Electronic Engineering and Computer Science

In this paper, a non-repeating quantum algorithm is introduced that depends on detectable Byzantine’s quantum solution that attains Clk synchronization in the arbitrary faultier processes’ presence through utilizing a double quantum system only. Precisely, it has been shown that general relativistic mass–energy equivalences intimate gravitational relation among Clks, however, energy’s quantum mechanical superposition resulted in a non-fixed metric background. Depending only on assumptions that gravitational principles held in such conditions, it has been shown that the Clks essentially gets involve over time dilation effect that ultimately results in a double Clk coherence loss. Therefore, the measured time through a double Clk is not defined precisely. Although, the time’s general relativistic notion is recuperated in the Clks conventional limits.

The rapid proliferation of digitally mediated travel and recreation services has exposed critical deficiencies in existing activity booking platforms, particularly their inability to integrate geospatial discovery, real-time session management, and secure multiuser interaction within a cohesive, scalable architecture. This paper presents the design, implementation, and empirical evaluation of WildSpire, a full-stack web-based platform for adventure activity discovery, management, and reservation. The system employs a layered Model-View-Controller (MVC) architecture built on Node.js and Express.js, supported by a MongoDB document-store backend and an EJS-based templating engine for dynamic client rendering. A modular microservice-style decomposition governs authentication (Passport.js), geospatial visualization (Mapbox GL), cloud-based media management (Cloudinary), and security middleware (Helmet, MongoDB-Sanitize, Express-Rate-Limit). Experimental evaluation across functional, performance, and security dimensions demonstrates average API response latencies below 220 ms under concurrent load, a booking workflow completion rate exceeding 97.3%, and zero critical security vulnerability incidents under standardized penetration scenarios. Comparative analysis against manual and legacy booking workflows confirms a 14-fold reduction in reservation completion time. The proposed platform demonstrates the viability of unified, modular, and secure web systems for domain-specific activity commerce, and establishes a replicable architectural template for similar geospatially enriched booking applications.

In the rapidly advancing realm of artificial intelligence, the Real-Time Image Arabic Captioning (RIAC) system presented in this paper is a pioneering framework designed to bridge the semantic gap between visual content and linguistic annotation in Arabic. By integrating the stateof-the-art Vision Transformer (ViT) and GPT-2 models, RIAC transcends conventional challenges in image captioning, offering real-time generation of contextually relevant and linguistically accurate Arabic captions. This hybrid model capitalizes on the strengths of advanced computer vision and natural language processing technologies, further augmented by real-time English to Arabic translation to accommodate the intricacies of the Arabic language. The RIAC system is rigorously evaluated on widely recognized metrics, yielding a CIDEr score of 0.91. RIAC showcases its capability to produce captions that are not only coherent and grammatically precise but also naturally resonant with the Arabic-speaking population. This work marks a significant leap towards creating a more inclusive and accessible digital ecosystem, paving the way for future innovations in multilingual image captioning technologies.

Fibrous nanomaterials such as electrospun materials have many uses ranging from tissue engineering to biosensors. High‐resolution imaging is an important component in the characterization of these materials. Important parameters required to predict and study the properties of fibre rich materials include diameter and orientation distribution as well as fibre spacing. The orientations and the relative dimensions of the fibres can be measured via specially designed imaging software. Difficulties in this measurement process can arise if fibres are distributed in close proximity to each other in relation to the resolution of the imaging modality. For example, if some automation is required in the measurement process and, particularly, if the automated processes are not designed for situations where the fibres are in close proximity to each other. This work is therefore concerned with the development of automated measurement techniques to provide estimates of the diameters of fibres and ...

Now a days the home safety detection system play the important role for the security of people. Since all the people from the home goes to work on daily bases, it make impossible to have check on the appliances available at home specially LPG gas cylinder, wired circuits, Etc. whereas in industrial system it also make difficult for the labors to keep the track of every second so to work on this problem, the system is develop which will keep the track on various home appliances such as LPG gas cylinder, wired circuit, etc. this system uses MQ6 gas sensor to detect inflammable gas leakage and LM35 temperature sensor which will sense the sudden rise in temperature than above the room temperature. This makes easy for both the commercial as well as domestic sector to keep the track on problem faced on daily bases. This system effectively track the problems arises in day to day life.

In India farming is done by traditional methods. Farmers plants crops traditionally without having the knowledge about the contents of the soil and as a result farmer do not gain sufficient profit. The existing method of soil testing is the manual testing starts which by taking soil samples and then sending it to laboratories. The manual process is time consuming and also not feasible. Due to human intervention, there are chances of human errors and so farmers may receive incorrect report. Thus, Development of agriculture using technology is much needed as to minimize the financial losses suffered by the farmers. Thus, our proposed module will provide a brief overview of soil components and other parameters affecting the growth of a crop. Our module is a complete platform designed to such a degree that it incorporates each and every information about the crop from initial level to advance level.

This research paper presents the design and development of a cloud-based Event Management System capable of efficiently managing event creation, user registration, real-time updates, and automated coordination between stakeholders. The system integrates modern web technologies including React (Vite), Node.js, Express, MongoDB, and Socket.IO, deployed on Amazon Web Services (AWS) EC2 for enhanced scalability and reliability. The objective is to eliminate the drawbacks of traditional event management processes by automating tasks, improving communication, and enabling real-time interactions between organizers and attendees. The system includes features such as event scheduling, ticket handling, attendee management, live announcements, and secure authentication. This paper discusses system architecture, module design, implementation strategy, backend workflow, testing, and deployment procedures. Results show that the cloud-based approach significantly enhances performance, reduces operational overhead, and offers a seamless user experience. The proposed system demonstrates a practical and scalable solution for institutions, companies, and event organizations.

In today's fast-paced restaurant industry, many businesses still rely on traditional methods like handwritten orders, verbal communication, or basic spreadsheets. These outdated processes often lead to mistakes such as incorrect billing, missing orders, slow service, and poor coordination between staff. As customer expectations continue to grow, restaurants need a digital solution that makes the ordering and managing process fast, smooth, and reliable. To solve these challenges, we developed RESTO-a complete web-based Restaurant Management System. The system has two main interfaces: • Client Side: Where customers can browse the menu and place orders for food, beverages, or meals directly from the restaurant interface. • Admin Side: Where restaurant staff or administrators can monitor and manage incoming orders, update the menu, manage staff details, track order status, and control overall system operations. RESTO is built using HTML, CSS, PHP, and JavaScript, with MySQL as the database. The project runs locally using the XAMPP server, where the Apache service handles request processing and MySQL stores the restaurant's data. Key features of RESTO include real-time order updates, digital menu management, user authentication, order status tracking, and centralized control through an intuitive dashboard. The system ensures quick service, reduces manual workload, eliminates ordering errors, and improves the customer experience.

In today's fast-paced restaurant industry, many businesses still rely on traditional methods like handwritten orders, verbal communication, or basic spreadsheets. These outdated processes often lead to mistakes such as incorrect billing, missing orders, slow service, and poor coordination between staff. As customer expectations continue to grow, restaurants need a digital solution that makes the ordering and managing process fast, smooth, and reliable. To solve these challenges, we developed RESTO-a complete web-based Restaurant Management System. The system has two main interfaces: • Client Side: Where customers can browse the menu and place orders for food, beverages, or meals directly from the restaurant interface. • Admin Side: Where restaurant staff or administrators can monitor and manage incoming orders, update the menu, manage staff details, track order status, and control overall system operations. RESTO is built using HTML, CSS, PHP, and JavaScript, with MySQL as the database. The project runs locally using the XAMPP server, where the Apache service handles request processing and MySQL stores the restaurant's data. Key features of RESTO include real-time order updates, digital menu management, user authentication, order status tracking, and centralized control through an intuitive dashboard. The system ensures quick service, reduces manual workload, eliminates ordering errors, and improves the customer experience. INTRODUCTION Running a restaurant involves many daily tasks-taking customer orders, updating the menu, tracking the kitchen status, managing staff, and handling billing. In many restaurants, these tasks are still done manually through handwritten notes, verbal communication, or basic register entries. While this method works to some extent, it becomes stressful, confusing, and inefficient as the restaurant grows or becomes busy. Some of the common problems faced with manual restaurant management include: • Mistakes in Orders When orders are written or communicated verbally, there is a higher chance of errors such as wrong items, missing dishes, or incorrect bills. These problems affect customer satisfaction and slow down service. • No Real-Time Tracking Without a digital system, staff cannot easily see which orders are pending, completed, or delayed. Menu updates, stock changes, and special requests also become hard to track quickly. Creating reports such as daily sales, most-ordered items, or performance tracking becomes time-consuming. This makes planning and decision-making difficult. • Increased Workload A lot of time and effort is wasted writing orders, updating menus manually, confirming requests, and coordinating between the kitchen and serving team. This reduces efficiency, especially during rush hours. Because of these challenges, restaurants today need a reliable digital solution that can simplify work, reduce manual effort, and make service faster. To address this, we developed RESTO-a Restaurant Management System designed to automate and organize restaurant operations. RESTO has two main interfaces: Client Side: Where customers can view the digital menu and place their food orders. Admin Side: Where restaurant staff can manage orders, update the menu, track activity, and handle internal processes. RESTO is built using HTML, CSS, JavaScript, and PHP, with MySQL as the database. It runs on a XAMPP Server, using Apache to process system requests and Mysql for data storage. Running a restaurant manually may seem simple, but as the number of customers grows, handling everything with paper notes or verbal communication becomes stressful and unorganized. Restaurants that still follow traditional methods to take orders, manage staff, and update menus often face confusion, delays, and service mistakes. Without a proper digital system, it becomes difficult for staff to keep track of ongoing orders, menu changes, and customer requests-all of which affect overall service quality. When there is no centralized platform, communication between the kitchen and serving staff becomes slow and unclear, leading to errors that could have been avoided. Some of the common problems faced in manual restaurant management include: • Order-taking_mistakes: Verbal or handwritten orders can easily lead to missing items, incorrect food preparation, duplicate orders, or wrong billing. • No live order tracking: Staff do not have a single place to check which orders are pending, cooking, or ready, causing delays and confusionespecially in rush hours. • Slow and unclear communication: If a customer changes an order or cancels something, it may not reach the kitchen or serving team on time, which affects customer experience. • No organized data or reports: Without a system, analyzing sales, popular dishes, menu performance, or staff productivity becomes difficult and time-consuming. Because of these challenges, there is a need for an automated solution that makes restaurant work simpler, faster, and more organized. RESTO -Restaurant Management System is designed to solve these issues by providing a centralized platform where customers can easily place orders and restaurant staff can manage everything-from the menu to order processing-with accuracy and real-time updates. The idea behind developing RESTO -Restaurant Management System comes from the growing need to modernize how restaurants manage their daily operations. Many restaurants still depend on traditional methods such as handwritten orders, verbal communication, or basic spreadsheets. As business grows, these methods become slow, confusing, and difficult to manage. RESTO aims to solve these problems and improve the overall workflow. The main motivations behind building this system include:

This research paper presents the design, development, and deployment of a full-stack web application inspired by the concept of Airbnb. The project integrates a robust backend built using Node.js and Express, a scalable MongoDB database, and an EJS-based frontend enhanced with modern UI techniques. Core features include secure authentication and authorization using Passport.js, password hashing and salting, cookie-based session management, MVC architecture implementation, validation schemas using JOI, Cloudinary-powered image uploads with preview capabilities, and geocoding functionality for location-based listings. The system supports listing creation, editing, deletion, reviews, owner-based permissions, map markers, popups, flash message feedback, and an optimized user interface. This paper follows the IEEE format and documents the methodology, techniques, and architectural decisions behind the project.

This research paper presents the design, development, and deployment of a full-stack web application inspired by the concept of Airbnb. The project integrates a robust backend built using Node.js and Express, a scalable MongoDB database, and an EJS-based frontend enhanced with modern UI techniques. Core features include secure authentication and authorization using Passport.js, password hashing and salting, cookie-based session management, MVC architecture implementation, validation schemas using JOI, Cloudinary-powered image uploads with preview capabilities, and geocoding functionality for location-based listings. The system supports listing creation, editing, deletion, reviews, owner-based permissions, map markers, popups, flash message feedback, and an optimized user interface. This paper follows the IEEE format and documents the methodology, techniques, and architectural decisions behind the project.

This research paper presents the design, development, and deployment of a full-stack web application inspired by the concept of Airbnb. The project integrates a robust backend built using Node.js and Express, a scalable MongoDB database, and an EJS-based frontend enhanced with modern UI techniques. Core features include secure authentication and authorization using Passport.js, password hashing and salting, cookie-based session management, MVC architecture implementation, validation schemas using JOI, Cloudinary-powered image uploads with preview capabilities, and geocoding functionality for location-based listings. The system supports listing creation, editing, deletion, reviews, owner-based permissions, map markers, popups, flash message feedback, and an optimized user interface. This paper follows the IEEE format and documents the methodology, techniques, and architectural decisions behind the project.

This research paper presents the design and development of a cloud-based Event Management System capable of efficiently managing event creation, user registration, real-time updates, and automated coordination between stakeholders. The system integrates modern web technologies including React (Vite), Node.js, Express, MongoDB, and Socket.IO, deployed on Amazon Web Services (AWS) EC2 for enhanced scalability and reliability. The objective is to eliminate the drawbacks of traditional event management processes by automating tasks, improving communication, and enabling real-time interactions between organizers and attendees. The system includes features such as event scheduling, ticket handling, attendee management, live announcements, and secure authentication. This paper discusses system architecture, module design, implementation strategy, backend workflow, testing, and deployment procedures. Results show that the cloud-based approach significantly enhances performance, reduces operational overhead, and offers a seamless user experience. The proposed system demonstrates a practical and scalable solution for institutions, companies, and event organizations.

This paper presents an AI-powered web-based
Missing Person Detection System designed to accelerate
and enhance the search for missing individuals. By
integrating advanced machine learning, facial
recognition algorithms, and robust database
management within the Django framework, the system
enables users—families and law enforcement—to upload
images and relevant data, match faces across a
repository, and receive notifications upon matches. The
solution emphasizes real-time detection, accurate
matching, and scalable, secure architecture. The
project's future scope involves real-time CCTV
integration, mobile application deployment, and cloud-
based expansion to maximize reach and efficiency.

This paper presents an AI-powered web-based Missing Person Detection System designed to accelerate and enhance the search for missing individuals. By integrating advanced machine learning, facial recognition algorithms, and robust database management within the Django framework, the system enables users-families and law enforcement-to upload images and relevant data, match faces across a repository, and receive notifications upon matches. The solution emphasizes real-time detection, accurate matching, and scalable, secure architecture. The project's future scope involves real-time CCTV integration, mobile application deployment, and cloudbased expansion to maximize reach and efficiency.

The IoT industry protection system, employing a Node MCU controller, aims to safeguard industries against potential losses and accidents through the utilization of Internet of Things technology. Gas leaks can precipitate fires, resulting in substantial industrial losses. Hence, the system necessitates instantaneous fire detection in scenarios like furnace blasts. Moreover, addressing low lighting conditions within industries is imperative to mitigate accident risks. To address these the system integrates temperature, light, and gas sensors with the NodeMCU controller, along with an LCD screen for interface. Continuous scanning of sensor data enables the detection of fire, gas leaks, or inadequate lighting, thus averting potential accidents and minimizing losses. The collected data is transmitted online via the WiFi module for remote monitoring and management. Subsequently, the IoT server displays this information online, facilitating prompt responses to ensure industrial safety.

This paper presents two novel heuristic algorithms for the design of wireless access networks (QoS-HWNDA-1, QoS-HWNDA-2) adapted in the case of QoS networks, which is the prevalent situation in the evolution of 5G technology. Emphasis was given to the design of CDMA based wireless networks and Fixed Wireless networks considering QoS architectures. The objectives of these methods are first to place a number of access points/base stations in a number of candidate sites and then to assign a number of fixed wireless terminals to the selected access points/base stations, while ensuring QoS requirements. Both methods are based on Graph Theory and they are essentially greedy algorithms. Except from capacity constraints, wireless reception characteristics are also considered. The algorithms are capable of designing medium and large-scale networks at polynomial time. Both algorithms were compared with a rival optimization problem through a series of tests. The results indicate that as regards design costs the performance of the proposed heuristic algorithms is very close to this of the equivalent optimization problem. The solution times for the proposed heuristic algorithms are smaller especially when the number of the candidate access points/base stations becomes large.

A great challenge in large scale wireless networks is the resource management adaptability to dynamic network traffic conditions, which can be formulated as a discrete optimization problem. Several approaches such as genetic algorithms and multi agent techniques have been applied so far in the literature for solving the channel allocation problem focusing mainly on network base-stations representation. A very promising computational intelligence technique known as ant colony optimization which constitutes a special form of swarm intelligence has been used for solving routing problems. This approach has been introduced by the authors for improving channel allocation in large scale wireless networks, focusing on network procedures as the basic model unit and not on network nodes as so far reported in the literature. In this paper, a novel channel allocation algorithm based on ant colony optimization and multi agents is thoroughly analyzed as well as important implementation issues bas...

Coverage is one of the fundamental metrics used to quantify the quality of service (QoS) of sensor networks. In general, we use this term to measure the ability of the network to observe and react to the phenomena taking place in the area of interest of the network. In addition, coverage is associated with connectivity and energy consumption, both important aspects in the design process of a Wireless Sensor Network (WSN). On the other hand, simulating a WSN involves taking into account different software and hardware aspects. In this paper we attempt to present a simulation framework suitable for integrating coverage mechanisms in WSN emulation using a layered architecture and a fitting scheduling model. The suggested model is derived after a critical overview and presentation of the coverage strategies as well as the simulation approaches for WSN developed so far. The main advantage of the proposed framework is its capability to handle concurrent events occurring at WSN deployment and operation through the suitable layered scheduler integrated.

The increasing number of cellular users and the demand for broadband mobile communications (3rd and 4th generation) raises the problem of bandwidth availability and the associated channel allocation strategies. Moreover, Quality of Service (QoS) is the challenge for such modern wireless multimedia telecommunications. This paper presents new algorithms for efficient bandwidth management of GSM cellular multimedia systems. Besides, it proposes a comprehensive simulation system for evaluating channel assignment schemes in QoS multimedia cellular systems incorporating their principles, entities and concepts involved. The proposed system is implemented in Java, in order to create an educational generic simulation environment with the future capability of internetworking. The system is designed with the goal to be efficient in simulating large scale generic cellular multimedia telecommunication systems.

Simulation models are used in the design, development and evaluation of wireless communication systems. While basic network entities as Base Stations and users are always taken into account in such simulation modeling, a critical but currently underestimated factor that affects the simulated network behavior is the corresponding simulation model which represents the physical activities and the events of the network. A novel event scheduling mechanism for supporting concurrent network events and a novel network modeling methodology based on the multi-agent concept implemented through multi-threading technology is presented in this paper. The state of the art event scheduling mechanism supports only sequential events and on the other hand, the multi-agent technology has been used only for modeling network nodes. Additionally, the technical aspects of the multi-threading technology regarding the agent implementation and scheduling for simulating wireless communication systems has not been investigated so far in the literature. The proposed simulation framework in this paper gives improved solutions to the above issues.

Land Use and Land Cover (LULC) classification is very important for monitoring the environment, planning cities, managing agriculture, and responding to disasters. Satellite imagery provides broad spatial and temporal coverage. It has been a key source of data for these tasks [16, 12]. Traditionally, machine learning methods like Support Vector Machines (SVM), Random Forests (RF), and Decision Trees (DT) used manual features to study patterns in remote sensing data [13, 16]. However, these methods often had difficulty with complex urban textures, subtle class boundaries, and changes in spectral data, especially in high-resolution images [12, 26]. In recent years, deep learning techniques, especially Convolutional Neural Networks (CNNs), have transformed land use and land cover (LULC) classification by automatically learning spatial and spectral features [12, 26, 1]. However, CNNs have limitations when it comes to modeling long-range dependencies, inter-class similarities, and relationships in multimodal data [13, 15]. Vision Transformers (ViTs), initially created for natural image recognition, offer a promising solution. They

The implementation of an IoT-based smart night patrolling robot is presented in this paper, utilizing an Arduino Uno, camera module, sound sensor, ultrasonic sensor, motor driver, motors, Nodemcu, and buzzer. The proposed robot is designed to autonomously patrol a designated area and capture images and videos of the area using the camera module. The ultrasonic sensor is used to detect obstacles and prevent collisions, while the sound sensor is used to detect unusual sounds and alert the user. The buzzer is included to provide an audible alarm in case of any significant disturbance in the patrolling area. The robot is designed to move around and change directions using the motor driver and motors, which are operated by an Arduino Uno. The Nodemcu provides internet connectivity, enabling remote monitoring and control. The proposed system can be used for a variety of applications, such as surveillance and security, and has the potential to improve the efficiency and effectiveness of night patrolling operations. The proposed system is developed at a low cost, making it accessible to a wider range of users. The implementation of the proposed system has been tested, and the results indicate that the system is efficient and effective in detecting and responding to environmental stimuli. The system is controlled using a web-based interface, and the users can monitor and control the system remotely..

In this thesis, a comprehensive investigation of the state-of-the-art guidelines for the conducted schemes in the near vicinity of the human body has been provided. The primary objectives of this work have been mainly focused on the electromagnetic (EM) wave exposure at both the microwave and millimetre-wave (mm-wave) frequency bands, along with their thorough analyses for a number of wireless technologies, such as the smart meters (SMs) and multiple-input multiple-output (MIMO) antennas. This work has undertaken a detailed theoretical and numerical modelling, as well as experimental measurements to propose the frameworks for the exposure conditions regarding the advanced wireless systems and applications. The employed numerical methods have been validated using the finite integration technique (FIT)-based simulations. The specific absorption rate (SAR) distributions have been determined using the anatomically realistic human models at various frequency bands. In this regard, each human model is assigned with the age-and frequency-dependent (AFD) dielectric properties, based on the novel expressions. This has then resulted in the representation of dispersive and age-dependent dielectric properties, in order to potentially improve the accuracy

EditEase is an advanced web-based image editing application that leverages state-of-the-art artificial intelligence to democratize complex photo editing tasks such as object removal, color transformation, smart filling, object replacement, and image restoration. Its core principle is accessibility-offering powerful editing tools to users of all technical backgrounds within a modern, responsive interface. The system uses cloud APIs and modular architecture built with Next.js, React, and Node.js to deliver intuitive one-click transformations, real-time previews, and seamless high-quality downloads. The robust backend supports secure user authentication, persistent storage, and batch processing, positioning EditEase as a unique, efficient, and scalable platform for digital creators, students, and professionals.

Skill entity recognition is a crucial task for aligning educational curricula with the evolving needs of the industry, particularly in multilingual job markets. This study introduces modified attention score transformer encoder (MAS-TENER), a novel transformer-based model designed to enhance the recognition of skill entities from Indonesian job descriptions. The proposed model modifies the attention mechanism by integrating relative positional embeddings and removing the scaling factor in self-attention. These improvements enhance the context of tokens, allowing for the accurate establishment of hard skills, soft skills, and technology skills. The MAS-TENER model was pre-trained and fine-tuned using a combinF.ation of job description datasets and additional corpora, achieving an F1-score of 90.46% at the entity level. The experimental results demonstrate the model's ability to handle unstructured, mixed-language job descriptions, with significant potential for curriculum reform and the development of new workforce capabilities. The study demonstrates the efficacy of the MAS-TENER model as an effective response for any natural language processing (NLP) task in low-resource languages. Moreover, the scope of long-term job market analytics in action research has been a key skill set in the education policy arena, demonstrating collaborative workforce capabilities.

Intelligent solutions that maximize collection, improve safety, and lessen environmental impact are required to meet the growing need for effective, sustainable waste management in urban and semi-urban settings. The design and implementation of an Internet of Things-based garbage monitoring system that uses cloud computing, real-time data collecting, and sensor integration to expedite the waste collection process is presented in this study. The system improves worker safety and environmental awareness by using gas sensors (MQ-135) to detect dangerous gases like ammonia and methane and ultrasonic sensors to track bin fill levels. GPS modules offer accurate location tracking, and a NodeMCU microcontroller gathers and sends this data over Wi-Fi to cloud platforms (ThingSpeak and Virtuino). Dynamic route optimization is made possible by real-time warnings and an intuitive dashboard, which lowers needless travel, operating expenses. GPS modules offer accurate location tracking, and a NodeMCU microcontroller gathers and sends this data over Wi-Fi to cloud platforms (ThingSpeak and Virtuino). Dynamic route optimization is made possible by real-time notifications and an intuitive dashboard, which lowers greenhouse gas emissions, operational expenses, and pointless travel. The suggested system is flexible and scalable for use in a variety of settings, such as public institutions, residential complexes, industrial zones, and towns. The solution supports the objectives of smart cities and makes the urban ecosystem cleaner, safer, and more responsive by integrating datadriven decision-making.

Elective subject selection in educational institutions is an important process that affects student's academic growth and teacher`s workload. Unfortunately, most institutions still handle this process manually with paperwork. This method is slow, prone to mistakes, and lacks transparency. Students often get confused about which electives are available and which teachers are assigned to them. Meanwhile, teachers have a hard time with scheduling, sharing study materials, and tracking student requests. Heads of Departments and Principals also struggle to manage approvals, coordinate subject assignments, and monitor performance effectively. To solve these problems, the proposed system offers a centralized digital platform that connects Principals, Heads of Departments, Teachers, and Students in one place. The system automates important tasks such as student registration, elective subject selection, teacher approval, test scheduling, distribution of study materials, and performance tracking. It ensures accuracy, cuts down on delays, and removes the need for paperwork while providing full transparency. By digitizing the whole process, the system improves efficiency, accountability, and speeds up decision-making, benefiting both administrative workflow and the overall student experience.

The conventional voting scheme employs paper-based ballot to verify votes. This voting scheme is insecure due to the attributed shortcomings including ballot stuffing, ballot snatching and voter's impersonation. In this paper, we present the design and development of secure e-voting to ensure a free, fair and credible election where the preference of electorate counts. This proposed system solves the authentication, integrity and confidentiality security issues of e-voting in kiosk and poll site evoting scenarios using unimodal fingerprint biometrics and Advanced Encryption Standard based Wavelet based Crypto-watermarking Approach. The developed system solves: The possibility of blundering voter's authentication, integrity and confidentiality of vote stored in the server. The results after qualitative evaluation of the system with antiwatermarking detectors revealed that the developed secure e-voting system could serve as a platform for the delivery of credible e-election in developing countries with significant digital divides.

Elective subject selection in educational institutions is an important process that affects student's academic growth and teacher`s workload. Unfortunately, most institutions still handle this process manually with paperwork. This method is slow, prone to mistakes, and lacks transparency. Students often get confused about which electives are available and which teachers are assigned to them. Meanwhile, teachers have a hard time with scheduling, sharing study materials, and tracking student requests. Heads of Departments and Principals also struggle to manage approvals, coordinate subject assignments, and monitor performance effectively. To solve these problems, the proposed system offers a centralized digital platform that connects Principals, Heads of Departments, Teachers, and Students in one place. The system automates important tasks such as student registration, elective subject selection, teacher approval, test scheduling, distribution of study materials, and performance tracking. It ensures accuracy, cuts down on delays, and removes the need for paperwork while providing full transparency. By digitizing the whole process, the system improves efficiency, accountability, and speeds up decision-making, benefiting both administrative workflow and the overall student experience.

The rapid expansion of Bangladesh's power grid to meet growing energy demands necessitates an efficient and reliable approach to transmission line fault detection. This paper presents the design and implementation of an IoT-based transmission line fault detection system tailored specifically for Bangladesh's unique environmental and infrastructural challenges. By leveraging real-time data from a network of sensors monitoring current, temperature, and environmental conditions, the system enables immediate detection and response to unsymmetrical faults, significantly reducing the risk of prolonged power outages. The proposed system integrates GPS for precise fault location, GSM for alert notifications, and Wi-Fi for remote monitoring, creating a comprehensive solution that enhances grid reliability. Additionally, the system's prototype model demonstrates its practical applicability, offering a user-friendly interface for grid operators and proving its effectiveness through real-time monitoring and fault detection. This research contributes to the modernization of Bangladesh's power infrastructure, aligning with the nation's goals of sustainable development and energy security by ensuring an uninterrupted and stable power supply.

Sensor technology has improved significantly in the last decade. Third generation sensors are now available to use in various walks of life including healthcare, gaming, agriculture, vehicular industry etc. One of the major use of sensors now a days is continuing and real time monitoring of patient specifically elderlies. Many health issues face by elderlies these days including falling because of weakness of muscle and their overall strength. These sensors can be used to monitor vital sign in elderly people who live alone. Various third generation sensors have been developed by industries including monitoring physiological parameters, movements, ECG, EMG, blood pressure and another vital sign etc. In this paper we review related technologies, different mechanism proposed for assisting elderlies specifically for falling and vital sign monitoring. Finally, we present our analysis of the review of existing literature.

The system proposed can be used to regular checkup of the COVID patients while maintaining the social distancing. Also, the data sensed by the sensors is directly sent to doctor, reducing the cost of paying regular visits to doctor. The Iot platform used in the system helps to transfer the real time patient's data remotely to host device. Daily health record can be maintained and can be viewed easily on graphs charts ease for doctors to see any abrupt changes in oxygen level or rise in temperature. To track the patient health micro-controller is in turn interfaced to an LCD display and wi-fi connection to send the data to the web-server (wireless sensing node). In case of any abrupt changes in patient heart-rate or body temperature alert is sent about the patient using IoT. This system also shows patients temperature and heartbeat tracked live data with timestamps over the Internetwork.

What is Full Stack Development? Full Stack Web Development refers to the practice of working on both the Front-End (client-side) and Back-End (server-side) of a web application. A full stack developer is proficient in all layers of the "stack," ensuring a seamless connection and efficient functionality from the user interface down to the database. The Web Development Stack The "stack" is generally divided into three main layers: 1. Front-End (Client-Side): Everything the user sees and interacts with directly in their browser. This is the Presentation Layer.

Liquefied petroleum gas (LPG) accidents pose significant safety risks, requiring continuous monitoring and Internet of Things (IoT) technology to prevent gas leakage and ensure human safety. This work proposes distributed field-oriented IoT gas sensing robots for detecting dangerous flammable gases like Ammonia, Sulphur Dioxide, Nitrogen Dioxide, and Carbon Dioxide. The SnoLURk solution enables cost-effective IoT gas leak detection in indoor and outdoor robots using budget-friendly casings and sensors. The study also discusses a robotic system for gas leak detection, aiming to detect and combat burglary using ZigBee and GSM modules. Cloud support allows Wi-Fi zone residents to receive alerts and send investigators via email, enabling remote data analytics monitoring. The IoTbased Worker's Health Monitoring System improves health and safety practices in industrial environments by monitoring workers' health 24/7. It allows on-site and off-site monitoring, enabling quick intervention and avoiding complications. The system's applications include construction, mining, manufacturing, and healthcare. Future versions may include improved sensors and machine learning.

Crowdfunding has emerged as a popular method for raising capital in various domains, providing a platform for entrepreneurs and innovators to access funds from a broad audience. This paper explores the application of Ethereum blockchain technology to enhance crowdfunding processes, emphasizing decentralization, transparency, and security. Ethereum's smart contract capabilities enable the creation of decentralized crowdfunding platforms, offering a trustless environment where contributors and project creators interact directly without relying on intermediaries. The use of Ethereum's native cryptocurrency, Ether(ETH), facilitates seamless, borderless transactions, eliminating the need for traditional banking systems and reducing transaction costs. Decentralized crowdfunding on the Ethereum blockchain enhances transparency through the immutability of transactions recorded on the blockchain. Contributors can verify the allocation offunds, ensuring that they are used as intended by the project creators.

The aim of this paper is to develop home automation system based on IOT using Wi-Fi based microcontroller. As scope of technology is widening every day, we are making our tech advance in mobile, robotics, Machine Learning, then why an exception for our home. Today houses are gradually transferring from ordinary/human’s input-based appliances to smart/IOT enabled appliances to be controlled remotely. At Present, existing home automation systems use technology that is limited to only that device. So, in a nutshell, we are making our devices IOT enabled not our homes.

Supreme likelihoods of fire disasters in buildings from consulted literatures includes: abnormal rise in temperature, gas leakages from gas cylinders and her accessories, and increasing concentration of smoke from burning materials. On this premise, three respective sensors were saddle with the responsibility of monitoring any anomalies from the aforementioned likelihoods of fire in market shops of which their presence above threshold possess a treat to lives and properties. These sensors are: LM35 for monitoring temperature, MQ5 and MQ7 for monitoring gas and smoke respectively. For LM35, a threshold of 50 0 C was used as a threshold for alarm and for MQ5 and MQ7, a threshold of 1000PPM (Part per Million) was used as the alarm threshold. Each sensor was grafted into four respective modeled market stalls. Threshold for smoke and gas were chosen based on the standard set by OSHA (Occupational Safety and Health Administration) and that of temperature was chosen based on the firing point of most materials that can easily kindle in flames, predominantly found in market stalls as discovered in consulted literatures. Once smoke is detected and its concentration approaches threshold, a fire fighting mechanism which is positioned strategically in the market stall, is triggered automatically to combat the fire generating the smoke. A GSM (Global System for Mobile Communication) module called SIM 800L is used to send notification as alarm through text message to owners of respective market shops when threshold is being approached. Lastly, an LCD (Liquid Crystal Display) display is used to display the status of all sensors to users. The brain of the whole project control rest on the shoulders of a microcontroller called ATMEGA328p.