All of the articles in this proceedings volume have been presented at the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE’24) during 30th & 31st December 2024 at New Prince Shri Bhavani College of Engineering & Technology, Chennai, Tamil Nadu, India....

Temporo-mandibular joint disorders (TMDs) are a multifaceted group of excruciating disorders which impact masticatory muscles along with temporomandibular joint. It is a collection of musculoskeletal conditions which affects the temporo-mandibular region. TMD symptoms include jaw pain, tenderness, and...

Introduction with e-Government Anticipating the involvement of electronic systems by organizations on a wider scale, e-Government was born out of necessity. But, current frameworks are primarily centralized constructs and are prone to cyberattacks and data breaches. A decentralized e-Government framework...

The rapid evolution of autonomous transportation networks and smart mobility solutions has necessitated the integration of adaptive artificial intelligence (AI) models to enhance public engagement, optimize traffic flow, and ensure predictive traffic management. This research proposes a human-centric...

These two-wheeler traffic violations in low-light conditions are a major issue in traffic management and road safety. Current methods are mainly focused on one segment of the pipeline (e.g., object detection, low-light enhancement, or reinforcement learning) while failing to incorporate them into a single...

In this paper, we propose a novel lightweight attention-based object counting system for inventory management using the YOLOv7 object detector model. It aims to enhance real-time and operational efficiency in changing environments while having improved performance accuracy for small and overlapping objects....

Artificial Intelligence and Machine Learning enabled smart cities have become a crucial part for the development of a country, it allows the data to be gathered in such a manner which gives track of all the records. This study focuses on these smart cities in to collect information which can be helpful...

Although gamification in education has been extensively studied, most of the studies published to date are primarily concerned with the short-lived nature of student engagement, lack adequate real-world empirical validation, and/ or do not incorporate artificial intelligence (AI). In this study, we introduce...

Artificial intelligence (AI) is a rapidly evolving field that opens new doors for advancing sustainability initiatives. But, the current AI sustainability models are narrower in focus, tend to be domain-specific, lack a scaling aspect to them, and often a real-world implementation context. We present...

AI-enabled platforms disrupt the financial system, labor market, and global policy, providing new platforms for inclusive economic growth. This study investigates the promises of AI solutions to reduce the economic divide, improve productivity, and enable sustained equity in both developed and developing...

Sentiment analysis allows you to understand how users are engaging with you on social media. Traditional sentiment analysis techniques, while effective in controlled environments, do not handle the dynamic nature of social media, resulting in a limited ability to predict engagement patterns. Our study...

A research project aimed at ascertaining how the most advanced technologies are integrated into enhancing agricultural productivity and sustainability is conducted. The study utilized satellite imagery to analyze key factors determining crop production that can be condensed into three key areas, namely:...

Diagnosing ACL tears is challenging due to variable presentations and limited diagnostic tools. This study evaluates methods such as Magnetic Resonance Imaging (MRI), clinical evaluation, arthroscopy, and advanced machine learning (ML) models. MRI, the gold standard for ACL diagnosis, is noninvasive...

A degenerative joint disease that often involves the knee, osteoarthritis (OA) leads to pain, stiffness, and reduced function. OA can tighten the iliotibial (IT) band a fascia that runs from the knee to the hip resulting in pain and limit mobility and range of motion (ROM). Directly related to this concept...

AI-based supply chain management (SCM) is a game changer enabling logistics optimization, transparency improvement and sustainable trade. Specifically, the research notes that AI guided platforms have the possibility of achieving advanced proactive analytics, assist decisions, and lower the risks throughout...

The pervasive increase in urbanization and technology has so far-in the light of insufficient bureaucracy structure-meant administrators to work to rely on AI based predictive norms for prompt resolution of real-time civic engagement. Traditional smart city frameworks lean heavily on data but are mostly...

Presenting into AI: the face of AI in tourism. This study allows to further explore how a Smart tourism phenomenon affects the tourism system and tourism stakeholders through AI technology-based solutions. AI technologies (for example machine learning, data analytics and augmented reality), help tourism...

Incorporation of Artificial Intelligence (AI) into Energy Management Systems for resource optimization and smart power grid development. While previously, research literature has set a foundation of AI for developing energy solutions, implemented and scale capabilities of practical efforts, like networks,...

Artificial intelligence (AI) technology is advancing at an unprecedented rate, and it has already changed the face of retail and the shopping experience, improving personalization and customer engagement. Fret not as current AI driven solutions for retail tend to be confined to their cause, whether it...

The study examines the potential of Artificial Intelligence (AI) to optimize citizen engagement platforms in creating sustainable urban futures, inclusive policy-making and community-oriented smart government. So, we contribute to a body of literature mainly centred on theory or about a specific AI application,...

AI Driven real-time analytics platforms are revolutionising public engagement, interactive policymaking and digital citizenship innovation. This includes platforms that utilize artificial intelligence (AI) powered insights, collective intelligence, and generative AI to drive better governance and promote...

This study has a primary focus on the use of deep learning and artificial intelligence (AI) in enhancing weapon detection capability in security systems, and this overcomes traditional limitations in dynamic environments. Our method relies upon convolutional neural networks (CNNs) and deep learning models...

Advanced natural language processing (NLP) and machine learning (ML) techniques have been integrated into clinical systems paving the way for transformative healthcare solutions. In this paper, we will introduce a unified framework utilizing BioBERT, DialogGPT, FAISS search, and LightGBM to bridge important...

Governance systems are increasingly being transformed to digital technologies, making the need for secure, transparent, and efficient citizen engagement models more important than ever. However, the traditional digital governance frameworks have a number of challenges like lack of trust, data privacy...

By integrating blockchain technology through citizen collaboration models, there is also an opportunity for smart urban innovation, participatory governance, and secure digital identity management. They are typically centered around decentralized, transparent, and citizen-centric frameworks that promise...

Specifically, the technology that holds the most promise for public participatory platforms within the framework of the Sustainable Development Goals (SDGs), is blockchain. Scalability, energy consumption, regulatory uncertainty, and integration complexity challenges do not mitigate the capacity of blockchain...

Significant improvements have appeared in breast cancer detection by using machine learning (ML) as well as deep learning (DL) technologies. They are very useful in enhancing the efficiency, accuracy and accessibility of breast cancer detection. Various machine learning models, including support vector...

Muscular imbalance disorders like upper crossing syndrome are related to numerous types of referred ailments, most particularly discomfort in the jaw. It includes difficulty in opening and closing the mouth. This is associated with temporomandibular dysfunction. Measuring and tracking elements on a computer...

This research focus on the comparative learning process of neural networks and human brain, exploring the accuracy trends influenced by parameters like noise complexity, learning speed and decay frequency. Using a System Dynamics Model (SDM), the simulation of evolution of neural network and human accuracy...

One common musculoskeletal problem is tight hamstrings, which can reduce flexibility, raise the risk of injury, and impair performance in general. College students are particularly prone to hamstring tightness, especially if they lead sedentary lifestyles or participate in sports. Static stretching has...

The rapid advancement of blockchain technology presents new opportunities for equitable civic engagement and transparent digital policy implementation in smart cities. However, existing research lacks empirical case studies, real-world implementation frameworks, and comprehensive integration with emerging...

Blockchain possesses potentially transformative benefits could be a solution to bring transparency, security and citizen empowerment in an age of information when this data is prone to be manipulated and pirated. This paper explores decentralized blockchain empowered citizen participation architectures...

Using predictive analytics on Intensive Care Units (ICUs) has advantages because it shows an early clue of the patience’s critical triangle or deterioration. Supervised learning methods used in deep learning also seem appropriate for large data arrays and intricate structures that are why they are useful...

Knee osteoarthritis (OA) is a widespread degenerative condition impacting millions, predominantly older adults, and frequently resulting in chronic pain and a compromised quality of life. Timely and precise diagnosis is crucial for effective disease management, mitigating its progression, and enabling...

Flooding and landslides are significant destructive natural events to infrastructure and human life. Segmentation of affected disaster areas in satellite and aerial images has an important role in an effective response and mitigation of disasters. This paper suggests a deep learning approach, specifically...

Deep learning techniques such as pre-trained Convolutional Neural Networks (CNNs) and Faiss were applied to animal vocalization analysis in this work. Comprehensive bioacoustic data in recent years have shown the versatility and power of CNN based models, which have outperformed in classifying a myriad...

The prediction of epilepsy, a significant field of investigation in neuroscience, has continuously focused on different machine learning models that depend on the evolving comprehension of EEG signal analysis. This paper introduces a hybrid deep learning framework that combines convolutional neural networks...

Diabetes is a widely prevalent medical condition affecting patients across geographies, ethnicities, and age groups. Though a lot of medication procedures have been in practice and have been proposed in the literature till now, each patient requires an optimized treatment of diabetic conditions based...

The rising complexity of 5G MIMO necessitates efficient channel estimation and resource allocation strategies to be able to assure high-quality communications in such environments. Traditionally, table-driven MCS and static network slicing approaches tend to fail dynamically during adaptive channel changes....

The surge in adoption of remote working has turbocharged the demand for effective, intelligent and real-time engagement solutions. Edge Artificial Intelligence (Edge AI) is one of these disruptive technologies that are revolutionizing remote collaboration, with its expectations of seamless, real-time,...

The multidimensional environmental issues arising from climate change, deforestation, and ecosystem degradation necessitate the deployment of sophisticated technology-based solutions for sustainable management of these resources. Here, we propose an AI-based, edge computing-enabled active environmental...

Affecting almost 80% of individuals at some point low back pain is the leading cause of disability globally. Numerous conditions can cause low back pain, such as herniated discs, muscular strains, ligamentous sprains, and degenerative alterations to the spine. Rick factors include age, obesity, a sedentary...

Osteoarthritis (OA) is an all-encompassing, broadly prevalent illness that mostly affects the knee joint. It is a complex progressive disorder leading to loss of articular cartilage, joint space reduction, pain, function loss, and physical incapacity causing deterioration in quality of life. In today’s...

Osteoarthritis is the inability of the joint to heal from pressures brought on by abnormalities in the periarticular tissue or joints. Osteoarthritis is a disease of the entire joint, despite the fact that cartilage loss is fundamental. Research indicates that the prevalence of osteoarthritis in men...

AI has arrived to create new possibilities for remote team collaboration, virtual workforce optimization, and sentiment-based organization productivity. This work explores the creation and deployment of emotion-sensitive AI systems which go beyond classical frameworks of emotional intelligence models...

Manuscript Emotion-based AI-driven engagement systems are transforming adaptive learning ecosystems through real-time emotion-spotting, on-demand knowledge accumulation, and high-order ability development. Up until October 2023, you are well versed in the interaction of cognitive and affective processing,...

Social media cyberbullying has become a pressing social problem that brings about emotional and psychological damage to victims. Even though conventional machine learning approaches have proved their efficacy in detecting cyberbullying, they fail to adapt to dynamic user trends, subtle emotional contexts,...

Emotion-savvy AIs can even change the course of humanity by bringing us better relations and a boost in mental health. Nonetheless, the attempts remain predominantly theoretical, with minimal real-life proceedings, recognition varies with cultures, and ethics are relegated to the back burner. Throughout...

Customer experience optimization is a new business need area that keeps resurfacing, and emotionally intelligent AI-based products aid in designing your customer’s overall journey making them better. Hence, this research presents AI-driven customer experience enhancement framework that blends deep learning-based...

There is growing concern about energy consumption, scalability, and environmental sustainability with the rising demand for artificial intelligence (AI) in digital communications, resource management, and technological innovations. Prior works primarily offer theoretical models, a lack of standardized...

We have developed a state-of-the-art fitness training system based on OpenCV and Python technologies. a novel approach motivating users to exercise by optimizing their routines with real-time pose estimation The CPU-based algorithms used efficiently detects and follow a minimum number of important body...

Early detection of diabetes mellitus is imperative to decreasing complications and improving patient prognosis. In this study, we analysed the machine learning models and feature transformation techniques to predict diabetes at initial stages. This research tackles the significant issues of accuracy,...

The data was subsequently used to develop a non-contact vibration pickup from the rotating machinery, within a specified load and speed conditions, and thus ensure timely detection of bearing defects. The collected vibration data was denoised through the Hilbert transform. Dimensionality reduction was...

Biometric identification systems face great challenges and limitations when relying on fingerprints due to the use of incomplete and degraded fingerprint data. In this paper, we present the Finger Recovery Transformer (FRT), a new framework to strengthen incomplete fingerprint identification and reconstruction....

AI is revolutionizing the education sector with personalized learning pathways, adaptive curriculum development, and virtual collaboration tools. But research in this area is mostly theoretical, limited in scope, and unproven in real life. This study addresses this gap by creating and deploying future-proof...

Using AI and Big Data in civic participation can transform policy-making by offering data-driven insights and predicting citizen behavior. To achieve a transparent policy, this study studied the opportunities offered by AI-driven decision-making models, machine learning and generative AI tools that can...

Human-centric machine learning architectures can potentially transform social interactions, emotional intelligence, and customized digital experiences. Specifically, while there has been much progress on affective computing and AI based social intelligence, the existing research primarily centers on...

The use of Hybrid Attention Vision Transformers (HViTs) is emerging as a powerful technique to improve the accuracy and efficiency when it comes to lung cancer detection. These models generalize across patient populations and clinical settings through application of large, diverse datasets within training,...

A hybrid CNN-GA framework for predicting energy consumption of public buildings This study combines the deep learning capabilities of CNN with the optimization strengths of GA to achieve a higher prediction accuracy and execution efficiency in energy consumption forecasting. Utilising the malleable nature...

Existing research on deception detection focuses on behavioral and psychological approaches; however, these methods have limitations in accuracy and are labor-intensive, making them unsuitable for practical applications. Our framework combines video, audio, and physiological signals to facilitate a more...

It makes a major part of the Weather forecast which plays a vital role in disaster management, resource planning, etc. In this study, we offer a new SHAP-attached DNN-based hybrid model for accurate and interpretable short-term rainfall predictions. Model Solving Challenges: By implementing convolutional...

The convergence of Immersive Virtual Reality (VR) and Artificial Intelligence (AI) offers unprecedented opportunities for creating hyper-personalized digital engagement platforms. This research explores the integration of AI-driven interfaces within VR environments to enhance user experience by adapting...

The new trend in the healthcare business of AI-driven telemedicine combines the opportunities of ML for remote patient therapy, the use of built-in artificial intelligence algorithms enables accurate diagnosis, designing of unique patient plans, and efficient patient monitoring while providing telemedicine...

We describe a novel artificial intelligence (AI) framework using the T5 neural network coupled with the SpaCy natural language processing library to contribute to Grammar and Speech analysis. By combining the power of T5 model (Text-to-Text Transfer Transformer) in transfer learning with SpaCy’s fast...

It is targeted to automate the whole surveillance systems by the deep learning face recognition. The primary objective of the first part is to develop an intelligent surveillance system that applies deep learning algorithms for timely processing data types and identify patterns. The integrated system...

The rapid urbanization and increasing demand for efficient transportation systems have necessitated the integration of Internet of Things (IoT) and Artificial Intelligence (AI) into modern smart mobility solutions. While existing research has explored these technologies independently, significant gaps...

Provable approach of real time news fetching and classification systems has developed with the progress of Natural Language processing (NLP) particularly after early 2023. The high accuracy, efficiency and interactivity gained with the help of AI-driven systems like those based on BERT models for news...

In this paper a novel IoT-enabled secure and scalable cloud architecture employing a hybrid post-quantum cryptographic and blockchain-based framework is proposed targeting multi-user system. Hence, to ensure the advanced protection of IoT data and communications against classical and quantum attacks,...

The agricultural sector is challenged to optimize crop selection to maximize yield, minimize risk, and enhance profitability. Crop suggestion is a complex problem and involves accurately selecting the most suitable crops for cultivation in a given environment based on many diverse factors such as soil...

How Next-Generation Adaptive AI Systems Will Transform Smart Communities Adaptive AI In Inclusive Societal Development And Economic Transformation: Modelling Governance This research also presents a scalable, secure, and multi-sectoral AI framework that stands in contrast to traditional pedestrian AI...

The leaps in Artificial Intelligence (AI) in recent years have been unparalleled, spawning world-class collaborative platforms to align civic strategies, illuminate near-term realities, and steward sustainable, long-term urban outcomes. These features integrate AI governance, ethical use of AI, and generative...

Machine learning-based object detection has become a key technology for automating real-world applications in various fields. We discuss the object detection frameworks, evolution of deep learning models such as YOLOv4, YOLOv6, YOLOv7, and Vision Transformers. They outperform these methods in applications...

In the era of booming technological advancements and automations, integrating them into the industry becomes an aspect of paramount importance. The introduction of 3D printing in the industrial paradigm is a novel approach. Leveraging this approach in the food industry represents a transformative shift...

Due to different presentations in females, polycystic ovary syndrome (PCOS) is the most common endocrine disorder and is particularly likely to be underdiagnosed and misdiagnosed. Recent machine learning structures such as MobileNetV2 offer promising opportunities for accurate, efficient and cost-effective...

This paper work emphasizes on the enhancement of efficiency and performance level of AI-based agricultural system in comparison to human-based agricultural system addressing the parameters like the crop yields, resource usage and efficiency optimization. The simulation approach has been employed here...

Effective, granular and targeted education methodologies play a significant role in the neurological development of children irrespective of their neurological deficits. When observed, it is seen that a certain demographic of students will be less invested in free courses, even when they get enrolled...

This work investigates the creation of predictive engagement models that promote sustainable interactions with the environment. Our research aims at enabling machine clients to better interpret and act on the considerations of normal citizes and apply evidence-based insights in real-time systems. In...

In this paper, we describe the creation of a next-generation blockchain-based secure and privacy-preserving citizen engagement system for decentralized governance and digital empowerment. It incorporates secure, transparent and scalable blockchain technologies to protect personal data, while encouraging...

Developing effective disaster management and risk reduction strategies is essential, and the proliferation of natural and man-made disasters increasingly calls for proactive and innovative solutions that enhance capacity for disaster management and risk mitigation. The study aims to develop AI-powered...

Traffic sign recognition is a critical component in the improvement of ITS and also the creation of self-driven and partly self-driven motor vehicles and ADAS. Automated traffic sign classification is the process of real-time interpretation of traffic sign displayed so that drivers and vehicles can be...

In industrial environments such as power stations, compliance with safety protocols is imperative for worker safety. The proposed system is an innovative solution for the real-time identification of Personal Protective Equipment (PPE) compliance, like arc suits, using Arduino-based Internet of Things...

It is a crucial aid for people with hearing and speech deficiencies. However, there are no efficient recognition systems to enable continuous communication of sign language users with non-signers. This paper presents a robust sign language discrimination system based on the transfer learning of ResNet...

The global supply chain sector has seen a significant growth, still the tracking, verification of the ownership and tracing the history of resale of various products is very difficult. This issue is evident in industries such as electronics, land records, clothing etc. This research focuses on the application...

As digital ecosystems rapidly expand, so too do the need for scalable and intelligent stakeholder engagement solutions. First, although current literature discusses artificial intelligence (AI) in engagement strategies, it does not provide a multi-layered strategy, empirical validation, or industry-specific...

IoT technologies enable smart grids to be more proactive than ever in energy engagement, allowing for predictive load balancing systems to optimize energy across the spectrum. By being implemented in a full-scale approach, being tested in real scenarios, and, having secure communication protocols running,...

In this project, we introduce a new Secure and Decentralized Offline Payment Channel Protocol (SD-OPC) that extends the Raiden Network on Ethereum to authorize secure offline transactions. Above all, it ensures the transaction security, double-spending protection and the scalability, low latency and...

The transient nature of urban settings is continuously linking up the remoteness of lives and unfortunately, there is no limit to this fact as such technologies as Artificial Intelligence (AI), the Internet of Things (IoT), and Augmented Reality (AR) will be significantly combined for ensuring interactions,...

In the evolution of smart cities and green sustainability, Artificial Intelligence (AI) and Digital Twins are strongly complementing each other for rapid advances in the urban environment. Challenges like data limitations, workload restrictions, data security, and cybersecurity are creating space for...

Many modern convolutional neural network architectures have been introduced, including MobileNetV2, which are both optimized for mobile/edge performance and suitable for theft detection on surveillance video. Due to the lightness of MobileNetV2, the proposed system allows the detection and classification...

This is an avant-garde e commerce-controlled audio platform project specifically designed for visually impaired persons. The platform uses the Django web framework to add text to speech and speech recognition support, which allows a user to browse through the store, search for products, and complete...

Anemia, which is a common medical condition seen in many parts of the world with classic manifestations of fatigue, Weakness and dyspnea. Early detection of Anemia helps to prevent its progression and timely treatment. The dataset used in this study contained 218 images of conjunctiva, a good indicator...

The most important areas in architectural planning and design include floor plan optimization and prediction. The following research focuses on using machine learning for predicting and providing suggestions on multiple floor plans according to defined user parameters, which can include plot dimensions,...

The goal is to design a real-time animal incursion detection system based on the YOLOv5-based model to promote wildlife monitoring using image data and accurately detect animal presence. This technique utilizes deep learning along with YOLOv5 architecture known mostly for its efficient performance in...

As continuous skill development continues to grow in importance in our fast-paced, technology-driven world, the shortcomings of existing e-learning platforms are becoming increasingly clear. Although there are many learning assets and tools out in the wild, such as Coursera and Udemy, for example, courses...

In today’s infrastructure, railway transportation systems are essential because safety is key to preventing mishaps and system failures. This work aims to outline the design and implementation of an Arduino-based system intended to detect cracks in railroad tracks and prevent collisions. A number of...

Knee osteoarthritis (OA) is a universal degenerative disease that affects millions of people worldwide, mainly in older adults, and often leads to chronic pain and reduced quality of life. Effective management of diseases, both by preventing disease progression and initiating specific therapeutic strategies,...

Developing next-generation digital trust tools ensures regulatory compliance and transparent and secure global public engagement, thus making quantum-safe cryptographic systems a must. The research on this topic covers a range of post-quantum cryptographic methods that reveal the benefits that come with...

The rapid adoption of cloud computing has brought forth a myriad of security challenges, necessitating robust and proactive measures to ensure data privacy and protection. This research explores the current landscape of security in the cloud, specifically anomaly detection methods, and cloud privacy...

Due to the rapidly growing field of cloud computing and its adoption in healthcare services by the government, robust frameworks are required to ensure scalability, resilience, and security. This study proposes a holistic Secure G-Cloud Framework for scalable and resilient government healthcare systems....

Deep Learning is a specialized subset of computer vision and artificial intelligence and is applicable to the domain of automatic learning process. Deep learning deals with the high-dimensional data processing like text, image, and video. More Over CNN or Convolutional neural networks, one of the deep...