All of the articles in this proceedings volume have been presented at the [ICAAAI 2025] during [February 27th & 28th, 2025] in [Shri Shankaracharya Institute of Professional Management and Technology, Raipur, Chhattisgarh, India]. These articles have been peer reviewed by the members of the [Technical...

We introduces a hybrid model that combines homomorphic encryption and Generative AI (Gen AI) to address the growing security and ethical concerns surrounding modern data protection. In today’s data-driven world, maintaining the confidentiality, integrity, and privacy of sensitive information is more...

Many aspiring musicians face challenges in creating their own music due to the high cost of equipment and the complexity of learning music theory. These barriers make it difficult for beginners to express their creative ideas, leading to frustration and disappointment. To address this issue, we propose...

Automatic image captioning in Indian languages like Hindi presents unique challenges due to the complex grammar and lack of large-scale datasets compared to English. This research introduces a new way of generating Hindi image captions using a pre-trained DenseNet121 as an encoder and a transformer as...

This work investigates the usage of deep learning algorithms for automated identification and recognition for plant leaf diseases to improve plant sprig health management. Food security and global agriculture are under grave risk due to the spread of plant diseases. In order to create effective mitigation...

Sentiment analysis has become a very useful tool for understanding user feedback and sentiment expressed on social media platforms. This study focuses on analysing comments to classify sentiment using various ML and DL models, including RF, K-Nearest Neighbours (KNN), LR, Decision Trees, NB, and Long...

The process of importing coal into industries faces critical challenges, compromising efficiency, accuracy, and quality control. Weight discrepancies often occur between challan-reported quantities and actual deliveries due to transit losses or moisture, making inventory management complicated. Even...

Advances in deep learning have fundamentally changed how cancer is diagnosed and treated. These cutting-edge models show great promise for boosting therapeutic approaches and increasing diagnostic accuracy, launching a new age of individualized cancer treatment. These days, sophisticated methods like...

The EduVibe is a cutting-edge platform that is revolutionizing education by overcoming the drawbacks of both digital and conventional learning. It adapts content to each student’s unique learning preferences, requirements, and development, providing focused assistance to help them succeed. Modern technology...

Here’s a clearer and more concise version of the abstract: This study presents a robust helmet detection system using computer vision techniques and the YOLOv5 model. Using Attributed to Table (VTT), we aim to identify motorcycle riders who violate safety regulations by not wearing helmets, thereby endangering...

Accident prevention and safety assistance using Internet of Things (IoT) technology is becoming increasingly important as road accidents continue to pose a significant threat to human life. This paper proposes an IoT-based system to improve road safety by monitoring drivers’ behavior and detecting risky...

The appropriate fusion of cutting-edge technology with widespread network coverage guarantees a pervasive marketplace. Our initiative provides employment opportunities for individuals by creating a user friendly platform where they can monetize their hobbies. People can exchange their abilities on this...

In contemporary healthcare, when medical imaging is essential to early detection and action, an accurate and fast disease diagnosis is crucial. DL models include convolutional neural networks (CNNs), have shown impressive performance in automating image processing tasks such as anomaly detection and...

In the recent times, image captioning had achieved widespread interest in the field of natural language processing. With the booming advancements in deep learning, there is a huge scope for the development in image captioning using deep learning. The proposed research addresses the challenges faced by...

The global burden of oral cancer continues to be a major challenge in the field of health, which demands the development and establishment of efficient diagnostic methods. This study introduces a novel ensemble model that harnesses the benefits of two best-performing convolutional neural networks in...

Artificial Neural Network is more interesting than what it just seems to be. The new world of inventions and innovation, all the possibilities opened up due to a simple arrangement of neurons in layers is stunning. The scope even widens up when the internal structure of the ANN or CNN is untangled. The...

This study compares the presentation of Logistic Regression and CNN approaches for image classification using the Animal-10 dataset, which comprises ten distinct animal categories including horse, elephant, dog, butterfly, hen, cat, sheep, spider, cow, and squirrel. To classify photos as either dogs...

Creating and delivering products that fully meet the expectations, which turn more complicated with time, of the highly competitive environment of flight companies has been and still is a major challenge in the aviation industry as sustainability transformation is getting increasingly dependent on airline...

Frequently occurring seizures are a hallmark of epilepsy, a persistent brain illness. Standard diagnostic modalities, such as electroencephalograms (EEG), magnetic resonance imaging (MRI), and clinical examinations, have limitations in terms of efficacy, spatial resolution, invasiveness, cost, and interpretative...

As Internet of Things (IoT) technology expands, there are numerous ways to transform protection and twist of fate prevention. This paper gives a brand new IoT-primarily based twist of fate prevention device designed to growth accident recognition and reduce injuries. The machine integrates smart sensors,...

In this paper explores the purpose for deep learning algorithms in the early recognition of cardiovascular diseases (CVDs). With CVDs being a indicating source of transience worldwide, early diagnosis is critical for successful treatment and prevention. In order to locate feasible risks and early signs...

This paper explores the application of artificial intelligence (AI) in predictive preservation for railway systems. As rail networks become an increasing number of extra complexes, the need for inexperienced and reliable preservation strategies grows. Predictive preservation, powered through manner of...

Face recognition technology has garnered a lot of interest because of its vast range of applications and potential market. Digital video processing, security systems, and many other technological advancements are among the numerous industries in which it is being used. A person’s emotions are also recognized...

Course Outcome Analysis (COA) is crucial for evaluating and improving educational effectiveness. This study aims to classify course outcomes and identify areas for improvement using ML models like D.T. (Decision Tree), R.F. (Random Forest), and L.R. (Logistic Regression) models got applied to historical...

The Raisin Dataset contains the morphological data for two different raisin varieties of Kecimen and Besni and forms the very basis of an essential approach to classification methods in agriculture and food science. This deals with the effort of a machine learning algorithm in the feature-based classification...

The liver is one of the vital organs in the human body, playing a crucial role in metabolism, maintaining blood sugar levels, aiding digestion, and storing vitamins and minerals. It is the largest organ, weighing about 3 pounds and roughly the size of a football. However, liver diseases such as hepatitis,...

This research explores how a product recommendation system can incorporate sentiment analysis with the help of web scraping tools such as Selenium. Its main goal is to streamline the process of collecting product ratings, evaluating customer reactions, and improving marketing tactics. The methodology...

Coal transportation involves a complex network of systems, including trucks, trains, and ships, where inefficiencies arise due to fragmented processes and lack of integration. This study introduces a unified digital platform leveraging supply chain management principles to address these challenges. The...

Cardiovascular diseases are a major burden to health systems in the world and are the leading cause of death and morbidity. Disease diagnosis is a critical component in disease management and prevention, if is done correctly within the shortest time. However, routine medical practices from time-to-time...

The primary impact of communication barriers on the lives of many deaf or hard-of-hearing individuals lies in their ability to understand and comprehend most spoken languages. Accordingly, this paper presents an effective system which can convert speech to Indian Sign Language (ISL) via images and gifs....

Face recognition-based attendance systems offer a modern and efficient alternative to traditional attendance tracking methods. However, existing systems face challenges related to accuracy, security vulnerabilities, and adaptability to different environments. This paper increases the scale and scope...

Globally, biophysical environment, human health, and economic processes are threatened by the deteriorating quality of water. Since water quality data is often complex, non-linear and cross-dependent, most of the typical prediction models fail to deliver an accurate outcome. Improving the predictive...

The research paper focuses on studying in-depth procedures that machine learning techniques combine with deep learning and Natural Language Processing (NLP) methods to develop speech recognition models. The remarkable progress made with speech recognition technology caused it to become an important element...

These results from the Solar Power’s stochastic nature, the forecasting on how much this electricity source will contribute at any particular time is very important in managing the grids. When it comes to the first generation of machine learning models, they are safe and accurate but have limitations...

A personalized healthcare recommendation engine is a strong machine learning system that enables a user to determine probable diseases and recommend measures on health care. It accepts the user’s symptoms and can predict diseases using various models like support vector machines, random forests, and...

Most screening tools for Autisum Spectrum disorder are questionnaire-based and rely on subjective responses by caregivers. While behavioral observation provides an objective approach, these usually come quite pricey, very time-consuming, and technically demanding. That is why there is a great demand...

Predicting house prices accurately is a complex challenge due to various influencing factors. This study compares multiple machines learning models, including Linear Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), and Neural Network, to determine the most effective approach for...

Indian Railways has relied on conventional announcement systems for many years, but the need for a more inclusive solution for passengers who speak only regional languages remains largely unaddressed. This paper presents the development of a real-time translation engine, powered by AI, to translate announcements...

BharatLex is an AI-driven chatbot designed to enhance access to legal information, offering legal query resolution, court judgment summaries, and document-based information retrieval. Supporting the Indian Constitution, it ensures inclusivity across India’s linguistic diversity. Leveraging advanced Large...

CareerCraft is an AI-driven career counselling platform that leverages the K-Nearest Neighbour (KNN) algorithm to provide personalized career recommendations for secondary-level students. By analyzing skills, interests, and preferences, the platform predicts suitable job roles with an overall accuracy...

The credibility of digital media has been significantly threatened due to advanced Artificial Intelligence techniques which are generally known as Deepfake, endanger the authenticity of audio-visual media. This paper presents an enhanced approach for identifying deepfake. This project utilizes a detection...

A Multi Disease Prediction System, or MDPS, uses cool machine learning methods! We focus on algorithms like Logistic Regression & Support Vector Machines (SVM) to predict specific diseases. Imagine a tool that’s easy to use; that’s made possible with the Streamlit library. The main goal? To create...

With the increased popularity of massive open online courses, ensuring active engagement of the students is a prime challenge. This proposed system tries to address that need by proposing an automated mechanism for detecting a disengaged student during the online class. Advanced algorithms of machine...

Metastatic osteosarcoma is the most common form of bone cancer in children and has a poor prognosis, particularly at advanced stages. Early detection is necessary to minimize the ability of malignant cells to spread and to reduce death rates. Despite various factors, such as bone tissue damage, degradation,...

This paper discusses the development and implications of virtual assistants AI, following their development from simple rule-based systems to sophisticated applications driven by cognitive computing, machine learning, and natural language processing. The paper discusses technology developments that catapulted...

The rising incidence of cancer globally highlights the urgent need for more accurate and early detection methods. This research initiative proposes a dual approach: first, the development of a state-of-the-art machine learning model trained to identify cancerous cells with high precision; second, the...

Image captioning represents a convergence of computer vision along with natural language processing, with the objective of creating an effective image caption generator through deep learning methodologies. This process entails annotating images with English keywords by employing datasets during the training...

In todays digital world, online safety is more crucial than ever, especially with the growing concern of cyberbullying this project present a design to prevent aggressiveness in social media interaction by identifying and blocking offensive content in social media. The rapid evolution of AI offers transformative...

The The design entitled “Fauget 3D modelling app using Augmented Reality and Virtual Reality (ARVR)” helps us enter into the new emerging tool ARVR technologies in the realm of apparel and jewelry retail. In recent times, the fashion assiduity has experienced a digital metamorphosis, with ARVR arising...

Extension of the sign language that helps to overcome the communication barrier for hearing impaired as well as speech impaired people has been presented in the form of the proposed multi-purpose smart glove for converting sign language to speech translation. This glove combines different sets of sensors...

This study examines the vital role of cryptography in maintaining data security, particularly with the integration of Artificial Intelligence (AI) and Artificial Neural Networks (ANN), in light of the increasing reliance on the Internet for communication and data sharing. It emphasizes key elements of...

This study explores the integration of machine learning techniques with multi-factor authentication (MFA) systems to enhance user verification, security, and usability. Recognizing the vulnerabilities of single-factor authentication methods, we propose an MFA framework combining three distinct verification...

This research focuses on leveraging deep learning models to detect grape leaf diseases with high precision and accuracy, addressing a critical challenge in the viticulture industry. Analyzing a dataset of 5779 training images and 360 test images, a deep learning model based on convolutional neural networks...

Critical issues in inventory and supply chain management for drug tracking within healthcare systems are examined in this paper, focusing on ensuring timely drug delivery, reducing wastage, and improving patient safety. Traditional methods of inventory management have always been plagued with the issues...

This paper analyzes the potential for change that a digital eMarketplace for legal services in India offers. The platform aims to address the inadequacies in traditional legal structures by using AI to enhance accessibility, transparency, and operational efficiency. The objectives include bridging the...

The trade-off between accuracy and efficiency is a fundamental principle in computer science, shaping advancements in fields such as hardware design, image processing, and approximate computing. This trade-off is particularly significant in distributed machine learning (ML) systems, where optimizing...

Agriculturist Merchant is a computerized stage planned to back country agriculturists by giving coordinate advertise get to, permitting them to offer their items specifically to customers and the nourishment handling industry. The stage leverages Manufactured Insights (AI) to optimize real-time estimating,...

This study explores the transformative role of mobile applications in empowering smallholder farmers by addressing key challenges such as restricted access to real-time agricultural information, inefficient market linkages, financial exclusion, and suboptimal resource utilization. The research highlights...

In today’s fast-paced world, managing finances efficiently is essential yet challenging due to the complexity of tracking various expenses such as travel, subscriptions, and budgets. Expensify Pro aims to simplify financial management by providing an automated expense tracking system that minimizes manual...

In this paper, a machine learning-based system for detecting vehicle safety is presented. The primary objective is to monitor and detect driver drowsiness in real time using face detection techniques. The main aim of this project is to identify signs of drowsiness, especially through eye behavior, as...

Integrating Machine Learning (ML) and the Internet of Things (IoT) into healthcare delivers transformative potential by enabling real-time monitoring and predictive care. This study introduces a smart healthcare system that employs IoT sensors to monitor vital parameters such as heart rate, oxygen saturation,...

The ecological significance of reef-building coral reef ecosystems in warm shallow waters has been brought to light in recent years by developments in environmental research and marine resources. For the protection of ecosystems, monitoring marine animal populations is essential. Real-time environmental...

Crop infection categorization is crucial for detecting disease causes, understanding disease development patterns, and determining the extent of hazards to crops. Categorizing infections by pathogen type provides valuable insights into disease spread and aids in suggesting effective control measures....

The texture is the basic factor in an image, representing each layer of the image. Hence, texture analysis is considered asa fundamental process for various computer vision operations including segmentation, image retrieval, and image recognition. Several current applications demand an effective texture...

Gait recognition is a modern form of biometric identification that utilizes the walking mannerisms of a specific person. Compared to conventional biometrics, gait recognition has low intrusion and can work with identification from a distance, and that is why it is applicable in fields like surveillance,...

Hindustani music and Carnatic music are the two main schools of Indian classical music. Basically, Indian music includes microtones (shruti), notes (swaras), ornamentations (alankar), melodies (ragas) and rhythmic patterns (tala). There is a vast interest developed among individuals to learn Indian music...

Communication is a cornerstone of human interaction, yet individuals with hearing and speech impairments face significant barriers in daily life. Over 430 million people worldwide experience disabling hearing loss, many relying on sign language as their primary mode of communication. This creates a substantial...

The aim of the project, “A Unified Portal for Developing a Model Curriculum for All AICTE-Approved Institutes,” is to create a unification, well-organized, and customizable digital platform to smooth curriculum development across higher education institutions in India. This drive mark the various and...

Knee osteoarthritis (OA) is a common degenerative joint condition that affects millions worldwide. Effective therapy requires early diagnosis and precise staging. The study introduces OA-Net, a sophisticated Convolutional Neural Network (CNN) framework intended for multi-stage knee OA severity classification...

This paper introduces an advanced autonomous navigation system utilizing RTAB-Map for simultaneous mapping and localization in the CARLA simulation environment, integrated with ROS2 for efficient data processing. Designed to enable the ego vehicle to autonomously explore and map its surroundings, the...

Diabetes mellitus (DM) is one of the most pressing health problems facing the world today. Chronically elevated blood glucose levels caused by insulin resistance or insufficiency are a hallmark of diabetes mellitus (DM). Serious issues affecting the heart, kidneys, eyes, nerves, and other vital organs...

Forest fires happen to be the most devastating natural calamities, which have serious ecological, economical, and social implications. Early detection and a timely fight are the crux of remedying this malady. Most of the traditional methods of fire detection in forests, which are human observation and...

Phishing attacks have surged in recent years, posing a significant threat to cybersecurity. One of the main strategies used by attackers is to create fake URLs that fool users into giving away their personal information. This paper introduces a novel machine learning model designed to effectively identify...

This work focuses on creating a powerful video compression algorithm tailored for satellite telemetry and GSM systems. The main goal is to optimize compression strategies for low-bandwidth systems without sacrificing video quality, which is crucial for resource-intensive networks like GSM and satellite...

The difficulties of predicting home prices in real estate investing, economic forecasting, and urban planning are discussed in this paper. As machine learning (ML) has developed, more sophisticated techniques like neural networks, random forests, and deep learning models have overtaken more conventional...

The agricultural sector serves as a fundamental pillar of India’s economy; however, it is currently confronted with significant challenges, including climate change impacts and soil quality deterioration. This paper presents an innovative crop recommendation system that leverages machine learning techniques,...

Current day companies can neither understand nor predict the marketing events. Any management will find it really difficult to survive in that particular field if detailed and regular data analysis is not done. Using a few machine learning techniques. Can be used to demonstrate visualization of current...

Existing grievance redressal mechanisms have long been plagued by departmental silos, slow responses, and a lack of openness, creating obstacles for individuals seeking to address their concerns with government bodies. This study introduces an artificial intelligence-driven solution that tackles these...

The detection of vehicle registration plates is a critical component in applications such as traffic monitoring, law enforcement, and automated toll collection systems. This project focuses on the development of a robust and efficient system for detecting and extracting vehicle registration plates from...

The integration of artificial intelligence (AI) into human-computer interaction has revolutionized various fields by enabling seamless interaction between users and machines. This research aims to design a standard image recognition chatbot that leverages the synergy of Computer Vision (CV) and Natural...

This research paper provides an in-depth exploration of the evolving role of Municipal Finances and Tax Management Systems (MFTMS) in transforming the financial management practices of local governments. It examines how these systems contribute to enhancing efficiency, transparency, and accountability,...

Automatic License Plate Detection (ALPD) plays a crucial role in intelligent transportation systems, law enforcement, and security applications. This paper presents an efficient ALPD methodology utilizing the YOLO (You Only Look Once) deep learning model for real-time and high-accuracy detection of license...

It focuses on using artificial intelligence (AI) to improve inventory management in pharmacy stores. The project addresses inefficiencies in traditional systems by leveraging machine learning (ML) techniques such as time-series forecasting, regression models. The system predicts demand, optimizes stock...

In the world, Skin cancer is the predominant cause of mortality from cancer-related conditions. However, the manual diagnosis of skin cancer continues to present challenges, despite the fact that timely detection significantly enhances the likelihood of effective treatment. The objective of this study...

This research investigates the effectiveness of the Community-Based Reporting and Monitoring Tool for Women Safety in Colleges, addressing the issue of sexual violence among young women as they pursue higher education. Though much progress has been made concerning women empowerment at the college level,...

This study explores the transformative role of machine learning (ML) and artificial intelligence (AI) in optimizing vendor transportation management, a critical aspect of supply chain logistics. Traditional systems struggle with inefficiencies in route planning, unpredictable demand, and fluctuating...

Freelancing platforms have revolutionized the gig economy by offering flexible and accessible employment opportunities across the globe. This study aims to evaluate the economic impact, technological advancements, and challenges faced by users of platforms like Upwork, Fiverr, and Freelancer.com. Using...

Extreme weather conditions such as storms, heavy rain, and heat bring danger to people, equipment, and the environment. Therefore, this project looks at an Extreme Weather Prediction and Alert System that uses machine learning algorithms to predict these events and send alerts in real-time. In this case,...

Smart Roads Networks (SRNs) that manage roads by intelligently de-congestion streaks and promoting smart urban projects benefit a great deal from receiving accurate and efficient forecasting traffic. CNN is the secret math; it is most useful for expressing space-temporal data. This study proposes a special...

The Emotion Detection web application is a powerful tool designed to analyze and interpret human emotions from diverse data inputs, such as text, images, video files, and live video feeds. It leverages a fine-tuned RoBERTa model for emotion analysis in text and a custom convolutional neural network (CNN)...

A binary classification model was analyzed for its performance measurements of depression, suicide, anxiety, PTSD and bipolar disorder. Each mental health condition was evaluated through precision and F1-score indicators to measure model performance with accuracy as an additional evaluation factor. Performance...

Research and development of artificially intelligent humanoid robots remains an exciting area. Since their initial introduction, humanoid robots have advanced significantly and are currently used in a wide range of sectors. Humanoid robots have limitless potential in theory, but real-world application...

Predictive maintenance, failure detection, and improved customer assistance are some of the ways that machine learning (ML) integration changes home appliance services. Appliance performance data is analysed using both supervised and unsupervised machine learning approaches, including clustering and...

Preparing for job interviews is often a challenging and stressful process, especially when candidates are uncertain about the types of questions they may face or how their responses will be evaluated. This research introduces an advanced AI-based tool designed to simulate real interview scenarios, helping...

Stray animals face significant challenges, including abandonment, neglect, and limited access to care. Research reveals that traditional rescue methods are hindered by fragmented communication, inefficient reporting systems, and insufficient community involvement. This study analyses the current state...

Blockchain technology is transforming the medical field by offering a safe and Separated and an impenetrable structure for managing patient data and information. Traditional healthcare data storage Techniques are susceptible to security lapses and illegal access and inefficiencies, leading to compromised...

Optimizing computational performance through efficient pipelining scheduling is crucial for high-performance and real-time applications. This paper introduces an AI-driven framework for benchmarking various scheduling algorithms, utilizing machine learning to enhance efficiency and optimize resource...

Super-resolution (SR) is a crucial task in computer vision, aimed at generating high-resolution (HR) images from low-resolution (LR) inputs. Traditional techniques, such as interpolation-based and reconstruction-driven methods, often struggle to recover fine details, re- sulting in blurred and low-quality...

With the increased pressure for environmental conservation concerning our planet, there is a great need for energy and water preservation, particularly in home appliances. This research is devoted to examining sustainable innovation in refrigerators, air conditioners, washing machines, and desert air...

Food waste phenomenon is massively racing across the world, 1/3rd of food produced for human consumption wastes in competition with our Food and Agriculture Organization. This staggering total accounts for approximately 1.3 billion tons of food wasted per year. Meanwhile, the World Health Organization...