Volume 13 | Issue 4 |

 Abstract

The field of human-computer interaction has seen significant advancements with the development of virtual mouse and gesture recognition systems. These technologies aim to create intuitive and seamless ways for users to interact with digital environments, eliminating the need for traditional input devices like keyboards and physical mice. Gesture recognition enables users to control applications through natural hand movements, enhancing accessibility and efficiency. The evolution of these systems has been driven by advancements in artificial intelligence, machine learning, and computer vision, enabling real-time tracking and interpretation of human gestures with remarkable accuracy. The development of virtual mouse technology and gesture recognition has undergone a transformative journey, incorporating innovations in sensor technologies, deep learning models, and pattern recognition algorithms. Early implementations relied on simple motion detection, but modern approaches utilize sophisticated techniques such as convolutional neural networks and 3D depth sensing for precise gesture mapping. These advancements have broadened applications in fields such as gaming, augmented reality, assistive technologies, and medical rehabilitation. As research continues, the integration of these technologies into everyday digital experiences is expected to further enhance user interaction, making computing more immersive and accessible.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Open-cv, Mediapipe, Pyautogui, Numpy, python, Virtual mouse

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Various technology used in the past some years and this is rise in the field of technology, and one of the technique like machine learning is widely used in various fields. Now it has various applications in the health industry. It works as a helping hand for the field of health industry. By the help of various learning algorithms, we can make various models for predicting the results through the large amount of dataset present in medical field. This comprises of efficient used in predicting disease through symptoms. As, the health industry has a very huge amount of data for various fields so, we want to make a system where we can use various other applications of machine learning on health industry. This all had been done to make the best medical decisions and also for rise in the accuracy. As early accurate analysis predict disease through some symptoms and helps in the patient care and the human services. These all challenges can be easier by the help of various tools, algorithms and framework provided by the prediction system

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 Keywords

AI chatbot, healthcare, natural language processing, rural healthcare, appointment booking, IOT enabled

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Employee Performance Appraisal System in a BPO (Business Process Outsourcing) environment is designed to evaluate and enhance employee productivity, identify training needs, and align individual goals with organizational objectives. In the high-paced and target-driven BPO sector, timely and accurate performance evaluation is critical for maintaining service quality and employee satisfaction. This system automates the appraisal process using key performance indicators (KPIs) such as attendance, quality of work, target achievement, customer feedback, and teamwork. It provides a transparent and structured framework for performance reviews, incorporating self-assessment, peer reviews, and managerial evaluations. By leveraging data analytics and user-friendly dashboards, the system ensures fair assessment, reduces manual bias, and helps in identifying top performers and underperformers. The overall goal is to foster a performance-driven culture, support career development, and improve organizational efficiency.

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project disclose the present appraisal system and future expectations in AI based system

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Identity endorsements by Celebrities act as a fundamental factor which determines how consumers view brands and establish trust as well as brand devotion. This research analyzes trustworthiness as well as brand endorsement effects through an evaluation of 150 subject participants. A celebrity controversy has the power to damage brand image and visibility and steer customers toward different choices about the brand's quality and cost. Future research must analyze if influencer sponsorships create more effective brand and attractiveness endorsements than traditional celebrity endorsements do. Trust from consumers emerges as a factor but its authority depends on how much fame and expertise the celebrity possesses. Product research should analyze monetary benefits of expanded knowledge about endorsement approaches even though brand recognition benefits from endorsements.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Celebrity Endorsement, Brand Trust, Consumer Behavior, Advertising Strategy, Social Media Marketing, Brand Awareness

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Janapada Loka mattu Kannada Sanskrrti

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Creative Commons Attribution 4.0 and The Open Definition

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Janapada Loka mattu Kannada Sanskrrti

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Creative Commons Attribution 4.0 and The Open Definition

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The main focus of the research is to study strength characteristics of pervious concrete and it's permeability. Pervious concrete's high porosity often leads to a honeycomb structure, which can compromise its strength compared to conventional concrete. Pervious concrete is a special kind of concrete which allows water to flow through it because of its high porosity and therefore high permeability. Therefore the pervious concrete can be used as solutions to many problems such as drainage problems, ground water table recharge, sustainable development. In pervious no fine aggregates are used or sometimes fine aggregates are used to very little extent. There are various application of pervious concrete. It can be used in basement drainage, pedestrian walkways, local streets, low traffic highway, parking lots.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pervious Concrete, Porous Concrete, Permeability, No-fine Concrete.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Herbal medicine, being derived from plants, has been practiced for centuries by various cultures due to its therapeutic use. Natural remedies are now becoming popular in modern society since they are thought to be safe, accessible, and even potent in healing many health conditions.

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: Natural Healing, Immunity Boost, Anti-inflammatory, Digestive Health, Skin Care.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

i want to survey people and ask them about variety topics

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Creative Commons Attribution 4.0 and The Open Definition

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electric two-wheeler automobiles, consumer perception

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Creative Commons Attribution 4.0 and The Open Definition

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The Indian Sign Language (ISL) is essential for communication among the deaf and hard-of-hearing community. However, the lack of widespread ISL understanding creates a communication gap. This research focuses on developing an ISL recognition system using Long Short-Term Memory (LSTM) networks and OpenCV to process video inputs, extract features, and recognize dynamic hand gestures in real-time. The system employs pose estimation techniques to detect hand movements and classifies them using LSTM-based deep learning models. The proposed approach achieves high accuracy, ensuring a robust and scalable solution for real-time ISL interpretation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Indian Sign Language (ISL), LSTM, OpenCV, Gesture Recognition, Deep Learning, Real-Time Processing, MediaPipe, Neural Networks, Computer Vision, Assistive Technology.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Maintaining discipline and security in educational institutions requires ensuring adherence to standard regulations. YOLOv11, OpenCV, and dlib are used in this study's AI-driven real-time Uniform Detection System to automatically identify and categorise people according to their uniform status. The device uses face recognition to identify pupils and confirm that they are wearing the necessary uniform. It also incorporates a video capture camera for ongoing surveillance. An automatic email notice is sent to the relevant authorities and pupils in the event that a uniform violation is found. A unique YOLOv11 dataset is used to train the algorithm, guaranteeing precise distinction between uniforms and casual attire. The device also flags any security issues by identifying unauthorised individuals. The system saves captured frames of infractions for later study and keeps detection logs with timestamps, uniform status, and facial recognition results to improve data management. Notifications are tracked via logging email alerts. OpenCV is used for real-time image processing, Roboflow is used for dataset preparation, and Google Colab is used for model training. This automated method guarantees adherence to institutional policies, improves security, and decreases the need for manual oversight. IoT-based remote alerts and dataset extension are examples of future advancements that will increase accuracy and dependability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI surveillance, YOLOv11, uniform detection, facial recognition, OpenCV, real-time monitoring, student identification, automation, object detection, data storage, school security, compliance tracking, discipline enforcement.

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Creative Commons Attribution 4.0 and The Open Definition