Volume 13 | Issue 7

 Abstract

Speech is a fundamental means of communication that allows individuals to express thoughts, emotions, and ideas. However, millions of people worldwide are unable to communicate verbally due to conditions such as amyotrophic lateral sclerosis (ALS), brainstem stroke, locked-in syndrome, or severe paralysis. Traditional augmentative and alternative communication (AAC) devices, such as eye-tracking systems or text-based interfaces, are often slow, labour intensive, and less expressive. In recent years, advancements in neuroscience, machine learning, and brain-computer interface (BCI) technologies have paved the way for neuro-driven speech synthesis, which holds the promise of restoring communication for individuals with severe speech impairments.

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 Keywords

Brain-Computer Interface, Speech Impairment, Human-Computer Interaction, EEG Signal Processing, Deep Learning, Assistive Communication.

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 Abstract

The Autonomous UV Sanitization Robot is designed to provide safe, efficient, and chemical-free disinfection of indoor spaces using UV light. This robot operates autonomously, leveraging AI-based object detection and sensor technology to ensure thorough sanitization while prioritizing human safety. It is equipped with ultrasonic sensors to detect obstacles in its path and infrared (IR) sensors to identify objects on its sides, enabling smooth navigation. A front-facing camera, integrated with an AI- powered detection model, monitors the environment to detect human presence. If a person is detected, the robot immediately stops and turns off the UV light to prevent harmful exposure. The robot operates in two modes: Autonomous Mode, where it navigates and sanitizes without human intervention, and Manual Mode, allowing user control via a Bluetooth module. This dual functionality ensures flexibility in operation across various environments. Ideal for hospitals, schools, offices, and public spaces, the robot reduces the risk of infection while minimizing human effort and exposure. By combining advanced sensing, AI-driven decision- making, and autonomous navigation, this project offers an intelligent and reliable solution for maintaining hygiene and promoting public.

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 Keywords

AI-based Object Detection, Autonomous Robot, UV Sanitization, Bluetooth Control, Dual Mode Operation.

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 Abstract

The growing need for reliable and sustainable energy production has led to advancements in solar power-based charging systems. This project presents the development of a solar power charging system with RFID-based charge control, designed to optimize energy distribution and prevent unauthorized access. The system integrates solar panels, a charge controller, a battery storage unit, an RFID module, and a microcontroller to ensure secure and efficient charging. The RFID module is used for authentication and access control, ensuring that only legitimate users can initiate the charging process. Once authenticated, the microcontroller regulates the power flow from the solar panel to the battery and connected load, ensuring stable and efficient energy transfer. The system also monitors voltage and current levels to enhance performance and protect against overcharging or deep discharge. This implementation aims to provide a secure, cost-effective, and renewable energy-based charging solution that can be used in electric vehicle (EV) charging stations, and other energy distribution applications.

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 Keywords

Power generation, Solar charging, RF-ID authorization, portable, battery.

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 Abstract

Access to healthcare services in rural areas has long been a challenge, with limited resources and healthcare facilities often leaving residents underserved. The advent of telemedicine has brought about a promising solution, bridging the gap between rural communities and healthcare providers. This Project presents a novel approach to enhancing telemedicine services in rural areas through the deployment of AI-powered Telemedicine Kiosks. These kiosks are designed to provide convenient and comprehensive healthcare access to remote communities, empowering patients to receive timely medical consultations, diagnostics, and health information. Furthermore, these kiosks have the capability to dispense medicines based on patients' symptoms, further enhancing convenience and accessibility to essential medications.

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 Keywords

Telemedicine, Rural healthcare, Artificial Intelligence

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 Abstract

This project is all about building a hardware accelerator for Convolutional Neural Networks (CNNs) on an FPGA, specifically designed for real-time sign language detection. By harnessing the parallel processing power of FPGA, the CNN model is implemented in Verilog, ensuring fast and efficient inference. To enhance performance, the trained model weights are seamlessly integrated into the hardware, enabling high-speed processing while keeping power consumption low. To validate the design, the implementation undergoes simulation, resource utilization analysis, and FPGA deployment, showcasing the immense potential of hardware accelerators for deep learning applications.

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 Keywords

Hardware Accelerator, Convolution Neural Network, Field Programmable Gate Arrays, Sign Language Detection.

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 Abstract

The footstep-induced electricity generator and energy harvesting system is a cutting-edge solution intended to transform kinetic energy from footsteps into electrical energy through piezoelectric transducers incorporated in flooring. To maximize efficiency, the system combines renewable sources of a solar tree, windmill, and dual-axis solar tracking. The stored energy is saved in batteries and controlled by a power management system for real-world applications. A significant application is powering an AI-powered traffic controller. The technology can be used for high-traffic locations such as sidewalks, transportation hubs, and public areas to energize lighting, signage, and intelligent infrastructure. It lessens reliance on traditional energy sources, enables carbon footprint minimization, and facilitates sustainable energy operations. The process involves system design, selection of the energy harvesting mechanism, conversion, storage, and testing. In general, it provides a scalable, green solution to urban energy problems by tapping into energy from the daily movement of people.

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 Keywords

AI traffic controller, Energy storage, Footstep energy harvesting, Piezoelectric effect, Solar and wind energy integration.

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 Abstract

In recent years, cctv cameras are used in various locations. The data captured by these cameras can be used for event prediction, real-time monitoring, and goal-oriented analysis, including anomaly and intrusion detection. With advancements in Artificial Intelligence, several methods are applied for anomaly detection, in which convolutional neural networks (CNNs) powered by deep-learning have improved detection accuracy. This article aims to introduce a novel deep learning- based approach for crime detection in video surveillance footage. this method has been tested on the UCSD dataset and has demonstrated improved accuracy in detecting criminal activities.

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 Keywords

Anomaly detection, Artificial intelligence, CNN, Datasets, Deep learning, Machine learning.

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 Abstract

Water pollution is a major global concern, affecting health and the environment. Traditional water testing methods are slow and labor-intensive. This project presents a low-cost, real-time water quality monitoring system using sensors and an Arduino to measure pH, turbidity, temperature, Total dissolved solids, and flow rate. Data is displayed on a Liquid-crystal display screen, and alerts are triggered when values exceed safe limits. The system is energy-efficient, accurate, and user-friendly, making it ideal for use in remote and diverse environments.

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 Keywords

Water Pollution, Water Quality Assessment, Turbidity Sensor,pHSensor , Temperature Sensor ,Total Dissolved Solids (TDS) Sensor, Real-TimeMonitoring

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 Abstract

Oil skimmer robot is a new innovation created to solve the issue of oil spill cleanup and water pollution. It uses the new technology like the ESP32 microcontroller, Bluetooth HC-05 module, DC motors, pumps, water sensors, and ultrasonic sensors to skim oil from water surfaces autonomously. The robot is operated by an Android app to enable remote operation and real-time monitoring. Its major operations are oil skimming, pumping of water, obstacle detection, and oil-water separation. The technology is designed to enhance environmental cleanup, reduce manual labor, and automate oil spill cleanup

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 Keywords

Oil Skimmer, Oil Recovery, Hydrophobic, IoT, Sensors, Wastewater

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 Abstract

The Personalized Room Cooling Unit integrates air purification, cooling, noise cancellation, and smart technology into a compact device. It uses HEPA filtration to remove pollutants, a Peltier cooling module for precise temperature control, and noise cancellation technology for quiet operation. Equipped with IoT capabilities, it allows remote monitoring and control via smartphones or voice commands. This eco-friendly system improves indoor air quality and comfort, making it ideal for homes, offices, and other spaces while promoting health and sustainability.

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 Keywords

Personalized cooling, air purification, Peltier module, IoT integration, HEPA filter, noise cancellation, air quality monitoring, energy efficiency, smart home, sustainable living.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In recent years, cctv cameras are used in various locations. The data captured by these cameras can be used for event prediction, real-time monitoring, and goal-oriented analysis, including anomaly and intrusion detection. With advancements in Artificial Intelligence, several methods are applied for anomaly detection, in which convolutional neural networks (CNNs) powered by deep-learning have improved detection accuracy. This article aims to introduce a novel deep learning- based approach for crime detection in video surveillance footage. this method has been tested on the UCSD dataset and has demonstrated improved accuracy in detecting criminal activities.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

BarcodeScanning,WarehouseAutomation,SortingSystem,EmbeddedSystems,Arduino,Stepper Motor,ServoMotor

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 Abstract

In modern military operations, robots play a crucial role in carrying out high-risk tasks that are too dangerous for soldiers. Military integrated systems, including video screens, sensors, grippers, and cameras, allowing them to perform various functions effectively. These robots come in different shapes and designs, tailored to specific mission requirements. This system that utilizes a low- power IoT-based wireless sensor network to detect intruders (unauthorized individuals) and enable the robot to take necessary actions autonomously. The Intelligent Unmanned Robot (IUR) enhances national security by reducing human casualties and minimizing manual errors in defence operations. Designed specifically for military applications, this robotic system aims to protect soldiers and safeguard the nation from enemy threats. At border security posts, where tanks, missiles, and firearms pose significant dangers, the proposed robot can assist in defense operations.

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 Keywords

Intelligent Unmanned Robot (IUR), IOT Wireless network, Military robot.

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The Fuel Analyzer is a low-cost, real-time system developed to detect fuel adulteration and ensure fuel quality at petrol stations. Motivated by the need for transparency and engine safety, the device measures fuel volume, density, and purity using a combination of flow, pressure, and conductivity sensors. An Arduino Uno processes sensor inputs and displays real-time values on an (Liquid Crystal Display) LCD. The system was tested on various fuel samples, achieving up to 94% accuracy in detecting water-based adulteration. Unlike conventional analyzers, this design emphasizes portability, affordability, and easy integration with existing vehicle diagnostics. The analyzer is particularly suited for rural and small-scale fuel vendors, where manual quality checks are lacking.

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 Keywords

Arduino UNO, Conductivity sensor, IOT- based monitoring, Embedded system, Fuel volume measurement, Fuel density analysis, Fuel purity detection, Flow sensors, Fuel adulteration detection, Fuel management system, Pressure sensors, Real-time fuel monitoring.

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This paper presents a comprehensive approach to automated motion control of servo motors using an Arduino microcontroller, specifically designed for robotic applications. The study focuses on the precise actuation, synchronization, and real-time control of a robotic arm using SG90 servo motors. By integrating Arduino's computational capabilities with sensor feedback mechanisms, the system optimizes motion accuracy, responsiveness, and efficiency. The proposed framework leverages open-source hardware and software, offering a cost-effective, scalable, and flexible solution suitable for industrial automation, robotics research, and educational purposes. Additionally, the system implements optimized control algorithms to enhance smoothness and minimize latency in motor movements. Experimental results validate the system's ability to execute coordinated and precise robotic operations, demonstrating its practical viability for real-world applications in automation and robotics

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 Keywords

Servo Motors, Arduino, Motion Control, Robotic Arm, Automation, Microcontroller, Real-Time Control, Sensor Feedback, Precision Actuation, Robotics.

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 Abstract

This study has been undertaken to investigate the determinants of stock returns in Karachi Stock Exchange (KSE) using two assets pricing models the classical Capital Asset Pricing Model and Arbitrage Pricing Theory model. To test the CAPM market return is used and macroeconomic variables are used to test the APT. The macroeconomic variables include inflation, oil prices, interest rate and exchange rate. For the very purpose monthly time series data has been arranged from Jan 2010 to Dec 2014. The analytical framework contains. This work was intends to develop a eco-friendly hybrid reinforced composite material using Jute and E-glass fibers with fly ash filler material. The effect of filler materials on the static, dynamic and wear properties has been investigated. It was found that as the percentage of fly ash is increased there is considerable decrease in the tensile and flexural strength but an incremental improvement in the hardness of the material. Dynamic analysis was carried out in order find the natural frequency and mode shapes for material. Wear test were carried out at room temperature and at constant speed and time and by varying the load. Scanning Electron Microscope (SEM) analysis was done on the surface of the fractured tensile specimens in order to analyze is the performance of the hybrid composite material with fly ash as filler material.

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 Keywords

FRC, E-glass, Jute, fly ash, SEM.

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 Abstract

Development and Fabrication of a Bluetooth-Controlled Seed Sowing Machine" is a project aimed at making farming more efficient and less labor-intensive, especially for small-scale farmers. Sowing seeds manually can be time-consuming, tiring, and often leads to uneven distribution. This project offers a smart, affordable solution by automating the process and giving farmers better control over how seeds are planted. At the heart of the machine are two main components: an Arduino Uno and an ESP32 microcontroller. The Arduino controls a servo motor that handles the seed dispensing mechanism. This setup ensures that seeds are dropped with precision, helping maintain equal spacing and reducing waste. Meanwhile, the ESP32 with its built-in Bluetooth capability, controls four DC motors that drive the machine's movement. Using a simple smartphone app, the user can steer the machine wirelessly, adjusting direction and speed in real time. Designed to be compact, easy to use, and budget-friendly, this machine is ideal for use in small farms and varied field conditions. It doesn't require much power, and because it's Bluetooth-operated, there's no need for the farmer to follow it around or make manual adjustments constantly. This project is a great example of how technology, especially wireless communication and automation can solve real-world problems in agriculture. It helps save time, cuts down on labour, and improves planting accuracy, all while being easy to operate. In the bigger picture, it reflects a growing move toward smart farming and sustainable agricultural practices, where innovation supports both productivity and simplicity.

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 Keywords

Bluetooth-ControlledAutomationSmart ControlSmart FarmingAgricultureESP32

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 Abstract

Inconel 718 is a nickel-based superalloy which is more commonly used in aerospace, marine, and chemical applications due to its mechanical strength, oxidation and corrosion resistance, and stability at high temperatures. However, these same characteristics contribute to rapid tool wear, high cutting temperatures, bad surface finish, and rising costs of machining during cutting processes. This review focuses on the effect of cryogenically treated inserts and cryogenic cooling during the turning of Inconel 718. Cryogenic treatment basically increases hardness, toughness, and wear resistance of cutting inserts through deep cooling and microstructure refinement. Cryogenic cooling using liquid nitrogen generates an effective minimal cutting zone heat along with thermal softening of the tools and suppression of built-up edge formation. Results of experimental works carried out so far demonstrates that there was significant improvement in tool life and surface integrity with reduced cutting forces due to the combination of cryo-treated inserts and cryogenic cooling. These results show the benefit that might be obtained by cryogenic strategies to improve the machinability of Inconel 718, yielding sustainable and cost-effective manufacturing processes in high-performance applications.

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 Keywords

Inconel 718, Superalloy, Cryogenics

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 Abstract

Bananafibre(BNF),obtainedfromthepseudostemofthebananaplant,isattracting interest as a reinforcement material in polymer composites owing to its abundance, low cost, and eco-friendly nature. This review explores the latest developments in BNF-reinforced polymer composites (BFRPCs), focusing on their production, properties, and uses. It covers aspects like the fibres chemical makeup and surface treatments used to improvebonding with different types of polymers, including both thermoplastics and thermosets. The article also examines into the composite's mechanical strength, heat resistance, and biodegradability, as well as the methods used to manufacture them. This comprehensive analysis underscores the significant potential of BFRPCs as eco-friendly alternatives to synthetic composites in advancing a circular economy and sustainable development

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Natural Fibres; Polymer Composites; Sustainable Materials; Mechanical Properties

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 Abstract

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Nanoparticle; Nanofluids; Artificial neural network (ANN); Stability Analysis; Regression Modelling; Thermal conductivity

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 Abstract

With growing concern for the environment and stricter rules on using petroleum-based cutting fluids, there's been a strong push toward finding cleaner and safer alternatives in machining. Bio-oils made from plants, used cooking oil, and animal fats are standing out as promising options--they're less toxic, break down more easily in the environment, and offer great lubrication. This paper reviews how these bio-oils are being used in machining processes. It takes a closer look at their impact on overall machining performance also examines how enhancing bio-oils with nanoparticles or modifying them chemically can boost their effectiveness for industrial use. Comparative studies show that, in some cases, bio-oils can match or even outperform traditional fluids. Still, challenges like how well they hold up over time, how they're stored, and their cost need to be addressed. Overall, this review highlights the growing role of bio-oils in making manufacturing cleaner and more sustainable.

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WCO, sustainability, machining, bio-oils, cutting fluids, lubrication

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