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International Islamic University Chittagong

 

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Recent Submissions

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Design and Analysis of a Metamaterial Absorber for Applicaion at 3.5GHz
(International Islamic University Chittagong, 2024-06) Hossain, Syed Mustavi
Analysis of a metamaterial absorber with an S-shaped structure is suggested to reduce the specific absorption rate (SAR) at 3.5 GHz. This absorber exhibits single negative metamaterial characteristics and achieves an absorption rate of over 90% for all electromagnetic polarization angles. In the age of 5G, numerous applications are functioning at various frequency ranges, emitting substantial amounts of electromagnetic energy (EM) that possess an elevated SAR value. This radiation has an impact on the human body, specif ically the head and hands, which are exposed to it. In Malaysia, a frequency band of 3.5 GHz has been designated for 5G communication. However, this has resulted in the emission of undesirable signals due to high Specific Absorption Rate (SAR) values. To address this issue, a proposed absorber would be implemented to reduce SAR levels.
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IoT Based Smart Irrigation System
(International Islamic University Chittagong, 2024-06) Islam, Md Zahidul
The challenges of water management, temperature and humidity control, and soil moisture management in indoor agricultural settings are addressed by the IoT-based smart water management system for indoor agriculture presented in this project thesis. The project's main goal is to develop a reasonably priced and effective system that makes use of Internet of Things technologies to allow real-time monitoring and control of water parameters essential to healthy plant growth. The project starts with a thorough analysis of the body of research on agriculture, smart water management, and the Internet of Things. The basis for selecting appropriate sensors, controllers, and communication protocols for system integration is provided by this research. The suggested system makes use of Internet of Things capabilities to provide precise and timely data on soil temperature and moisture levels, doing away with the need for manual data collection and analysis. Sensors, microcontrollers, and communication modules are all integrated into the system design and are managed by a cloud-based data management platform. In order to provide farmers with remote control over the system and real-time data access, an intuitive user interface has also been developed
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Optimizing Water Management: An IoT-Driven Approach to Smart Irrigation
(International Islamic University Chittagong, 2024-06) Bin Nazir, Md Motasim
The challenges of water management, temperature and humidity control, and soil moisture management in indoor agricultural settings are addressed by the IoT-based smart water management system for indoor agriculture presented in this project thesis. The project's main goal is to develop a reasonably priced and effective system that makes use of Internet of Things technologies to allow real-time monitoring and control of water parameters essential to healthy plant growth. The project starts with a thorough analysis of the body of research on agriculture, smart water management, and the Internet of Things. The basis for selecting appropriate sensors, controllers, and communication protocols for system integration is provided by this research. The suggested system makes use of Internet of Things capabilities to provide precise and timely data on soil temperature and moisture levels, doing away with the need for manual data collection and analysis. Sensors, microcontrollers, and communication modules are all integrated into the system design and are managed by a cloud-based data management platform. In order to provide farmers with remote control over the system and real-time data access, an intuitive user interface has also been developed.
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Unsafe Driving Behavior Detection By Using CNN Deep Learning Method.
(International Islamic University Chittagong, 2024-06) Adnan, Shihab
The complex nature of human behaviour and the numerous factors contributing to distractions on the road, particularly in terms of the limited ability to provide precise and timely early warnings, are addressed in this paper through the introduction of a novel method. The proposed method aims to enhance the detection of distracted driver behaviour using modified CNN transfer learning. By employing transfer learning within the Convolutional Neural Networks framework, the method seeks to tackle the intricate challenges associated with identifying distracted driving behaviours. The experimental results demonstrate an overall accuracy of approximately 99%, with the highest achieved accuracy reaching 99.46% on a publicly available dataset. This highlights the effectiveness of the proposed approach in significantly improving the precision of distracted driver behaviour detection.
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A Transfer Learning Approach with Modified VGG16 for Driving Behavior Detection in Intelligent Transportation Systems
(International Islamic University Chittagong, 2024-06) Nur, Abdullah Hafez
The complex nature of human behaviour and the numerous factors contributing to distractions on the road, particularly in terms of the limited ability to provide precise and timely early warnings, are addressed in this paper through the introduction of a novel method. The proposed method aims to enhance the detection of distracted driver behaviour using modified CNN transfer learning. By employing transfer learning within the Convolutional Neural Networks framework, the method seeks to tackle the intricate challenges associated with identifying distracted driving behaviours. The experimental results demonstrate an overall accuracy of approximately 99%, with the highest achieved accuracy reaching 99.46% on a publicly available dataset. This highlights the effectiveness of the proposed approach in significantly improving the precision of distracted driver behaviour detection