Authors: Assistant Professor Sangeeta Mohapatra, Mr. Samarth Vitthal Pandit, Mrs. Ankita Jagdish Naik, Mrs. Sakshi Govind Nagargoje, Mr. Nandani Surendra Gaikwad, Mrs. Pranjal Santosh Pardeshi

Abstract: Mental health often takes a backseat in the fast-paced life of India, leading to rising cases of stress, anxiety, and lifestyle-related diseases. Many individuals struggle to find accessible and effective support systems. Our mental health tracker app aims to address this gap by offering an interactive chatbot for emotional support, expert-written blogs on wellness, a mood and habit tracker, and a smart health band to monitor vitals. This paper delves into the system design, key features, and its impact, drawing insights from recent research in digital mental health, peer influence, and intervention strategies.

 

 

Published by: vikaspatanker

Authors: Lokesh, Saurav Ingale, Ayush Kapse, Om Solanke, Milind Ankleshwa, Professor Kirti Randhe

Abstract: This survey paper investigates advancements in applying neural networks to Autism Spectrum Disorder (ASD) diagnosis, a condition characterized by challenges in communication, social interaction, and behavioral patterns. With early intervention critical for positive outcomes, traditional diagnostic methods are often time-consuming, subjective, and prone to limitations in accuracy. Emerging technologies like neural networks offer promising solutions for automating and improving ASD diagnostics. Our study systematically reviews current applications of neural networks, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), in analyzing behavioral patterns and facial image data. Key findings underscore the strengths of these models in capturing distinct ASD traits while also addressing challenges such as overfitting, data scarcity, and model generalizability. The integration of multi-modal data—such as combining behavioral cues with facial analysis—is explored as a pathway for enhancing diagnostic precision. While demonstrating the potential of these techniques, this paper highlights ethical considerations, including data privacy and the interpretability of neural network-based decisions in clinical settings. Future directions focus on developing self-updating datasets, promoting explainable AI, and fostering global collaborations to ensure diverse and representative data pools. This comprehensive review aims to guide the development of innovative, scalable, and ethically compliant diagnostic tools that make early ASD diagnosis more accessible and reliable.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Sangeeta Mohapatra, Assistant Professor Pooja Mohbansi, Omkar Bhalekar, Avinash Nayakawadi, Sumit Patil, Md Mahbub Reza

Abstract: This paper presents an innovative application that converts PDF documents into interactive mind maps using advanced AI technologies. By leveraging Google’s Gemini AI model and Streamlit, PDF2MindMap extracts text from uploaded PDFs, processes it to identify key concepts, and generates a hierarchical markdown mind map. The mind map is visualized through an enhanced Markmap interface, providing an intuitive and dynamic way to explore document structures. This tool aims to streamline knowledge extraction and visualization, offering significant value in educational, research, and professional contexts where understanding complex documents quickly is essential.

 

 

Published by: vikaspatanker

Authors: Deepti Varshney, Prerna Jadhav, Anam Shaikh, Anisha Dhumal, Tejal Pawar

Abstract: The "Helping Hands" app is designed to link donors with those in need, streamlining the process of distributing essentials like food and clothing. This mobile platform enables users to donate items effortlessly, monitor their contributions, and ensure that deliveries reach the intended recipients efficiently. By incorporating NGOs, hospitals, and animal shelters, the app enhances transparency and optimizes resource management. It tackles urgent issues such as hunger and homelessness, providing a straightforward yet powerful means to foster social responsibility and philanthropy within the community.

 

 

Published by: vikaspatanker

Authors: Professor Swati Bagade, Dr.Anamika Jain, Vedashri Satle, Samruddhi Raskar, Viniya Sanap, Sneha Salunke

Abstract: This research targets an automated system developed in the form of a mobile application which provides relevant legal acts and sections based on user queries. It aims both at legal practitioners and the layman. Users need to explain a legal issue in a normal language and the software seeks the relevant laws, sections, and regulations. It enhances legal transparency, supports research, and aids compliance by tailoring content to different jurisdictions. The system uses structured databases and sophisticated search techniques to provide guaranties for precise and quick retrieval of legal information. With a user-friendly interface and offline accessibility, this application bridges the gap between legal complexities and public understanding, making legal knowledge more accessible, actionable, and efficient for various users, including legal professionals, businesses, and individuals seeking legal guidance.

 

 

Published by: vikaspatanker

Authors: Professor Swati Bagade, Khushi Dilip Wable, Siddhi Virendra Galande, Shreya Vinod Galande, Chanchal Suresh Khandarkar

Abstract: Wearing face masks is a recommended preventive measure to curb the spread of infectious diseases, particularly SARS-CoV-2. Consequently, automated detection of mask usage, including proper placement and mask type, remains a key area of research. Coronaviruses, a vast family of viruses, have significantly impacted public health due to their high transmissibility. To safeguard public health, individuals are encouraged to practice social distancing, maintain hand hygiene, and most importantly, wear face masks. Mask usage has become widespread globally, with densely populated regions, such as India, facing heightened challenges in ensuring compliance. The developed model has undergone through training and validation using a real-world dataset and has been additionally tested on live video streams to assess its effectiveness. The system’s accuracy has been evaluated under various conditions, including different distances, positions, and multiple individuals within a single frame, ensuring reliable and consistent performance.

 

 

Published by: vikaspatanker

Authors: Professor Swati Bagade, Dr. Anamika Jain, Sujata Patil, Anusha Rolla, Vaishanavi Sarangdhar

Abstract: This project presents a security system that helps protect laptops from unauthorized access. If someone enters the wrong password once, the owner receives a notification. After three incorrect attempts, the laptop shuts down automatically to prevent further access. If an intruder manages to log in using the correct password, they will be asked three security questions set by the owner. If they fail to answer correctly, the laptop shuts down again. This system improves security by sending real-time alerts, adding extra verification steps, and preventing unauthorized use while keeping user data private.

 

 

Published by: vikaspatanker

Authors: Professor Yashanjali Sisodia, Om Dongare, Pranav Gaikwad, Risheekesh Gavate, Atharva Dumbre

Abstract: Traveling through jungles and wildlife reserves is an exciting adventure, but it comes with its fair share of challenges—getting lost, struggling to find transport, securing safe lodging, and connecting with trustworthy tour guides. This paper introduces a website designed to solve these problems by offering real-time navigation help, transport details, accommodation options, and immersive cultural experiences. By using technology, the platform ensures a smoother, safer, and more enjoyable journey for travelers. Here, we discuss how the website works, its key features, and its potential to transform jungle tourism.

 

 

Published by: vikaspatanker

Authors: Swati Bagade, Lavanya Vinaykumar Pashine, Mrunalini Kamble, Pranav Jadhav, Abhinash Roy

Abstract: Disasters, both natural and man-made, pose significant threats to human lives and infrastructure. Effective disaster management requires timely response, coordination between government agencies, s, and affected individuals, and real-time data collection. This project proposes a Disaster Management System, which serves as a platform where people in distress can request help and where volunteers, NGOs, and government agencies can respond efficiently.The system will include real-time reporting, resource allocation, and volunteer management features. The platform will support multiple users, including citizens, volunteers, and administrators, with role-based access to ensure efficient operations. The proposed system aims to improve disaster response efficiency and enhance communication during emergencies.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Manisha Wasnik, Jay Burde, Shreya Tapkir, Apurva Solanke, Yash Burde, Siddesh Tapkir

Abstract: Drying clothes outdoors is a standard household practice, but unexpected weather changes, particularly rain, can cause inconvenience. Traditional drying methods rely on constant human supervision, making them inefficient. This project presents an Automatic Rain Sensor for Clothes, which autonomously detects rainfall and activates a protective covering to prevent clothes from getting wet. The system is designed with a rain detection sensor, a microcontroller, and an automated covering mechanism. When rain is detected, the microcontroller signals the system to deploy the protective covering. Once the rain stops, the cover retracts, allowing clothes to resume drying. This project emphasizes affordability, energy efficiency, and quick responsiveness to changing weather conditions.

 

 

Published by: vikaspatanker