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An IoT-Based Sustainable Automation System for the Garments Industry in Bangladesh 3

An IoT-Based Sustainable Automation System for the Garments ...

引用

3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies, ICEFEET 2023

作者： Ahmed, Khandakar Rabbi Salam, Towfika Rabbu, Mohammad Mahmudul Haque, F.M. Hasan, Nazmul Miraz, Shafiun Rana, Md. Masud Mansur, Maliha Tabassum, Humayra Shayer, Khandokar Shadman Miyan Research Institute International University of Business Agriculture and Technology Dhaka Bangladesh Dept. of Mechatronics Engineering Rajshahi6204 Bangladesh International University of Business Agriculture and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Computer Science & Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Varendra University Dept. of Computer Science and Engineering Rajshahi Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Ahsanullah University of Science & Technology-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350307399

The Readymade Garments sector accelerates Bangladesh's development. The 'Made in Bangladesh' brand has also helped to boost Bangladesh's reputation and brand recognition on a global scale. Despite its limited resources, the country has maintained a 6% annual GDP growth rate while attaining extraordinary social and human development. On the other hand, the phrase 'Internet of Things' (IoT) refers to a broad concept that can be summarized as an ecosystem of intelligent gadgets equipped with networks, sensors, and processing tools. IoT is a new technological platform that enables the many objects in our environment to connect via sensors and the Internet to improve our quality of life. Manufacturing and the industrial sector, agriculture, the health sector, smart cities, security, and emergency services, to name a few. IoT implementation in the garment sector would open a new door to growth in production and worker safety. Implementing home automation and safety systems in the garment sector will help in production and ensure the safety of the workers. The suggested IoT -based sustainable automation system for the Bangladeshi garments sector is efficient, eco-friendly, secure, reliable, and user-friendly. The system's user-friendly interface makes it straightforward to use and manage. The Bangladeshi garments industry's IoT -based sustainable automation system is a comprehensive and integrated solution that addresses the industry's primary difficulties and provides a sustainable and viable future. © 2023 IEEE.

关键词： Internet of things

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A Hybrid Machine Learning and Deep Learning Approach for Diabetes Prediction with a Tkinter-Based User Interface

A Hybrid Machine Learning and Deep Learning Approach for Dia...

引用

2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology, IC-SIT 2024

作者： Kasetty, Sai Bhargav Margret, Issac Neha Madhuri, K. Sai Ojha, Rajesh Kumar Sudha, Nuthalapati Rajakumar, K. V.I.T University SCOPE Tamilnadu Vellore India Data Science BVRIT Narsapur Dept. of CSE Telangana Hyderabad India Silicon University Dept. of Computer Science & Engineering Odisha Bhubaneswar India Mahindra University School of Engineering Telangana Hyderabad India

ISBN: (纸本)9798350369175

Diabetes prediction is a critical task in healthcare that can significantly benefit from advancements in machine learning and deep learning technologies. This paper presents a hybrid approach combining deep learning and traditional machine learning models for diabetes prediction. The proposed system integrates a Tkinter-based Graphical User Interface (GUI) to make it easier for users to interact and make predictions. In our discussion, we will cover the design and implementation of the system, and evaluate the performance of different models using precision, F1 score, recall, and, accuracy to provide insights into their effectiveness. Results demonstrate the efficacy of the hybrid approach, with a focus on model accuracy and user experience. © 2024 IEEE.

关键词： Prediction models

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A Comprehensive Review for Optimizing the Design of Cluster Head Selection to Enhance the Network Lifetime in WSN

A Comprehensive Review for Optimizing the Design of Cluster ...

引用

2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development, OTCON 2022

作者： Bhuvaneswari, S. Abirami, A. Suvetha Sri, R.P. Srinithy, R. Swathi, R. Easwari Engineering College Faculty of Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665492942

Large numbers of cooperative sensor nodes make up wireless sensor networks (WSNs). Sensors are the integral component in WSN IoT. Sensors separate and organize in the clusters by similar characteristics. A cluster head is in charge of gathering information from the nodes in every cluster and transmitting it to its base station (BS). Because every node are powered by batteries, lessens energy usage and elongating lifetime of network are crucial concerns for WSN. The primary goals of this analysis are to address issues that previous writers have not addressed and to provide beginning researchers with a fundamental understanding of how to choose cluster head (CH) based on various methodologies. To designate a node as CH, some enhancing parameters are chosen, such as residual energy, packet transmission rate, throughput, distance between BS and Cluster Node (CN), and betweenness centrality. data packets are transferred using the optimized protocol to reduce delay time and increase transmission rate after many CH are chosen. Analysis of the many literatures was done. An Optimization Algorithm is needed to enhance network lifetime from this analysis. A comparison of various algorithm based on the features and difficulties from the analysis is done. There are many drawbacks, such as a cluster head is chosen at random, data transmission rate is not considered, no proper formation of clusters, importance for load and temperature is not given, stability is not taken into account. Thus, there is a need for optimized algorithm to overcome all the mentioned issues. © 2023 IEEE.

关键词： Packet networks

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Early Brain Tumour Detection in MRI Images Through Hybrid Deep Learning Model 3

Early Brain Tumour Detection in MRI Images Through Hybrid De...

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3rd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2025

作者： Parida, Samrat Aditya Keshari Ashirbad, S.B. Maharana, Mangal Ghadai, Debasis Kumar De, Sumane C.V Raman Global University Dept. of Computer Science & Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798331533205

Brain tumours are among the emerging significant health challenges that require early detection for complete management. Though the mainstay of diagnosis remains MRI, it can be applied in its interpretation with some challenges. This study investigates the potential of leveraging Convolutional Neural Networks, a form of artificial intelligence, to classify different brain tumours from MRI images with enhanced metrics. CNNs are said to provide the best currently available solution in achieving minimal preprocessing followed by feature engineering especially with respect to image analysis. Accuracy and efficiency in brain tumour diagnosis can be drastically improved by leveraging the power of AI. © 2025 IEEE.

关键词： Convolutional neural networks

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Empowering Android Malware Detection: A Deep Learning Ensemble with Optimal Features 26

Empowering Android Malware Detection: A Deep Learning Ensemb...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Shakil, Mehedi Hasan Hasan, Md. Mynul Chittagong University of Engineering & Technology Dept. of Computer Science and Engineering Chattagram Bangladesh

ISBN: (纸本)9798350359015

Because of the rapid expansion of mobile devices and the growing reliance on mobile applications, there has been an increase in Android malware threats, necessitating the development of sophisticated detection systems. This research proposes a technique for detecting Android malware that makes use of several deep learning models. The goal is to provide an accurate and dependable method for classifying mobile applications as malicious or benign. To assure data integrity, the Drebin dataset is preprocessed. RFECV was employed to obtain the optimal features for deep learning algorithms such as Bi-LSTM, Bi-GRU, and 1D CNN. The dataset was trained using the selected features for each deep learning algorithm based on the feature selection method. The ensemble technique, employing a weighted average method, was utilised to combine the predictions of the individual models. Extensive testing revealed that combining Bi-LSTM and CNN in the ensemble technique achieves the greatest accuracy of 98.99%. This combination highlights the efficiency of combining various models strengths for Android malware detection. © 2023 IEEE.

关键词： Bi-Directional Gated Recurrent Unit (Bi-GRU) Bi-Directional Long Short Term Memory (Bi-LSTM) Convolutional Neural Network (CNN) Recursive Feature Elimination with Cross-Validation (RFECV) weighted average ensemble

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Recent Advancements and Challenges in Bangla Textual Document Classification: A Review 26

Recent Advancements and Challenges in Bangla Textual Documen...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Nahar, Khairun Al Mahfuz, Mohammed Abdullah Haque Sweety, Mahmuda Comilla University Faculty of Engineering Dept. of Computer Science and Engineering Cumilla Bangladesh

ISBN: (纸本)9798350359015

Bengali is the world's sixth-most frequently used dialect. Natural language processing (NLP), which enables data scientists to extract useful information from the constantly growing quantity of text data available on the net, includes text categorization as a key component. It is the act of organizing already-created groups or classes of text documents. But compared to other languages, like English, Bengali does not have as many capabilities for classifying texts. This study offers an extensive analysis of the current categorization of Bengali documents. Also gives a comprehensive summary of recent advances in ML and DL, covering datasets, methods, performance, accuracy rate, classification category, strengths, and limits. The purpose of this discussion is to identify current challenges that must be addressed and recommend some guidelines for future studies that might be explored. © 2023 IEEE.

关键词： Bangla Language Bengali text classification Classification Document classification Natural Language processing Text categorization

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Analysis of Time-Lapse Camera Using IoT

Analysis of Time-Lapse Camera Using IoT

引用

2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Manjunatha Swamy, C. Sundaram, S. Meenakshi Pranati, N. Karthik, R. Srivatsan, R. New Horizon College of Engineering Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350333244

Time-lapse photography is a widely used technique in various applications, such as film and video production, construction, and scientific research. However, traditional methods for creating time-lapse photography are limited and often require manual intervention, which can be time-consuming and error-prone. Additionally, current systems are not easily portable, and it's difficult to access the footage remotely. In this paper, we propose an IoT-enabled time-lapse camera that addresses these limitations by providing a solution that is easy to use, can be deployed in a variety of locations, and provides remote access to the footage. The camera is designed to capture high-quality images at set intervals and store them on a cloud platform for easy access. A desktop application is also developed to allow the user to remotely control and monitor the camera, set the camera's settings, and view the footage. Experiments were conducted to evaluate the performance of the proposed system. The results show that the proposed system significantly improves the efficiency of time-lapse photography and makes it more accessible to a wider range of users. The system is easy to use, has a low power consumption, and is highly scalable, making it suitable for various applications. The proposed IoT-enabled time-lapse camera provides a practical solution for creating time-lapse photography and has the potential to significantly impact the way time-lapse photography is done. © 2023 IEEE.

关键词： Remote control

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A Technique to Avoid Blockchain Denial of Service (BDoS) and Selfish Mining Attack 5

A Technique to Avoid Blockchain Denial of Service (BDoS) and...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Habib, Md. Ahsan Hossen Manik, Md. Motaleb Khulna University of Engineering & Technology Dept. of Computer Science and Engineering Khulna Bangladesh

ISBN: (纸本)9798350339239

Blockchain denial of service (BDoS) and selfish mining are the two most crucial attacks on blockchain technology. A classical DoS attack targets the computer network to limit, restrict, or stop accessing the system of authorized users which is ineffective against renowned cryptocurrencies like Bitcoin, Ethereum, etc. Unlike the conventional DoS, the BDoS affects the system's mechanism design to manipulate the incentive structure to discourage honest miners to participate in the mining process. In contrast, in a selfish mining attack, the adversary miner keeps its discovered block private to fork the chain intentionally that aiming to increase the incentive of the adversary miner. This paper proposed a technique to successfully avoid BDoS and selfish mining attacks. The existing infrastructure of blockchain technology does not need to be changed a lot to incorporate the proposed solution. © 2023 IEEE.

关键词： Machine design

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Prakruthi Sedhya: A Natural Farming Mobile App

Prakruthi Sedhya: A Natural Farming Mobile App

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2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent engineering, ICECONF 2023

作者： Sambrajyam, J. Tejaswini Rao, J. Ranga Reddy, E. Eswar Chowdary, K. Yashwanth V R Siddhartha Engineering College Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350334357

Andhra Pradesh Community Natural Farming (APCNF) is an organization that promotes natural farming. Their farming techniques are low-cost and eco-friendly and include the use of local resources. Natural farming has the ability to achieve the twin objectives of ensuring global food security and environmental preservation because it does not rely on agrochemicals. The Andhra Pradesh government has initiated Rythu Sadhikara Samstha (RySS), which occasionally conducts village-level training on natural farming techniques through SHG and RySS groups. But, it is still unknown to many people and has no support to assist them. We have designed this Prakruthi Sedhya application, a complete Natural Farming Mobile app. Our motto is to help people by assisting them in farming and creating a network among them. This app provides details about cultivating different crops, using natural farming techniques, and crop care information, including preparing natural fertilizers and using them at appropriate times. Furthermore, it indicates the weather forecast in each region. It also includes details about government schemes and minimum support prices(MSP) of all crops, fixed by the central government of India. This application connects farmers and buyers so that farmers can sell their yield directly to customers. Building a network among farmers through discussion forums can also be met. This app was created using real data that was gathered from APCNF specialists, agriculture officers, and active farmers. It is a complete Telugu language-based app and anyone can use this app because it is made to be user-friendly. © 2023 IEEE.

关键词： Crops

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Oral Cancer Detection using Deep Learning Techniques

Oral Cancer Detection using Deep Learning Techniques

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2023 IEEE International Conference on Innovative data Communication Technologies and Application, ICIDCA 2023

作者： Tenali, Nagamani Desu, Vasavi Sripriya Boppa, Charishma Chowdary Chintala, Varshith Guntupalli, Bhavana Sr Gudlavalleru Engineering College Dept. of Computer Science and Engineering Gudlavalleru India

ISBN: (纸本)9798350397208

One of the most serious tumors that affects the oral cavity is oral cancer. Smoking cigarettes and increased tobacco use are the main risk factors for mouth cancer. When oral cancer is found in its early stages and treated successfully, many lives can be saved Histological analysis of an oral cavity tissue sample is the accepted method in medicine for identifying oral cancer. This method requires more time and is more invasive than obtaining a brush sample and then performing a cytological analysis. For a better prognosis, treatment plan, and chance of survival, early diagnosis is essential. Therefore, this paper suggests deep learning techniques to perform early detection of oral cancer and eventually leads to its prevention. Deep learning techniques enable early detection of disease to provide precision medicine. According to the recent research reports, this method has significantly advanced the extraction of data and interpretation of crucial information related to medical imaging. It has the potential to identify oral cancer with a cost-efficient, non-invasive, and effective method, having substantial clinical implications. © 2023 IEEE.

关键词： Tobacco

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