Real-Time Bicep Curl Tracking and Pose Detection Using OpenCV and Media-Pipe
Human pose estimation is crucial for enabling real-time monitoring of physical exercise via the analysis of movement and orientation of the body. However, existing pose estimation techniques are prone to major flaws such as mislocalization of joints, occlusion issues, and mis-recognition of repetition of exercises. Such flaws undermine the efficacy and reliability of fitness tracking systems. In an attempt to address these flaws, the present study proposes a real-time bicep curl tracking system based on OpenCV and MediaPipe. The proposed system is designed to accurately estimate human pose, calculate joint angles, and provide automatic user feedback. One of the system's basic features is that it uses a state-based repetition counter, which improves accuracy in repetition detection by eliminating false positives caused by minor landmark placement variation. The system only detects repetitions when form is proper and range of motion is full. In addition to providing real-time feedback on posture changes and detecting improper exercise form, the system effectively eliminates the risk of injury during the execution of strength training exercises. It provides real-time feedback on posture changes and incorrect exercise form. Through empirical analysis, the system proposed has a remarkable accuracy of 96% in quantifying repetitions, which outperforms the performance of the traditional pose tracking models. The high accuracy verifies the system's robustness as well as its usability in real-world fitness applications. Findings indicate that the integration of AI-driven pose estimation and feedback mechanisms can potentially make personalized fitness training much more effective. Together with real-time correction and individualized data, these technologies can improve efficiency in training while motivating safer training habits. This work contributes to the growing field of AI-driven health and fitness technology and opens the door to more advanced and responsive physical activity monitoring devices
Published by: Shiv Arora, Drishti Sharma, Shubh Mudgal, Sudhanshu Chaudhary
Author: Shiv Arora
Paper ID: V11I3-1257
Paper Status: published
Published: May 28, 2025
EV BMS with Charge Monitoring and Fire Protection
In the silent heartbeat of our electrified era, lithium-ion batteries hum with potential and peril, their compact chemistry balancing progress on the knife’s edge of combustion. As thermal runaway lurks—unseen, unbidden, catastrophic—the Battery Management System (BMS) emerges not as a passive overseer but as an intelligent, multi-layered oracle of prevention, prediction, and protection. Within this chaotic choreography of heat, gas, pressure, and current, sensors become storytellers, whispering the earliest murmurs of disaster; algorithms, trained on the echoes of past failures, thread together anomalies into foresight; and suppression technologies, ever-vigilant, stand ready to suffocate the spark before it breathes. This paper explores the hybrid symphony of emergent AI, sensor fusion, and real-time control systems, where layered architectures form not just circuits, but cybernetic guardians. No longer are BMS mere managers; they are sentinels, anatomies of foresight crafted in silicon and code, promising not just energy, but safe, self-aware power in a world increasingly defined by its electric pulse.
Published by: Navajeevan, Rakesh, Sandeep M, Vishal T, Tenson Jose
Author: Navajeevan
Paper ID: V11I3-1251
Paper Status: published
Published: May 28, 2025
Anti-Face Spoofing Detection using Texture and Eye Blink Parameters
Growing reliance on facial recognition for secure authentication in various applications, ensuring that facial inputs are genuine and not spoofed using photos, videos, or masks has become critical. This work introduces a real-time anti-face spoofing detection system that harnesses computer vision and deep learning to verify the liveness of facial inputs. The system integrates Media Pipe Face Mesh for accurate facial landmark detection, a Convolutional Neural Network (CNN) for classifying real vs fake faces, and eye blink detection using Eye Aspect Ratio (EAR) to further enhance liveness verification. Additionally, a texture analysis module and motion blur detection help assess image quality and prevent spoofing attempts through printed photos or video replays. A dynamic overlay displays relevant metrics such as EAR, texture score, model confidence, and blur score, aiding both real-time feedback and system transparency. The interface includes a timestamp module and real-time performance chart for enhanced monitoring. This robust solution contributes to secure biometric authentication by combining multiple detection layers for high accuracy in face liveness classification.
Published by: Abhishekayya Kambi, Ankit Ronad, Sumanth Mudegoudra, Dr Vidyagouri B
Author: Abhishekayya Kambi
Paper ID: V11I3-1203
Paper Status: published
Published: May 27, 2025
Public Perception of Justice and Its Influence on The Legal System
This paper explores the influence of public perception on the legal system, particularly in democratic nations where public opinion is crucial for legal policy reforms. It evaluates how factors such as issue salience, media portrayal, and sentiment can affect public perceptions of justice, thus influencing legal change. Through examples like the George Floyd, ‘Black Lives Matter’ movement case, this research reveals that while public opinion can create significant legal reforms, such changes can be fleeting as public focus or salience shifts. Furthermore, the paper delves into the role politics and interest groups play in either strengthening or hindering the influence of public opinion on legal systems. Although a relationship between public opinion and legal change clearly exists, the significance of this influence is still uncertain, emphasising the need for further research.earch.
Published by: Avani Malhotra
Author: Avani Malhotra
Paper ID: V11I3-1238
Paper Status: published
Published: May 27, 2025
Deep Search: An Intelligent File Searching through Content Analysis
Real-time full-text search holds essential value in current digital libraries because it helps users find documents with content rather than names [1]. Users can perform content-based searches that reveal files through the extraction of textual contents within documents and optimize the retrieval process for research databases as well as legal document search and enterprise knowledge management solutions [2]. A full-text search technique-powered document retrieval system, which seeks to create a content-based file searching mechanism, is analyzed within this report. These search systems implement ranking as their main step to evaluate document relevance through the combination of term frequency and document length analysis with inverse document frequency factors [3]. The foundation for improving search accuracy and efficiency depends heavily on knowledge about directory creation as well as score calculation methods. The research also explores performance comparison between Whoosh and Elasticsearch regarding their scaling capabilities and their abilities to index data and respond to search queries and rank results [4]. Whoosh functions best for compact document sets, yet Elasticsearch delivers real-time search functionality for extensive data collections. The final report will present the most effective solution for creating a content-based search system with high performance levels for various application domains.
Published by: Nachiket Parjane, Kartik Patare, Rohan Ingle, Renuka Wakhare
Author: Nachiket Parjane
Paper ID: V11I3-1240
Paper Status: published
Published: May 25, 2025
The Effect of Dollarization on the Argentine Economy- A Global Analysis
This research paper looks at the possible social and economic impacts of the implementation of the American Dollar in Argentina, through the use of a comparative analysis, between 5 different countries that have implemented numerous forms of dollarization. After an analysis of the socio-economic factors of El Savador, Ecuador, Cambodia, Panama and Zimbabwe, the researcher makes a conclusion on the benefits and harms of the implementation of the dollar. The historical analysis provides insight into the various policy reformation decisions made by different countries across the globe, to combat one major problem, inflation, all with the desire to achieve economic stability. This research paper looks at the applicability of the dollar in the Argentine economy, white analyzing and evaluating economic policy decisions throughout Argentine history. The research paper also finds out that economic prosperity is not a byproduct of simply the geographic location, natural resources or its culture, but rather the effectiveness of the political and economic institutions that govern the country.
Published by: Kevin Isaac
Author: Kevin Isaac
Paper ID: V11I2-1396
Paper Status: published
Published: May 25, 2025
