All of the articles in this proceedings volume have been presented at the ISSF 2026 – International Conference on Intelligent Systems for a Sustainable Future held at SCSVMV University, Enathur, Kanchipuram, India. These articles have been peer reviewed by members of the Scientific Committee and approved...

The paper presents an explainable AI (XAI) framework that enables detecting, localizing, and segmenting of skin lesions with the YOLOv8 object detector model, which is available as a Streamlit web application. This system consists of a trained YOLOv8 detector and other image-processing techniques (hair...

To achieve an addiction recovery process, continuous monitoring, early risk identification and presence of timely intervention are necessary to avoid relapse and aid in long-term rehabilitation outcomes. In this paper, the author describes Rehab360, a versatile AI-based platform to explore addiction...

PCOS which stands for Polycystic ovary syndrome is a very common endocrine disorder which affects women of childbearing age and which also causes infertility, biochemical abnormalities like insulin resistance and obesity, and serious psychosocial stress. Early diagnosis and intervention is key to good...

One of the leading causes of death worldwide is myocardial infarction (MI), for which prompt diagnosis is essential to averting serious cardiac events. Long Short Term Memory (LSTM) networks trained on sequential clinical data are used in this work [1], [2] to present a multimodal intelligent framework...

Heart disease remains one of the leading causes of illness and mortality worldwide, making quick and accurate diagnosis more essential. Many doctors rely on multiple clinical indicators such as patient’s age, lifestyle habits, and laboratory test results to evaluate a patient’s risk. Most existing computerized...

Neurodegenerative diseases are a group of progressive disorders that affect the nervous system, characterized by a gradual deterioration in mental and physical functions. In the domain of neurodegenerative diseases, Alzheimer’s disease (AD) and Parkinson’s disease (PD) are some of the most prevalent...

This research examines the integration of visual communication and cognitive psychology principles to enhance AI-driven decision-making in engineering fields. This study investigates the integration of cognitive psychology and visual communication principles to enhance AI-driven decision-making in engineering....

The worldwide mental health crisis and the lack of licensed providers are forcing the need for to identify innovative and efficacious possibilities for expanding access to mental health care that can be delivered in a streamlined manner. This review assesses the simultaneous potential and pitfalls associated...

The eighth most frequent disease in the globe in India is oral cancer (OC), which kills 130,000 people every year. Oral cancerous tumors can arise in a variety of locations, such as the tonsils, salivary glands, neck, face, and mouth. Histological pictures are useful for cancer screening because they...

The combined use of the Internet of Things (IoT) with Machine Learning (ML) has grown considerably Remote Patient Monitoring (RPM) because of regular clinical data generation, accelerated measurement, and predictive healthcare decision support. Even so, the extensive use of IoT and ML based RPM systems...

Cardiac evaluation at initial stages depends on precise handling of biological data. A method involving separate models appears here, examining PCG and ECG signals through distinct computational paths. Instead of merging information early, processing stays independent, allowing use even if only one signal...

The increasing use of digital health consultation systems shows that technology now plays an essential role in identifying health problems and teaching patients. The existing digital health systems depend entirely on text communication which creates problems for users who need assistance and for health...

Manual claims approval cycles are typically involved in the processing of health insurance claims, as well as delayed approvals, data tampering and poor visibility for both patient, hospital and insurer during the claims cycle. Clamora is a decentralized application utilizing blockchain technology and...

Liver disease is currently a significant societal health issue in many countries around the world, and the causative factors include alcohol abuse, food poisoning, drugs, and environmental pollution. This needs to be identified early and handled effectively to slow down the progression of the disease...

Efficient healthcare management depends on accurate prescription handling, proper medication adherence, and continuous monitoring of patient health conditions. In everyday situations, many patients find it difficult to understand prescription instructions, remember dosage timings, or consistently follow...

Maternal and fetus health surveillance is crucial in curbing pregnancy complications and maternal and fetal death though traditional hospital-based surveillance systems are periodic, resource-demanding, and demand physical presence making it to be slow in the early identification of critical health abnormalities,...

Robots are better equipped to communicate through movement than through spoken language. Herein we propose a method of specifications of tasks for disabled people in terms of robotics service. This helps to implement an automatically working system that will replace the efforts of human so disabled people...

The problem of mental health becomes more widespread in the world, whereas the possibility to receive timely and stigma-free help is minimal. This research will help to satisfy the demand of a convenient and smart system of mental health assistance by designing the role of AI-based companion that would...

A rigorous modelling of biomechanical pattern of lower limb fracture patients is required to handle the class imbalance between normal and defective gait, rehabilitation assessment for patients. This work uses vertical ground reaction force (vGRF) data and suggests a novel cost sensitive deep learning...

Niramaya-AI is an intelligent health assistant designed to support preventive healthcare and early diagnosis by combining image-based skin disease detection, asthma risk prediction, and chatbot interaction within a single platform. The system is developed as an accessible and user-friendly application...

This work presents a web-based intelligent diagnostic cardiovascular diseases automatic classification system based on the electrocardiogram (ECG) images. The system has a pre-trained hybrid CNNResNet deep learning model to assign the ECG images to four categories, Myocardial Infarction, History of Myocardial...

Pneumonia is an infection caused by various pathogens, be they bacteria named Streptococcus pneumonia or viruses named Influenza and SARS-CoV-2. It is one of the leading causes of death in the elderly and young population. Traditionally, the diagnosis of pneumonia was done by an experienced physician,...

The combination of data science and technology has revolutionized disease detection and prediction in today’s healthcare environment. This research presents an advanced approach of multi-disease prediction using deep learning architectures, namely InceptionV3 and VGG19 in the framework of a Flask-based...

Dental disease is considered to be one of the biggest healthcare issues worldwide, and the most widely distributed chronic infection known today. The identification of dental issues via image assessment early on can help dentists develop better treatment plans and manage more severe health issues sooner....

Diabetes mellitus is a problem that affects many parts of the body and gets worse over time. near of the ways we try to predict what will happen to people with Diabetes mellitus only look at one thing at a time. This study is trying to do something. It is trying to make a system that can predict all...

Machine Learning (ML) and Deep Learning (DL) have emerged as powerful techniques in many fields, including speech recognition, cybersecurity, text generation, financial fraud detection and medical image analysis. There are numberless Image Processing (IP) techniques used for processing, analyzing and...

Alzheimer’s disease refers to a progressive the neuro degenerative condition that causes an irreversible deterioration in memory, reasoning, and cognitive functions, presents great problems to patients, families, and the health care system. The effective clinical management of the disease requires accurate...

Ovarian cancer remains one of the most lethal gynecologic malignancies due to late diagnosis and frequent recurrence after treatment. Accurate prediction of both survival and recurrence risk is essential for personalised clinical decision-making. This research work proposes a Multi-Modal Supervised Contrastive...

This study evaluates the effectiveness of nano enriched repair mortars in restoring the mechanical and durability performance of concrete exposed to elevated temperatures. Concrete structures subjected to fire or thermal loading experience significant strength loss, deterioration of bonding zones, and...

The present paper describes a Smart Autonomous Guided Vehicle (AGV) with a new Triple- Mode Navigation system and a specific mobile application interface created with Flutter. The AGV enables the flow of line following based on the IR sensors, manual control through the application, and automatic minimum...

This research investigates the flowing appearances in a solar air heater utilizing a gap reverse arc pattern integrated with staggered elements. The investigation was carried out with some roughness parameters and also arc inclination (α) of 600, 0.4 relative staggered rib pitch (p'/p), 1 the relative...

Rapid urbanization has made significant changes and challenges to traffic systems. Increased vehicle usage in the metropolitan regions has resulted in the surge in roadway crowding and pollution near junctions, as the traffic signals are predetermined without considering the levels of congestion. This...

The use of machine learning (ML) methods is the new wave of precision agriculture that will transform the traditional methods of farming by refining fertilizer recommendations, increasing crop yields, and reducing environmental impacts. This study provides a comparative analysis of the ML and deep learning...

The growth of the e-commerce industry along with additional last-mile de- livery service options has created the need for enhanced logistics systems that can meet the needs of customers more efficiently than they are being met now. The fixed timeframes for delivery established by the majority of courier...

Reliable and efficient fault detection in transmission lines is vital for ensuring the stability and safety of modern power systems. Conventional fault detection techniques often face challenges in accurately identifying fault types and locations under dynamic operating conditions and noise interference....

Transportation, energy, water, and built environments are increasingly being used as more innovative infrastructure through predictive analytics to guarantee reliability, efficiency, and resilience. Conventional centralized data analytics platforms have limitations on scalability, latency, and privacy...

Recent technologies for high-energy optimization and storage control have been accelerated by the growing integration of renewable energy sources and smart building systems in modern power systems. The new generation of smart grids and green buildings gives rise to extremely dynamic and heterogeneous...

Rapid urbanization has escalated the problem of road safety in general and has also led to the concentration of these challenges in certain areas, particularly those that are manpower- and infrastructure- deficient. In such places, expensive systems such as CCTV, ANPR, and red-light detectors cannot...

Civii is a citizen-powered mobile-based disaster reporting and rescue support system that addresses the communication and coordination gap during emergencies. The application enables users to capture and report critical incidents using images or videos directly from their smartphones, with full support...

Rapid growth in electric vehicle sector has resulted in a substantial increase in the manufacturing and usage of lithium-ion batteries which create challenges that are related to battery degradation and end-of-life management. During vehicle operation, there is a fade and increased internal resistance...

Sustainable water management in smart cities refers to combined and intelligent management of urban water supply, distribution, wastewater, reuse and stormwater systems to guarantee the security of resources in the long term, protect the environment and resiliency of the city. This paper’s purpose is...

Today's global concern is the increase of the earth temperature, to overcome this use of EV and PV has been motivated. This solution has it challenge also, as to incorporate both PV and EV together in one system. This paper presents an approach to integrate grid-integrated electric vehicle (EV)...

taking care of urban gardens and promotes healthy plant growth with minimal human interference. With today's busy life, most individuals find it difficult to regularly care for their indoor or balcony plants. Chitti Pot solves this issue by fulfilling the role of a smart friend that tracks the requirements...

Light and noise pollution are now recognized as major environmental issues, which put human health, biodiversity, and the sustainability of urban areas at risk. Combined scientometric study that synthesizes the two areas is still rare, despite the increased volume of research. This paper maps trends...

Digital twin technology will allow better control of robots since it allows to synchronise physical with virtual versions of systems in order to minimise risk associated with hardware and enhance experimental flexibility. In the traditional robotic arm programming, fixed kinematic models are used, and...

Unmanned Aerial Vehicles (UAVs) or specifically drones are commonly used in monitoring and delivery applications. Due to their versatile characteristics in many sectors, they are also used in all environments, which also include EMI prone zones. Zones which are surrounding transmission / power lines...

Microbial hotspot sensing and environmental surveillance in remote or hostile locations need intelligent systems that can conduct real-time analysis with strict computational limitations. Traditional cloud-based approaches are often slower, require more bandwidth and reliability, and their performance...

UAVs are increasingly used in these emergencies, delivering supplies or assessing damage [2]. But there’s a catch: most of them still rely a lot on GPS to get around [1]. If the satellite signal cuts out or gets weak—and it happens, especially if you’re only using one system—those UAVs can’t always finish...

This paper presents a comprehensive study on the mathematical modeling and control design for a three degree of freedom helicopter system. The mathematical modeling, linearization, and control design of a three degree of freedom helicopter system are the main focus of this study. The initial phase focuses...

Vibrations and dynamics within mechanical engineering concern the behaviour of mechanical systems under forces and movement, making it possible to optimise system performance, safety, and reliability in a wide range of applications, including in the design of machinery itself or structural integrity....

To achieve optimal planning of the energy system and stability of this system, it is essential to have precise forecasting of the solar power. Based on long-term solar production and meteorological records obtained at the Annamacharya University in Rajampet, this paper proposes a machine learning-based...

In agriculture sector maintaining and improving the leaf health is having important role. This task is obtained by using deep learning techniques and it provides more no of models for analyzing the leaf’s patterns and also it extracts the features from image based leaf data sets. There are two models...

Manual crowd monitoring at public gatherings, religious events, and transportation hubs often causes delays, inaccurate estimates of crowd density, and limited awareness of the situation, especially in busy environments where crowd behaviour changes quickly. This paper introduces a smart vision-based...

Motorcycle safety is still a big issue all over the world. Riders run into more dangers because they often miss what’s around them. Road conditions can be pretty rough too. Traditional helmets lack smart features to help out. That is where things stand right now [1]. This work lays out a full design...

In hydroponic cultivation, maintaining proper nutrient concentration and environmental conditions is essential for healthy plant growth. Continuous monitoring of these parameters is therefore an important requirement in hydro- ponic systems. Although several IoT-based solutions have been proposed for...

This study analyzes machine learning methods for crop recommendation using an agricultural dataset that contains soil nutrients (N, P, and K), pH value, temperature, humidity, and rainfall. Several machine learning models were used and assessed, including Decision Tree, Random Forest, Gradient Boosting,...

Forecasters need to change their approach to weather prediction because extreme weather events keep increasing in number and strength throughout Southeast Asia which experiences extreme weather disasters. The implementation of physical-based Traditional Numerical Weather Prediction (NWP) models faces...

With the increasing integration electric vehicles (EVs), reactive power management is crucial for preserving voltage stability and guaranteeing effective distribution of energy in hybrid AC/DC microgrids. These microgrids integrate DC and AC systems, providing greater flexibility and reliability for...

Traffic congestion continues to be a significant problem in Indian cities which grow quickly because of multiple vehicle types and unpredictable traffic patterns and irregular lane usage. Traditional traffic signal operations that depend on fixed schedules and sensors fail to adjust properly to these...

Images captured underwater have low contrast, distorted colors, and limited visibility because of light attenuation and scattering in water. This poses a huge challenge in marine organisms monitoring, where species recognition, categorization, and behavior evaluation are performed. We propose a deep...

Plant disease detection is essential for enhancing sustainability in agriculture domain, as it enables early detection of any possible crop loss. It allows to have reduced production loss and chemical dependency. This paper proposes deep architectures utilizing VGG16 and VGG19 for automated plant disease...

The increasing frequency and severity of wildfires have highlighted the urgent need for intelligent, real-time monitoring systems. These systems are capable of detecting early signs of forest fire activity. This paper experiments with the real time datasets from various websites with deep learning techniques....

Accurate flood forecasting is required for disaster risk mitigation. Risk mitigation, however, a lot of data-driven models are based on synchronous spatio-temporal assumptions which cannot reflect the inherent asynchronous character of flooding propagation. In hydrological systems, stream indicators...

The primary focus of this initiative is the onboard fast charger of the Electric Vehicles (EVs), on single phase. One of the limiting characteristics of on-board rapid charging density is the power capacity of the converter. The current stress on the current flowing between the inverting segments restricts...

Solar energy has ceased to be a secondary energy source and is becoming an essential part of the contemporary power grid with a growing need to have a sustainable source of generation. However, the system of integrating utility-scale photovoltaic systems with the existing electrical systems presents...

In this study, the system proposed by the researcher is Sahayak, an AI-based learning solution that seeks to automate the process of learning content creation and academic performance analysis of students in schools and colleges. Teacher can create class and subject, and then the in-built AI module automatically...

Stable communication and quality Wi-Fi systems, in particular, are among the main challenges posed by the variable nature of wireless communication environments. The ability to predict Wi-Fi link quality is of prime importance in making the network perform excellently, making the connectivity reliable,...

Transformer less grid-connected photovoltaic (PV) inverters are gaining in usage due to their vast efficiency and small size. But, because of variations in common-mode voltage, the absence of galvanic isolation might result in leakage currents, which usually reduce power quality. The conventional proportional-integral...

The increasing requirement for the distribution of renewable energy sources into the current power system is causing increased challenges with regards to system stability, specifically frequency response. Current Automatic Load Frequency Control (ALFC) methods developed for a centralized power system...

Lake areas prediction is a prerequisite for safe and sound environmental management and planning, especially in the regions that are influenced by the changed hydrological regime. This Research displays what machine learning regression methodologies Regression (Linear Regression, Ridge Regression, and...

The present study analysed the heat transfer and pressure-viscous behaviour of sustainable refrigeration oil/green refrigerant for domestic refrigeration systems. The sustainable refrigeration oil was synthesised from pentaerythritol esters (PE) using the uninterrupted transesterification process. Then...

Object detection systems used in outdoor settings are often degraded by adverse weather conditions, such as fog, haze and low illumination. Reduced visibility results in weak feature representation and unstable prediction and missed detections. This paper introduces Weather Eye, a weather aware object...

Organizations today are also combating increasing rates of cyber menace emails phishing, malwares, fakes and network attacks that are soaring at an unprecedented pace. The field of isolated security solutions perceives the teams as being blindfolded and reactive. ThreatShield API is to be used as a combination...

Structured query language (SQL) involves technical writing expertise that poses a big obstacle to non-technical users, thereby restricting data-driven decision making at the organizational level. Available solutions like direct database clients or the conventional Business Intelligence (BI) solutions...

Facial images captured in real life often get blurred due to motion blur or poor focus. Facial image deblurring plays an important role in surveillance, authentication and biometric applications. Although conventional Convolutional Neural Network (CNN) and Generative Adversarial Network (GAN) based deblurring...

Healthcare fraud detection is inherently difficult to model because the available data combine several challenges at once. The number of confirmed fraudulent providers is typically very small compared to legitimate ones. The features are diverse and providers are indirectly connected through shared patients...

To support complex city systems, including transportation, energy distribution, citizen security, and environmental surveillance, smart city infrastructure is increasingly dependent on artificial intelligence. Although reinforcement learning can be used to make adaptive judgments in such settings, conventional...

In recent years, cryogenic ceramics and non-metallic materials have emerged as a transformative research frontier, attracting growing attention for their ability to perform reliably under extreme low-temperature conditions. Defined by their dimensional stability, resistance to embrittlement, and superior...

The idea of fatigue and fracturing mechanics has always been primary in the safety and reliability of structural and mechanical systems, and over the past few years, there has been a paradigm shift between the conventional safe-life design and the damage-tolerant design. This paper intends to review...

This paper presents Gradelix, a web-based system that helps schools manage student results. It is built using a combination of technologies including MongoDB, Express.js, React.js and Node.js. The system aims to make it easier to manage performance by generating results doing calculations and providing...

Automated analysis of rodent behavior in the Open Field Test (OFT) plays a central role in objective and scalable behavioral assessment within neuroscience research. This paper presents a fully automated, video-based framework that performs arena-aware localization, motion feature extraction, and temporal...

Sanskrit prosody (Chandas) represents one of the most rigorous metrical systems in world literature, combining phonology, morphology, and semantics into strictly governed poetic forms. Automated metrical analysis of Sanskrit text requires precise sandhi resolution, syllable and mora identification, and...

Global illumination variations make unpaired day–night image translation challenging. Under such conditions, convolution-based CycleGAN methods primarily focus on local texture translation, often neglecting global lighting consistency, which results in inconsistent sky–ground illumination and noisy outputs....

Artificial Intelligence (AI) is now a part of the education system. Artificial Intelligence (AI) changes how students work with study materials and learn things. I have observed that speech recognition, natural language processing (NLP) and text-, to-speech synthesis have advanced quickly. Speech recognition,...

AUTODOX is a cross-platform desktop application designed to remove the burden of manual file organization through personalized, intelligent automation. Rather than relying on fixed sorting rules, the system observes how individual users interact with their files and continuously refines its behavior...

The interchange of processes, systems, and users between Artificial Intelligence (AI), Blockchain, and immersive technologies such as Augmented Reality (AR) and Virtual Reality (VR) have expedited the advancements and evolution of the Metaverse into a decentralized and engaging digital ecosystem. While...

The amount of heterogeneous services and users deployed on cloud computing systems is soaring at an extremely fast rate and hence, the concern of secure service selection and access control has become a fine-grained access control that is more and more complex. This paper proposes a Hybrid Deep Learning-based...

Road traffic accidents cause hundreds of thousands of injuries, deaths, and economic costs annually, and hence the prediction of severity is significant for effective rescue resource allocation and policy intervention [1]. Machine learning (ML) has been shown to be a valuable tool in achieving the patterns...

The conditions of heterogeneous aircrafts, dynamic environmental factors, and uncertainties related to humans are all involved in the operations of the private jets and pre-takeoff risk assessment is a complicated safety problem. This paper suggests AeroSafe, a hybrid guided machine learning model to...

In the current paper, I would like to discuss a blockchain-powered academic certification check system, combining decentralized storage of credentials with identity checks based on biometrics to improve the reliability, safety, and authenticity of scholarly records. The conventional system of certificate...

With the rapid creation of artificial intelligence in the sphere of conversational technologies, the management of the interaction with the customers has been changed by the organization in question, specifically, the adopted use of the automated call-handling system. I will present an interactive voice...

Small and micro businesses often work with very limited money and time. Many owners still track sales, expenses, rent, and taxes on paper or in messy spreadsheets, making it hard to plan or spot problems early. This project creates a simple, smart tool that lets businesses upload their records and quickly...

Customer sentiment analysis will make us aware of their thoughts on online shopping websites and make more informed decisions. Due to the growth of online marketplaces, we require automatic tools to discover valuable insights when working with very large volumes of customer comments. In this paper we...

The emotion recognition is a significant role in human-computer interaction, in the field of affective computing and intelligent decision-support systems. Most existing methods of sentiment analysis presuppose one channel as a text or speech one, which cannot be applicable in any real-world context when...

Cyber threat reports are widely used in security investigations to understand how attacks are executed and how systems are compromised. These reports usually contain detailed descriptions of attacker behavior, but the information is presented in narrative form rather than structured according to standard...

Proper prediction of inventory demand is extremely significant in the case of a healthy, operating supply chain. In case companies make incorrect forecasts they can either have more inventory (which must be stored at a cost), or run out of inventory which leads to dissatisfied customers. The given study...

The paper provides a deployable banking transaction fraud detection system, written in Python and Streamlit, which uses a pre-trained supervised machine learning classifier as an interactive web-based dashboard. Structured transactional data is also processed in the system in seven engineered features...

Women career progression is highly dependent on mentorship, and according to the conventional models of mentorship, the latter is mainly manual, biased, and unreachable. In a bid to shorten these challenges, SEEK HER is a Web-based application designed based on the MERN stack that is meant to offer intelligent,...

The work covers the creation of the intelligent chat bot system, which helps users with the college-related queries by means of the efficient and automated interface. The system combines natural language processing, machine learning and rule-based technologies to read with accuracy user queries and provides...