Volume 13 | Issue 7 |

 Abstract

This study explores the implementation of an Adaptive In-Loop Filter (AILF) for High Efficiency Video Coding (HEVC) utilizing deep learning technique. The need for effective compression techniques that preserve excellent visual quality has grown as video content continues to spread. Even though the traditional in-loop filters perform well, they frequently have difficulties maximizing performance in a variety of video scenarios and environments. According to the properties of the video being analyzed, this study suggests an AILF that includes Convolutional Gated Recurrent Unit (ConvGRU), a type of Recurrent Neural Network typically involves enhancing reconstructed frames by exploiting temporal dependencies across frames. In addition to enhancing reconstructed frames, the AILF performs better than traditional techniques in terms of Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), indicating its potential for practical uses in broadcasting and video streaming. By demonstrating how well deep learning techniques can be integrated into video processing tasks, this work adds to the continuous developments in video coding technology.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Adaptive in-loop filter, Deep learning techniques, High Efficiency Video Coding, Convolutional Gated Recurrent Unit, Neural Network.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the design and development of an Internet of Things based solution for urban environmental monitoring and pollution hotspot detection. The system integrates with a Espressif Systems 32-WROOM microcontroller for sensor data acquisition, while the Espressif Systems 32 Wi-Fi module processes the data and sends it to a central server, where Geographic Information System mapping is used to visualize pollution hotspots in real time. The Long Range Radio Frequency RF module extends the communication range in urban areas with limited cellular coverage. Geographic Information System mapping helps visualize pollution levels across urban areas, facilitating the identification and management of pollution hotspots. To enhance pollution mitigation, the system integrates an Active Carbon Filter, which helps reduce airborne pollutants before data collection. The filter is placed near gas sensors (MQ-135, MQ-7, MQ-8) to compare pre-filtered and post-filtered air quality, providing insights into filtration efficiency. It actively removes harmful gases such as carbon monoxide, Nitrogen Oxides, and Volatile Organic Compounds, supporting sustainable urban management. This system supports data-driven decision-making and timely interventions, contributing to sustainable urban planning and public health initiatives. The system aims to offer valuable insights into pollution trends, aiding in the identification of critical areas for intervention. Additionally, the use of a low-power, low-cost microcontroller makes it suitable for large-scale deployment in urban environments.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet of Things (IoT), Long Range radio Frequency (LoRa RF), ESP32 Wi-Fi module, Metal Oxide (MQ), carbon monoxide (CO), Nitrogen Oxides (NOx), Volatile Organic Compounds (VOCs), Geographic Information System (GIS).

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

IoT-Based Intelligent Trolley System enhances shopping by integrating IoT and embedded systems to automate product selection and billing. It eliminates long checkout lines by enabling real-time billing within the trolley. The system includes an Arduino Uno, Radio Frequency Identification based product scanning, and a display for product details. New customers enter their mobile numbers via a keypad to receive offers through Short Message Service, while regular customers use Radio Frequency Identification membership cards for personalized recommendations. Products are added or removed using Radio Frequency Identification taps. After shopping, the customer presses a finish button to trigger billing. The total bill is sent via Bluetooth to a thermal printer for receipt generation and via Wireless Fidelity through Node Mirco Controller Unit to the store owner's Personal Computer. A Quick Response code inside the store provides access to a website for browsing products, viewing discounts, and tracking expenses. This system improves efficiency, reduces manual errors, and enhances the shopping experience.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT, Radio Frequency Identification, Real-time Billing, Bluetooth, Wireless Fidelity, Automated Checkout.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sewage block detection and removal presents an automated system for detecting and removing sewage blockages using sensors and microcontroller-based control. Ultrasonic and water flow sensors monitor water levels and flow rates in real time. When abnormal readings indicate a blockage, a relay-controlled pump is activated to flush the system. The design aims to reduce manual intervention, improve sanitation, and prevent overflow in urban and residential settings. The system is cost-effective, scalable, and suitable for smart city applications.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT, Sewage management, Real-time monitoring, Automation, Blockage removal

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Low-Density Parity-Check (LDPC) codes are a key error correction technique in communication systems, ensuring reliable data transmission over noisy wireless channels. Traditional LDPC decoders, such as the Min-Sum algorithm, use fixed normalization (?) factors to approximate belief propagation. However, these fixed parameters do not adapt to varying channel conditions, leading to suboptimal performance in real-world scenarios. This project introduces a gradient descent-based approach to dynamically optimize ? based on estimated Signal-to-Noise Ratio and Rayleigh fading conditions. The system predicts the optimal values for ? in real time, improving decoding efficiency and error correction performance. These predicted parameters are then used in the Min-Sum decoding process, reducing the number of iterations required for convergence and minimizing the Bit Error Rate. The proposed approach enhances the adaptability of LDPC decoding, significantly improves error correction performance, reduces decoding time, and adapts effectively to varying channel conditions.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

LDPC codes, error correction, communication, Min-Sum algorithm, normalization factor, offset factor, belief propagation, Rayleigh fading, SNR, gradient descent optimization.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

One of the major causes of irreversible blindness is Glaucoma. It causes progressive damage to the optic nerve, often without noticeable symptoms in the early stages. Detection of this condition is vital for averting vision loss. Recent technological advancements in medical imaging technologies coupled with new and improved computational methods have enabled significant progress in glaucoma diagnosis. This literature review examines the evolution of automated glaucoma detection, with a focus on the role of image preprocessing, feature extraction, and the use of machine learning (ML) along with deep learning (DL) techniques. The review highlights essential preprocessing methods to enhance image quality, such as contrast enhancement and noise reduction, which are critical for accurate analysis of fundus and OCT images. Additionally, it explores various feature extraction approaches that bridge raw image data to meaningful clinical insights. This comprehensive review also provides an overall picture of different ML and DL models employed to detect glaucoma, evaluating their strengths, limitations, and performance metrics. Furthermore, it addresses the challenges faced in the field, such as dataset imbalance, the need for diverse and high-quality datasets, and the integration of these automated systems into clinical practice. The paper concludes by discussing future directions for research, including the potential of hybrid models, multimodal frameworks, and improved interpretability in advancing glaucoma detection and management.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Glaucoma, Retinal Imaging, Optical Coherence Tomography (OCT), Fundus Images.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper gives a real-time landslide detection and traffic automation system based on ADXL sensors, IR sensors, and rain sensors. The system gives real-time alerts using an LCD display and manages traffic by motorized gates. Road safety and accident avoidance are enhanced with wireless communication based on Zigbee and emergency notification based on GSM.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Landslide detection, traffic automation, ADXL sensor, IR sensor, rain sensor, ESP 32, Zigbee communication, GSM module, road safety, real-time monitoring.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The IoT-based Dam Automation System proposed combines microcontrollers, sensors, and image processing to improve the efficiency and safety of dam operation. With ESP32 microcontrollers, ultrasonic sensors, turbidity sensors, rain sensors, and a GSM module, the system tracks important parameters such as water levels, water quality, and structural condition. Camera-based image processing identifies cracks or damages in the dam structures and sends real-time notifications to concerned authorities. The system also has an automatic control mechanism that operates to manage the dam gates according to water levels in order to avert overflow and optimize water allocation. This solution minimizes dependency on manual adjustment, enhances preparedness for disaster, and presents a consistent, real-time alternative for more effective and safer operation of contemporary dam infrastructure.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Automation, Camera, ESP32, water level, monitoring, crack, dam.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cleaning staircases is tedious and labor-intensive. This work presents an autonomous staircase-cleaning robot. It efficiently traverses and cleans stairs using a NEMA17 stepper motor for climbing. Rear wheels are powered by DC motors, while a front-side DC motor enables rotation. The cleaning system includes spinning brushes, suction, and optional water sprays. 'Proximity' and 'edge' sensors ensure safe operation. A microcontroller-based system controls movement and scrubbing. This robot speeds up cleaning and reduces manual effort. It enhances cleanliness in various environments. Suitable for homes, offices, and public spaces. A smart, efficient cleaning solution

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autonomous, DC motors, edge sensors, intelligent cleaner, microcontroller, NEMA17 stepper motor, spinning brushes, staircase-cleaning robot, suction system, water sprays

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

An amphibious hovercraft is a highly adaptable vehicle capable of traversing both land and water by riding on a cushion of air produced by powerful fans. This unique mode of operation allows it to glide effortlessly over diverse surfaces such as water, mud, sand, and ice, making it particularly valuable in areas with difficult or unstable terrain. Its versatility makes it ideal for use in flood zones, wetlands, and remote regions where conventional vehicles often face limitations. The hovercraft's seamless transition between land and water also makes it an effective tool for rapid emergency response, including rescue operations and disaster relief efforts. Beyond emergency services, hovercrafts are utilized in military operations, passenger and cargo transport, and recreational activities. However, to achieve broader adoption, challenges such as high fuel consumption, noise levels, and complex maintenance requirements must be addressed. Modern designs now incorporate advanced features like GPS navigation, improved propulsion systems, and robust construction materials to boost performance, efficiency, and reliability.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skirt Design, Hybrid Propulsion, Durable Materials, Propulsion systems, sustainable technology

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Creative Commons Attribution 4.0 and The Open Definition