Driver drowsiness is a major cause of road accidents, especially during long-distance or late-night driving. This paper presents a real-time Driver Drowsiness Detection and Alert System that uses a webcam to monitor the driver’s facial behavior. YOLO (You Only Look Once) is employed for accurate face detection, and Convolutional Neural Networks (CNNs) analyze facial features.

Task Bounty Board is a decentralized application () developed to revolutionize how microtasks are produced, claimed, and finished with the help of blockchain technology. Built upon the aground network, this platform enables clients to post tasks with enlisted rewards as ALGO tokens.

Hash tags play a pivotal role in increasing the visibility, discoverability, and engagement of social media content, particularly in the tourism sector where users search for travel inspiration using thematic tags. This project presents a multi-label hash tag recommendation system for tourism related social media posts focused on Indian destinations.

Understanding and monitoring various types of ecosystems and vegetation play an important role in the protection of the natural world and the sustainable management of land. This paper presents a dual approach artificial intelligence system for the analysis of satellite remote sensing data and the application of deep learning techniques to identify changes in forest cover and classify leaf types.

In an era of rapidly increasing digital content, the ability to efficiently process and comprehend large volumes of textual data has become essential. Automatic text summarization, a fundamental task within Natural Language Processing (NLP), seeks to condense lengthy documents into shorter, coherent summaries without losing essential information.

The project “Vision Meets Language: An Image Captioning Framework Using Deep Learning” explores the intersection of computer vision and natural language processing (NLP) to automatically generate descriptive captions for images. Image captioning is a complex task that requires understanding both the visual content of an image and the linguistic structure necessary to express that understanding in natural language.

India’s rapidly aging population, expected to surpass 340 million by 2050, faces significant challenges in providing dependable and reasonably priced elder care, particularly in rural and semi-urban areas with inadequate infrastructure and caregiver shortages. This paper proposes SevaSetu-ShantamCare, a decentralized, AI-powered ecosystem designed to deliver community-based and privacy-preserving elder care services.

The way that contemporary systems communicate with physical objects and environments has been completely transformed by the Internet of Things (IoT). IoT has increased the accessibility and efficiency of automation by allowing devices to communicate via internet connectivity. One of the most useful applications of IoT technology are smart home systems, which let users automate daily chores and remotely operate appliances. .

Human Metapneumovirus (HMPV) is a respiratory pathogen causing significant morbidity across pediatric, adult, and immunocompromised populations. Early diagnosis is critical, but conventional methods—such as RT-PCR and immunofluorescence—are time-consuming and costly, while radiological findings are non-specific. Recent advances in artificial intelligence (AI) and machine learning (ML) present opportunities for automated diagnosis by integrating medical imaging with clinical data.

A legacy monolithic application was successfully refactored into a containerized microservices architecture, uti- lizing modern DevOps practices to enhance scalability, main- tainability, and security. The original system, built with Flask, Python2, and SQLite, was re-engineered with an ASP.NET Core backend, a ReactJS frontend, and a PostgreSQL database, follow- ing Clean Architecture and SOLID principles.