Most video processing applications, including surveillance, object detection, and scene comprehension, rely on edge detection. Real-time video data processing requires efficient hardware that meets the demands of edge detection algorithms with minimal power usage. High-speed edge detection and resource...

Embedded systems used in safety-critical applications demand the highest level of reliability. To ensure continuous operation and automatic recovery from runtime failures, external watchdog timers are commonly employed. However, most conventional watchdog timers require additional circuitry for timeout...

A Reconfigurable Optical Add-Drop Multiplexer (ROADM) is an optical add-drop multiplexer that can remotely switch user’s traffic. This optical network considered input power for the project’s first stage by implementing a 4-channel Dense Wavelength Division Multiplexing (DWDM) system. The resulting outputs...

The cryptocurrency market is noted for it’s built in by its unpredictability, usually punctuated by rapid and large price movements. Such volatility is challenging for investors who must keep a close eye on market conditions to make timely and informed choices. To counter these challenges, a real-time...

Driving in fog is a major issue for drivers, especially in the early morning and late at night, as it reduces visibility and raises the possibility of accidents by making it difficult to see far-off objects on the road. Heaters and air conditioners are common fog removal devices that are notoriously...

Brain tumor recognition is a serious task in medical imaging, helping in main diagnosis and handling development. This paper shows a deep learning-based method utilizing MRI scans for tumor detection and classification. The model integrates U-Net intended for splitting up and ResNet-50 for classification,...

Parallel Pixel Processing and Filtering Architectures for Image Processing in Verilog (PPPFA). The article discusses image processing using hardware acceleration with focus on the systems which process grayscale images independently of color images. The architecture for processing grayscale images applies...

Vehicle-to-Vehicle (V2V) communication is a crucial aspect of Intelligent Transportation Systems (ITS) aimed at improving road safety and traffic efficiency. Wireless Optical Networking (WON) technology has emerged as a promising solution to overcome the limitations of conventional radio-frequency-based...

Third-generation (3G) biofuels, derived from algae, have been created to address the increasing demand for renewable fuels. With high energy density, low land use, and carbon dioxide sequestration capabilities, biofuels from algae are seen as a good alternative to fossil fuels. However, for making the...

There is a new implementation of text or speech controlled home automation application system using Arduino ATMEGA 328P and HC-05. This project uses a Arduino nano microcontroller and HC 05 Bluetooth module. Instant home and industrial automation such as lights, fans, motors. Arduino controller is a...

Emotional Intelligence is the procedure of identifying the emotional tone of a string of words in order to comprehend the sentiments, viewpoints, and feelings conveyed in an online mention. This project presents a comprehensive study on the applications of Machine learning (ML) techniques in emotion...

The increasing requisition of low power and advanced computing architectures has driven the demand for efficient arithmetic units, particularly in digital circuits like Adders. The primary concern being dealt with here is the need to reduce power consumption while providing high computational performance...

Comparators are essential in analog and mixed signal applications because they compare inputs and provide the appropriate output. In this paper various comparator types of open loop, dynamic latch, preamplifier latch, and hysteresis comparator are compared using CMOS and FinFET technology. Analyzing...

This project presents an automated traffic violation detection system developed to recognize and confront helmet violation and triple riding using real time and static data. The system applies the YOLOv8 model for real time object detection. Pre-trained YOLOv8 is utilized for triple riding detection,...

In the modern era, continuing translucency and fairness is a main way to secure a voting process in educational institutions. Traditional voting is a basic parliamentary pursuit; experts have a feeling that using paper in balloting is the only procedure to ensure everyone votes; however, this procedure...

Deep learning has made significant progress in medical imaging by improving diagnostic accuracy. However, processing sensitive patient data on cloud-based platforms introduces major privacy risks. This study introduces a privacy-centric approach to analysing medical images, utilizing learnable encryption...

Social media content is rapidly growing and varies across platforms, making it challenging to process and analyze manually. This study explores the effectiveness of two deep learning models—CNN and MobileNet—for clustering content from different social media sources into five distinct categories: news,...

A correct prognosis of Alzheimer’s disease is crucial for effective treatment, especially in its early levels, because it enables mitigation of the risk of severe brain damage. While early diagnosis of Alzheimer’s disease is possible, predicting its onset before signs appear remains a challenge. Deep...

Air pollution is a hidden but serious public health risk that has been made worse by urbanization and industrialization. This study compares deep learning and statistical models for predicting urban air quality in order to lessen its consequences. LSTM, GRU, CNN, and ensemble combinations were among...

With interaction going online, there is increasing importance placed on con- trol. Basic ways devices can break your flow: Kindergartens and devices such as key- boards and mice. The Gesture Based Media Control System (GMGS) repairs this by means of computer vision and machine learning. It allows hands-free...

Medical image segmentation is an important task to assist radiologists in accurate diagnosis and treatment planning, particularly for complex anatomical structures. Traditional CNN-based models have demonstrated good performance but often suffer from computationally costly costs and poor generalizability....

Efficient crowd management is crucial for ensuring a seamless user experience, optimizing operations, and minimizing safety risks in public spaces such as malls and transit areas. With the increasing number of pedestrians, issues like overcrowding, stampede-like situations, long queues, inefficient space...

Brain strokes are a significant cause of mortality and disability worldwide, necessitating early detection for effective intervention. Traditional diagnostic methods relying on manual interpretation of CT scans are often time- consuming and prone to errors. To address this, we propose an automated brain...

There is an increase in the number of security vulnerabilities in Software Development Lifecycle (SDLC) as the practice of cloud computing expands. The main problem with traditional SDLC models is that they often neglect security and this leaves several threats and vulnerabilities uninspected. Our paper...

This project titled “PROFESSIONAL PATHWAY HUB” aims to develop a college placement website designed to streamline the placement process. It includes separate login for faculty and students, offering personalized access. The website offers students with three modules: Training Skill Development Module,...

straightforward layout for the dynamic comparator is created. A key metric in very large scale integration (VLSI) circuits is power consumption. There are a lot of ways to lower the circuit’s power usage have been suggested before. Presented here is a FINFET comparator that makes use of a dynamic latch;...

Tragically, many innocent lives are lost daily in car accidents. Driving mistakes and delayed emergency response time are the leading reasons. The braking system is an essential part of every vehicle. Problems or accidents might occur as a result of improper or delayed braking. Failure to rapidly apply...

This research looks at how well GRU, LSTM, and Dynamic LSTM architectures work at predicting energy use based on changes in time, pointing out their unique pros and cons. Long Short-Term Memory (LSTM) networks are noted for their ability to model complex temporal dependencies, making them well-suited...

Multi-valued logic systems were first conceived to solve connection problems with conventional binary circuits. Ternary logic offers the advantages of minimum circuit complexity, lower power consumption, and a more compact chip design. To further improve these advantages, this project presents a novel...

Accurate diagnosis of diabetes and particular willpower of insulin dosage are vital for most appropriate management of the circumstance. This research utilizes machine learning, using the Gradient Boosting Classifier to predict diabetes and Logistic Regression to decide insulin dosage. The PIMA Diabetes...

Facial sketching and recognition is a critical crime solving tool in identifying criminal suspects. Conventionally, sketching is done using forensic artists interpreting eyewitness accounts into a drawing, a process prone to being subjective, time-consuming, and highly reliant on artistic skill. In addition,...

Vehicle tracking plays a crucial role in intelligent transportation systems, traffic monitoring, and autonomous driving. Traditional tracking approaches often struggle with occlusions, varying lighting conditions, and com- plex backgrounds. This paper proposes an innovative method that integrates YOLO...

Respiratory infections are the third most common cause of mortality worldwide, and successful treatment and prevention of their spread depend on early identification. This application proposes a unique, lightweight inception network intended to identify a wide spectrum of respiratory disorders by monitoring...

Novel XOR/XNOR and simultaneous XOR-XNOR circuits are suggested in this study. The suggested circuits significantly enhance power consumption and delay thanks to their tiny output capacitance and almost nonexistent short-circuit power dissipation. Additionally, six separate hybrid 1- bit full-adder (FA)...

Most people are suffering from brain tumors in recent days. In medical image processing, brain tumor detection and risk prediction continue to be important problems needing very accurate models for early diagnosis and treatment planning. Using model-agnostic explainable Artificial Intelligence (XAI),...

Every kind of processor relies on full adders in their design and development. An area-efficient full adder with a small number of transistors is shown in this project. It is designed to be both powerful and power-efficient. In this paper, we present the design of a low-power full adder with good performance,...

Using a combination of static complementary metal-oxide semiconductor (CMOS), transmission gate logic, and pass transistor dual-value logic, this short presents a mixed-logic design strategy for line decoders. We provide two new topologies for the 2-4 decoder: one with 14 transistors to reduce power...

Design of dual-band and flexible microstrip patch antennas for cancer hyperthermia in biomedical applications. The proposed antenna consists of patch, with half ground plane and is used for impedance matching purposes. The proposed antenna meets the impedance bandwidth required for two bands,2.4 GHz...

Every day, video streaming services produce enormous volumes of information, making it difficult for consumers to locate videos that are relevant to their interests. By offering personalized material based on viewing history, preferences, and metadata, recommendation engines improve the user experience....

One out of every 700 live newborns worldwide is affected by Down syndrome (DS), a genetic disease brought on by an extra copy of chromosome 21. For impacted children to receive the right interventions and have their quality of life improved, early diagnosis is crucial. Traditional techniques for identifying...

In this article, we present an automatic currency recognition system based on digital image processing methods. The system is designed to identify currency notes through major features such as size, color, and printed text such that users are able to identify major details such as currency value, denomination,...

This project focuses on the design and development of a digital loop filter for an All-Digital Phase- Locked Loop (ADPLL) implemented as an Intel- lectual Property (IP) core in SCL 180nm CMOS technology. The loop filter is a critical component of the ADPLL,it is responsible for stabilizing the system...

Network administration has been completely transformed by Software-Defined Networking (SDN), which makes it for centralized possible control, programmability, and dynamic resource allocation. However, because it is centralized, it is vulnerable to serious security risks, including DDoS assaults that...

This research details a computer interface operated through eye tracking, replacing conventional mouse input. The system enables users to navigate and interact with a computer solely by moving their eyes. Employing an IP camera, the software utilizes OpenCV for pupil localization and DLIB for precise...

The proliferation of unstructured medical documents necessitates efficient methods for extracting and analyzing patient symptoms to enhance clinical decision-making. Now-a-days, in medical field clinical coding and symptoms identification are doing manually or they are manual process. This paper presents...

This project is concerned with real-time emotion recognition from speech using machine learning methods to interpret vocal expressions. The system records audio through a microphone, processes it to extract major prosodic features like pitch, intensity, and tone using the Librosa library, and then classifies...

Sign language is a fundamental mode of communication for the deaf and hard-of-hearing communities, yet real-time automated translation remains a significant challenge due to the complexity of hand gestures, variations in lighting, and differences in signing styles. This study introduces Hand Speak, an...

This literature review emphasizes the importance of early brain tumor detection for improving treatment outcomes and survival rates. It critiques traditional diagnostic methods, such as MRI interpretation by radiologists, which can be slow and prone to errors. The review highlights advancements in artificial...

Understanding human gait patterns is essential for medical diagnostics, rehabilitation, and prosthetic development. This study presents an advanced deep learning approach that combines Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) to analyze lower...

As our reliance on networked systems continues to grow, so does the risk of cybersecurity threats, which are becoming increasingly sophisticated and difficult to detect. Traditional Intrusion Detection Systems (IDS) often fall short in keeping up with these evolving threats, as they typically rely on...

Career guidance in the modern era faces significant challenges in creating accessible systems that effectively bridge education and employment. While there has been limited research on leveraging artificial intelligence (AI) in this domain, its potential to transform career guidance services in higher...

Earthquakes are a big threat. They kill people, wreck buildings, and mess up economies. We need to predict them well to lower risks and handle disasters better. This project uses deep learning methods, such as neural networks and Long Short-Term Memory (LSTM) models, to guess earthquake sizes and depths....

Plant diseases pose a significant challenge to agricultural productivity, leading to considerable reductions in both the quality and quantity of crops. In rice, a vital staple for global food security, common disorders caused by mineral deficiencies and pest infestations typically emerge during critical...

Skin cancer remains one of the most common and life-threatening diseases globally, making early and accurate detection crucial for effective treatment. This study introduces a deep learning-based solution that significantly enhances skin cancer diagnosis. The proposed system employs a Convolutional Neural...

Object detection is the very backbone of computer vision. Applications surface in autonomous vehicles, healthcare diagnostics, and surveillance systems. All the conventional methods of object detection typically require massive amounts of annotated data and use heavy computation, making it hard to use...

Almost one in six deaths worldwide is due to infection, although the speed and accuracy of conventional diagnostic techniques are limited. Medical image analysis, such as CT and MRI scans, can now be done more quickly and accurately thanks to artificial intelligence (AI), which has become a potent tool...

Cervical spine fractures are critical medical conditions that demand rapid and accurate diagnosis due to their potential to cause severe neurological impairment or death. Traditional diagnostic methods relying on manual radiographic interpretation are often limited by subjectivity and time constraints....

In today’s digital age, cyber threats like phishing and malware attacks have become increasingly sophisticated, making it essential to develop advanced solutions to protect users. Phishing websites often disguise themselves as legitimate platforms, tricking users into entering sensitive information such...

The rapid evolution of malware poses significant challenges for traditional detection methods, necessitating advanced approaches that combine deep learning with effective interpretability techniques. This work combines Long Short Term Memory (LSTM) networks and Generative Adversarial Networks (GANs)...

The Bullwhip Effect is a supply chain management phenomenon wherein slight changes in consumer-level demand result in substantial order variability in upstream supply chain processes, thus leading to the inefficient generation of excess inventory costs, stock-outs, and instability in their operations....

The evolution of cybersecurity in a landscape with observable changes calls for sturdy and inventive alternatives for the escalating threats to traditional authentication approaches such as passwords and personal identification numbers (PIN). Keystroke dynamics emerges as a behavioral biometric that...

Packaging Standards; Packaging quality is key in the modern industrial sector where defects can cost-businesses large sums and harm their brand, image. Conventional ways of inspection are time-consuming, labour intensive and error prone, unsuitable for modern production. The project explores the use...

Brain tumor detection is increasingly becoming an issue in the medical field. A brain tumor is a growth or mass of abnormal cells in your brain cells develop uncontrollably. MRI (Magnetic Resonance Imaging) plays one of the primary roles in brain tumor detection where the tumor segmentation is required...

A 2-port MIMO (Multiple input Multiple Output) antenna is analyzed in this research. The antenna configuration is designed with antenna elements positioned orthogonally. FR4 foundation, with an antenna with a dielectric constant of 4.4 and a loss tangent of 0.02 is built. Within the below-6 GHz spectrum,...

It is important to consider multiple factors, including academic fit, finances, and personal preferences, while deciding to select a university. For this, we propose a hybrid recommendation system that uses Machine Learning (ML) and Natural Language Processing (NLP). Using acceptance rates, tuition fees,...

Sign language translation systems have been studied over and over and have become really important for helping deaf people talk to those who hear every day. This paper is a broad overview of what recent critical progress has been made in the conversion of one sign language into another, conveying efforts...

High-dimensional documents play a crucial role in classification tasks, yet their size often raises challenges and signals potential issues. Dimensional reduction, while offering both advantages and disadvantages, becomes pivotal in managing these challenges. However, improper dimensional reduction can...

Rapid advancements in power electronics have enabled the evolution of multilevel inverters (MLIs) for diverse applications. Compared to traditional two- level inverters, MLIs offer several advantages such as reduced voltage stress, minimized electromagnetic interference, and smaller filter requirements....

The “Two-Stage framework for Job Title Identification System in Online recruitment” presents an approach to accurately extracting and classifying job titles from online job advertisements using a two-stage process. This system addresses the challenge of parsing and understanding job titles from diverse...

Cardiovascular diseases (CVDs) pose a significant worldwide health issue, and early prevention and detection are therefore critical to lowering mor- tality. This heart disease prediction app relies on sophisticated machine learn-ing techniques to assess an individual’s risk level against vital health...

The purpose of an intrusion detection system is to prevent damaging attacks. Additionally, the tactics and technologies used by attackers are always changing. In the last work, we proposed employing random forest and support vector machines (SVM) in military defense environments (KDD dataset).Numerous...

This Paper focuses on enhancing the detection of student attentiveness in online classes through the use of Recurrent Neural Networks (RNNs). The system leverages video data to assess student engagement by analyzing both emotions and behavioral cues over time. RNN-based models are employed to handle...

The agriculture sector has become a focal point in addressing global greenhouse gas emissions due to its substantial contribution to the carbon footprint. As population growth and resource consumption accelerate, there is an urgent need for sustainable solutions to mitigate environmental impacts without...

Cyberbullying has become a major concern in digital communication, as they are appropriate for any other device, social media is on-demand giving rise to a new form of bullying called cyberbullying and their detection is required for immediate action. In this work, we propose an automated cyberbullying...

Secure web-based voting systems improve the accessibility of elections, especially for NRIs and the disabled, through internet-enabled device-based voting from anywhere. Incorporating OTP authentication, facial recognition, and surveillance via cameras enhances security and authenticity of voters. An...

This project proposes a wearable health monitoring device aimed at supporting individuals with physical and mental disabilities through real-time monitoring and direct alert capabilities. The primary objective is to create a reliable system that enhances user safety and independence by continuously tracking...

The security of industrial supply Chains (ISCs) has progressed with the incorporation of industrial internet of things (IIoT) and Blockchain (BC) technology, presenting sturdy defense in opposition to cyber attacks and ensuring operational resilience. This work examines lightweight machine learning algorithms...

Kidney tumor segmentation and identification. This system detects tumor in digital images of kidneys by means of analysis. Precision tumorlocalisation is achieved using U-Net model, so improving the segmentation and detection flow. This method guarantees better performance in medical diagnostics as well...

The remote sensing imagery classification is a vital application of machine learning technology going beyond satellite-based platforms into aerial imagery. These techniques substitute for conventional manual categorization, allowing for auto- mated detection of particular land features in geospatial...

One of the biggest problems today is how fast misinformation spreads, affecting people, groups, and entire societies. With so many of all of the people relying on social media such as WhatsApp, Facebook, and blogs, it’s more important now than ever it was to check for whether the information that we...

Precise identification and quantification of necrotic lung lesions in CT scans are important for analyzing lesion traits and monitoring disease advancement; how- ever, conventional techniques frequently face challenges in extracting detailed features and depend significantly on manual input. An optimized...

This project focuses on the development of a low-cost, web-controlled surveillance robot using the ESP32microcontroller, which offers Wi-Fi capabilities for real-time remote access. The robot is equipped with a camera module that streams live video to a web interface, allowing users to monitor and control...

Driver fatigue-induced road accidents are one of the primary threats to traffic safety, and this has driven the need for real-time detection systems. A driver drowsiness detection system based on deep learning, machine learning, and computer vision is proposed in this study for improving road safety....

In Computers must be able to identify human emotions and gestures by examining a person’s behavior, body language, emotional state, and hand gestures in order to engage with them intelligently. In interpersonal interactions, facial expressions and hand gestures let computers and people respond intelligently...

In today’s ever-changing educational environment, students and teachers face many challenges related to effective communication, attendance management, and resource accessibility. Traditional solutions address these needs alone, often resulting in ineffectiveness and timelessness. This study presents...

Subscription-based services have made digital platforms more accessible; their rapid rise comes with mixed blessings for users looking for low- cost deals. In this paper, we introduce Sab-Share, a web-based application that enables users to share subscriptions across different services, including OTT...

Monitoring the health of plants and diagnosing diseases at early stages is an important step to boost agricultural productivity. This project proposes an IoT plant monitoring system that collects images of plants, taking into consideration secondary environmental factors such as soil moisture, temperature,...

Personalized tax optimization and fraud detection pose a challenge to financial decision-making due to the constraints of conventional methods. This research provides a composite machine learning framework combining XGBoost with SHAP for personalized tax- saving recommendations and Random Forest with...

In traffic monitoring and surveillance systems that have been improved with the empirical mode decomposition (EMD) technology, this re- search suggests an effective radar-based method for vehicle classification. A type of signal known as micro-Doppler signatures can identify minute motion patterns in...

Agriculture is one of the long-established occupations across the globe. More than half of the population predominantly rely on agriculture as the primary occupation for their livelihood. Despite the advancement of technology farmers still follow traditional methods to carry out the tasks. The development...

Human carelessness frequently affects traditional water management systems, leading to waste and runoff. To address this issue, we have created Internet of Things solutions. Plans presented by Rankin: An immediate solution for water monitoring and management in a variety of applications, including water...