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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 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