enhances user experiences but also contributes to a safer environment, especially for children. By combining technological innovation with sensitive topics, it paves the way for more informed discussions about good and bad touch, empowering individuals to navigate their interactions confidently and responsibly.
Also, this collected and generated data can be reused as training data to train the model further and obtain better results and predictions during the evaluation of good touch and bad touch. It can help in further management, analysis, visualization, and interpretation to obtain finer and enhanced results.
Advantages of the proposed model,
The proposed model provides the capability to detect good touch and bad touch and promotes a safe and friendly environment by teaching users about personal boundaries through interactive scenarios that build awareness and the prevention of dangerous circumstances. By analyzing physical interactions, object detection technology enables a robot to distinguish between good and bad touch. The robot recognizes human motions and distinguishes good touches from bad ones using sensors and AI algorithms, encouraging safety and awareness. This project promotes safer surroundings and improves personal boundary education.
Children can learn about proper and improper touches from robots in a non-judgmental and consistent manner. They can provide knowledge in an objective manner, avoiding any discomfort that might result from talking about such subjects with adults. This creates a secure environment where kids may learn and ask questions without worrying about being judged.
The provision of a better guidance system for evaluating good touch and bad touch can be leveraged using this model. Children are actively involved in the learning process because of interactive scenarios and real-time feedback from the robot. Through experience learning, this hands-on approach promotes children in better understanding concepts of good and bad touch.
The robot's capacity to recognize different types of touches can help in the early identification of potential abuse. Children will be better equipped to recognize warning signs, empowering them to seek help and report uncomfortable situations promptly, thereby preventing or minimizing harm.The robot serves as a safe and controlled platform for children to practice and refine their understanding of touch-related concepts. It provides a secured environment where children can experiment with different scenarios and receive immediate guidance, promoting self-assured decision-making.
6 Claims and 3 Figures , Claims:The scope of the invention is defined by the following claims:
Claims:
1. The machine for human behavior detection comprising:
a) The cameras in the robot of this invention capture physical interactions. The robot can distinguish between appropriate and inappropriate touches by using AI algorithms that analyze these interactions, thereby promoting safety education and awareness.

b) The robotic hardware in the robot enables physical interaction. The equipment consists of robotic limbs and other devices that mimic human motion. It enables the robot to interact with people, detect touches, and give timely feedback. The effectiveness of touch evaluation and safety teaching is improved by this physical presence.

c) The sensors in the robot detect tactile data during interactions. Touch and pressure sensors capture physical input from users, enabling the robot's AI to analyze touch patterns. This technology helps classify touch interactions as appropriate or inappropriate, facilitating safety education and awareness.

2. As per claim 1, the user interface in the robot facilitates communication. Through voice it conveys feedback about touch interactions. Positive responses for good touches and appropriate warnings for bad touches help users understand and internalize personal boundaries. Actions are done in response to harmful touches, and concerned persons are informed about caution, promoting safety education and awareness.

3. As per claim 1, the touch sensors in the robot of this invention detect physical interactions. These sensors capture data about touch pressure, duration, and location, allowing the robot's AI to assess and categorize touches as appropriate or inappropriate. The Pressure sensors in the robot of this invention detect varying force levels during physical interactions.

4. As per claim 1, the object detection technology enables the robot to identify and analyze touch interactions. The robot recognizes touch patterns and movements using cameras and other sensors.

5. As per claim 1, the NLP (Natural Language Processing) technology in the robot interprets user language. The speech recognition technology in the robot processes verbal interactions.

6. As per claim 1, the emotional intelligence technology in the robot enables it to perceive and respond to users' emotional cues. By analyzing voice tone and facial expressions, the robot gauges 7 emotional states during touch discussions.