Published papersfrom researchers in 60+ countries.
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Smart Fire Detection and Response System
This paper presents the design and development of an IoT-based smart fire detection and autonomous fire-fighting robot using the ESP32 microcontroller. The system aims to reduce human risk in hazardous environments by enabling early fire detection and automatic suppression. It integrates multiple sensors, including flame sensors, a temperature sensor, and an ultrasonic sensor, to accurately detect fire and navigate obstacles. The ESP32 processes real-time data and controls the robot’s movement through a motor driver while activating a water pump via a relay module to extinguish fire. A servo motor ensures directional water spraying for effective suppression. Additionally, IoT connectivity allows remote monitoring and manual control through a mobile application. Experimental results demonstrate reliable performance, fast response, and improved safety, making the system suitable for residential and industrial applications.
srijan manna · mumbai
Attendo: An IoT-based Smart Attendance System Using Biometric Edge-to-Cloud Architecture and LBPH Textural Analysis
The administrative workflow for student attendance tracking in higher educational institutions has historically relied on manual roll calls and physical sign-in sheets, methods that are inherently inefficient, time-consuming, and prone to the pervasive security vulnerability of “proxy attendance” (buddy-punching). This project presents “Attendo,” an integrated IoT-enabled smart attendance system designed to automate the authentication process using contactless facial recognition. The research addresses the “Security Usability-Cost Trilemma” by synthesizing low-cost edge-computing hardware with enterprise-grade cloud-native software architectures. The hardware architecture centers on a custom-fabricated Printed Circuit Board (PCB) integrating a standard ESP32-CAM microcontroller, a Passive Infrared (PIR) sensor for energy-efficient presence detection, dual LED status indicators, and a dedicated push-button triggered biometric capture pipeline. By leveraging a hardware-interrupt driven state machine, the edge node minimizes baseline power consumption to approximately 2.5mA in deep sleep while ensuring deterministic acquisition of VGA-resolution (640×480) JPEG matrices via the onboard OV2640 CMOS sensor. The software ecosystem is engineered on a distributed PERN (PostgreSQL, Express, React, Node.js) stack, utilizing AWS S3 buckets for scalable and persistent image blob storage. To accommodate the resource constraints of edge environments, computationally intensive bio metric processing is offloaded to a dedicated Python-based vision microservice. This microservice employs Haar Cascade classifiers for precise facial localization and the Local Binary Pattern Histogram (LBPH) algorithm for texture based feature extraction. By projecting micro textural patterns into concatenated spatial histograms, identity verification is executed efficiently using a strict Chi-Square (χ2) distance metric against pre-computed vectors securely stored in the PostgreSQL database.
Tejas Shinde · Vishwaniketan's Institute of Management Entrepreneurship and Engineering Technology
- Computer ScienceIndia
Snakebite Detection and Treatment Using AI
Snakebite envenomation remains a critical public health challenge, particularly in rural and resource-limited regions where timely diagnosis and treatment are often unavailable. Traditional diagnostic methods rely heavily on clinical symptoms and patient history, which can lead to delays and misclassification. This research introduces an AI-driven snakebite detection and treatment system that leverages machine learning and computer vision to classify snakebite images into specific snake types and recommend appropriate treatment protocols. The model is trained using convolutional neural networks (CNNs) and deployed via the Django framework, ensuring accessibility through a user-friendly interface.
KOMAL SINGH MARKAM · Parul Institute of Engineering and Technology, Parul University, Vadodara, India
- EngineeringIndia
Smart Healthcare Blockchain Platform
Our project is on blockchain which is used in healthcare , as we know people travel over different country , if in case any accident happens and patient runs to the near by hospital .In that case our app will help them in medical history of patient . it provides the records of patients to doctors which patient will give access from our app .. then doctors will know about the patients history is they have any serious problems previously , and according to that the treatment will perform to patient .
Vidhi Prashant Patil · A.C .Patil College of Engineering / Mumbai University
Enhancing Manufacturing Supply Chains through Improved Visibility and Collaboration Using Artificial Intelligence within the Industry 5.0 Paradigm
This paper seeks to explore and transition Industry 4.0 to Industry 5.0 concept among Indian manufacturing industries and their supply chains. Many industries have forecast that the future of operations in supply chain management (SCM) may change steadily dramatically, from planning, scheduling, optimisation, to transportation, with the presence and integration of artificial intelligence (AI). Although the integration of Artificial Intelligence (AI) into supply chain management has emerged a pivotal role in enhancing efficiency and resilience in industries operations. The paper delves into integrating of AI in SCM processes strengthening supply chain resilience including improving data sharing, enhancing real time visibility and ensuring smooth communication among partners. With the technological advancement we tried to build a AI interface which uses real time analytics and secures collaboration to fix poor visibility and drive efficiency across complex manufacturing supply chain. It ensures the interface is User Centric and Effective in solving the core visibility and collaboration problem.
Keshav Arun Tyagi · Vishwaniketan's Institute of Management Entrepreneurship and Engineering Technology
Swastyasathi AI: An ABHA-Aligned, AI-Enabled Digital Health Platform for Integrated Clinical Documentation, e-Prescribing, and Longitudinal Patient Record Access
Swastyasathi AI is an ABHA Card revolutionary Initiative. It aims to make Abha card to be practiced in each and every hospital. Making it accessible for each and every individual to track health record.
Divyesh Potawde · Mumbai University
- Computer Engineering Indai
DreamJobApp: Job Matching Application
DreamJobApp is an intelligent, centralized platform designed to streamline the tracking of job applications and mitigate the complexities of the modern recruitment process. By providing a structured digital environment, the system enables users to efficiently manage job listings, corporate metadata, application deadlines, interview milestones, and final selection outcomes. Its modular architecture ensures optimal data storage, low-latency access, and seamless scalability, while robust database connectivity and secure authentication protocols guarantee the accuracy and reliability of all user records.
CHAITANYA ANKUSH SATHE · Vishwaniketan college
- Computer ScienceIndia
Expansion.AI: A Globally Scalable AI-Driven Decision-Support Framework for Autonomous International Market
International business expansion is a high-stakes strategic process requiring the synthesis of fragmented data across regulatory, economic, and competitive domains. Traditional expansion strategies rely on human-centric consultancy, which is often cost-prohibitive for Small and Medium Enterprises (SMEs) and prone to cognitive bias. This paper introduces Expansion AI, an integrated decision-support framework that leverages Multi-Criteria Decision Making (MCDM) and Explainable Artificial Intelligence (XAI) to automate global market evaluation. Utilizing real-time data from the World Bank, WTO, and UN Comtrade, Expansion.AI generates transparent, data-driven recommendations that reduce the time-to-insight for strategic planning by over 70%.
Shivani Mangesh Bhosale · University of Mumbai
- Computer ScienceIndia
Sketch2Animate
Sketch2Animate is an AI-driven system designed to automatically transform hand-drawn sketches into animated sequences with minimal human intervention.
DHIRAJ MANGESH RUPVATE · UNIVERSITY OF MUMBAI
VITA: Visual Intelligent Teaching Assistant
This paper introduces VITA (Visual Intelligent Teaching Assistant), an artificial intelligence–driven system for the automatic generation of animated mathematics explanations. Conventional methods for creating visual educational content are often time-intensive and require specialized skills, limiting their scalability and accessibility. VITA addresses this limitation by enabling users to submit mathematical queries through a simple interface, which are then interpreted using a Large Language Model (LLM). The system converts these queries into executable animation scripts using the Manim library, producing step-by-step visual explanations that may be supplemented with narration. By transforming textual queries into dynamic visual content, the proposed approach enhances conceptual understanding and supports personalized learning experiences. Despite challenges related to computational cost and script accuracy, the system demonstrates strong applicability in digital learning environments. VITA offers a scalable and efficient solution for automated visual instruction in mathematics.
Manan Patil · Vishwaniketan’s Institute of Management Entrepreneurship and Engineering Technology (iMEET), Khalapur, Raigad, Maharashtra 410202, India.
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