Authors: Prof. Kirti Randhe, Atharva Kendale, Siddhesh Bhargude, Shantanu Thorat

 

 

Abstract: – With the proliferation of digital technologies, cyber threats have become increasingly complex, dynamic, and difficult to mitigate using traditional defense mechanisms. Artificial Intelligence (AI), encompassing machine learning (ML), deep learning (DL), and Natural Language Processing (NLP), has emerged as a transformative force in modern cyber security systems. This survey presents an in-depth exploration of how AI is revolutionizing the landscape of cyber defense. We analyze key AI techniques, their applications in intrusion detection systems (IDS), malware analysis, phishing detection, threat hunting, and anomaly detection. Additionally, the paper explores real-world deployments, benefits, challenges, and the future trajectory of AI-driven cyber security solutions. The study integrates insights from over ten recent peer-reviewed sources and proposes future research directions in explainable AI, adversarial robustness, and real-time edge-AI models.

DOI: http://doi.org/

 

 

Published by: vikaspatanker

Authors: Vishwajeet Kadlag, Rohit Chavan, Atharva Fulware, Tejas Khirad

Abstract: Access to clean and safe drinking water remains a pressing challenge, especially in rural and developing regions. Traditional chemical coagulants like alum are effective in water treatment but can pose health risks and environmental concerns. To provide a safer and eco-friendly alternative, we explored the use of Aloe Vera as a natural coagulant for the treatment of potable water. Aloe Vera contains bioactive compounds such as polysaccharides and glycoproteins, which facilitate the coagulation process by destabilizing suspended particles. In this project, raw water samples were treated with Aloe Vera extract, and key parameters such as turbidity, pH, and microbial load were monitored. The results demonstrated significant improvement in water clarity and quality, proving that Aloe Vera is a promising natural substitute for chemical coagulants. This method offers a sustainable, non-toxic, and cost- effective solution suitable for rural communities and emergency water purification needs. By promoting the use of plant-based coagulants, the system enhances public health and environmental safety. It represents a step forward in natural water treatment technologies and supports the global move toward green chemistry.

Published by: vikaspatanker

Authors: Dr. Deepti Varshney, Aditya Humbe, Rohan Vanjari, Nidhi Goyal, Om Hole

Abstract: The smart parking system is an advanced problem solution made to improve parking efficiency and user benefit by using sensor technology and mobile web application. The system uses components such as infrared sensors, ID UNO SMD, LCD display, 3.7 V battery, ESP 32, etc to monitor the status of parking spaces in real time. Identifying whether each slot is occupied or vacant. This data is transmitted via sensors on a user-friendly mobile web application. The data will be based on no. of parking slots available in the parking. The application provides on time updates on parking slots availability, allowing users to easily find and navigate to empty parking slot. By reducing time spent for finding parking, the system lowers fuel required and minimizes environmental impact.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Sangeeta Mohapatra, Sujay Pardeshi, Abhishek Nimbalkar, Santoshi Nelwade, Suhani Muke Divisha Patel

Abstract: Neighbourhood Connect is an innovative networking application designed to faster stronger community relationships and enhance local engagement. The application provides a digital platform for residents within a neighbourhood to connect, communicate, and collaborate on common interests and initiatives. Key features include a community bulletin board for announcements, chat functionalities for private and group discussions, an events calendar to highlight local activities, and showing availability of rooms. calendar to showcase local events, and a room availability display are some of the key features.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Manisha Wasnik, Jayraj khule, Mayur Mahajan, Tejas Gangrude, Nupur Gambhire, Riya Uchale

Abstract: The offline sale of books has been met with more and more challenges concerning market visibility, accessibility, and consumer engagement in this digitalizing world. This research proposes a mobile application to facilitate transactions between traditional book vendors and the online market, thereby raising their reach and streamlining their sales processes. The application thus provides an easy platform for the buying and selling of books, thereby creating a sustaining ecosystem for book reuse and affordability. It now bestows the vendors with utmost power in terms of modern tools and amenities to com In the ever-evolving retail space against the backdrop of storefronts, secured financial gateways, and inventory monitoring. The digital migration study thus addresses the vendors from a local perspective, operating within a paradigm of enhanced interplay within market corridors, economic engagement, and enhanced consumer experience.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Yashanjali Sisodia, Aryan Chaudhari, Ashish Bhanuse, Aman Kumar Arya, Aryan Rajpoot

Abstract: The purpose of this research paper is to create a website that will help with OPD and healthcare service management. Additional features on the website include video consultation, appointment scheduling, patient medical records, billing, and follow-up. The study assesses how well a website improves patient satisfaction, cuts down on waiting times, and eliminates needless crowding.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Yashanjali Sisodia, Suraj Doke, Kaustubh Chaure, Shivam More, Sanskar Dhayade

Abstract: The increasing demand for social interaction and entertainment has led to the development of intelligent platforms that facilitate spontaneous connections in public spaces. Our Social Meetup and Movie Booking Platform integrates location-based services, AI-driven recommendations, and secure communication to provide users with seamless social experiences. By leveraging artificial intelligence and real-time data, the platform ensures personalized meetups, enhancing social engagement while prioritizing security and privacy. Additionally, the system is designed to be user-friendly, making it accessible to individuals with varying levels of technical expertise. This paper outlines the system architecture, methodology, implementation, and ease of use of our platform.

 

 

Published by: vikaspatanker

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