IoT-Driven Fall Detection and Smart Monitoring System for Elderly Care Prashant Dalvi Dhiren Kumar Volume 2, Issue 1, Pages 1-5, January 2025 Epidemiological studies indicate that the incidence of accidental falls among older adults is significantly higher than previously estimated, representing a major public health concern. Falls are a leading cause of morbidity and mortality in the elderly population, particularly among individuals aged 75 years and above. Clinical data suggest that approximately 70% of injury-related deaths in ... Read More Article DOI: doi.org/10.47001/JAIET/2025.201001
Design and Implementation of an IoT-Based Real-Time Alert System for Women’s Safety K. Prashanth Kumar Volume 2, Issue 1, Pages 6-10, January 2025 Epidemiological studies indicate that the incidence of accidental falls among older adults is significantly higher than previously estimated, representing a major public health concern. Falls are a leading cause of morbidity and mortality in the elderly population, particularly among individuals aged 75 years and above. Clinical data suggest that approximately 70% of injury-related deaths in ... Read More Article DOI: doi.org/10.47001/JAIET/2025.201002
The Role of LLM-Based Tools in Shaping Cognitive Skills Among Young Adults A. Manish Sundar Volume 2, Issue 1, Pages 11-15, January 2025 This study systematically examines the cognitive implications of AI-assisted thinking by analyzing how the use of large language models (LLMs), such as ChatGPT, influences critical thinking ability, memory retention, and decision-making processes among young adults. As generative AI tools become increasingly embedded in academic environments and professional workflows, concerns have emerged r... Read More Article DOI: doi.org/10.47001/JAIET/2025.201003
Multimodal Sign Language Recognition Using Convolutional Neural Networks A.Anbarasan Arasu P.K.Ramachandran G.Arun Babu R.Sathish Kumar Volume 2, Issue 1, Pages 16-19, January 2025 The primary objective of the proposed sign language recognition system is to automatically interpret hand gestures into meaningful linguistic representations by analyzing their shape, spatial orientation, motion trajectory, and relative position. The work focuses on the development of a real-time, vision-based interpreter capable of recognizing and classifying alphabet gestures from American ... Read More Article DOI: doi.org/10.47001/JAIET/2025.201004
Deep Learning–Driven Visualization Framework for Osteo Carcinoma Detection in X-Ray and MRI Images Parvathy Gunasekaran Nanjundeshwaran Kannappa Abinav Rao Volume 2, Issue 1, Pages 20-26, January 2025 Osteo carcinoma (osteosarcoma) is an aggressive primary bone malignancy that requires early and accurate diagnosis to improve patient survival and treatment outcomes. Radiological imaging modalities such as X-ray and Magnetic Resonance Imaging (MRI) play a crucial role in detecting structural and soft tissue abnormalities associated with bone tumors. However, manual interpretation of these im... Read More Article DOI: doi.org/10.47001/JAIET/2025.201005
