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UFCity: A Software Architecture to Create Data Ecosystem in Smart Cities

UFCity: A Software Architecture to Create Data Ecosystem in ...

引用

2023 Symposium on Internet of Things, SIoT 2023

作者： Pereira, Danne Brayner, Angelo Federal University of Ceara Doctoral Program in Computer Science Fortaleza Brazil Federal University of Ceara Dept. Computer Science Fortaleza Brazil

ISBN: (纸本)9798350329438

Smart city platforms manage resources and information to offer services to citizens. Developing technological solutions for this scenario is not trivial, given data and resource heterogeneity and the need for platform flexibility and adaptability. This work presents UFCity, a software architecture for smart city data ecosystems using microservices, artificial intelligence, and a three-layer networking structure. As a proof of concept, we developed a prototype and tested it in usage scenarios with real data. These use cases explored how our solution solves identified problems, showing meeting essential requirements for smart city platforms. In this way, UFCity is an alternative for data management in a smart city, presenting advantages over other solutions listed in this work in meeting the platform requirements. © 2023 IEEE.

关键词： Smart city

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The Use of Time and Frequency Features in Finger Movements Based on Electromyogram Recording

The Use of Time and Frequency Features in Finger Movements B...

引用

2022 International Conference for Advancement in Technology, ICONAT 2022

作者： Atmaji, Catur Lelono, Danang Harjoko, Agus Dharmawan, Andi Universitas Gadjah Mada Doctoral Program in Computer Science Yogyakarta Indonesia Universitas Gadjah Mada Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9781665425773

Human movement is a direct result of brain commands to muscles. The muscle activity can be analyzed with an electromyograph device and produce a recording in the form of an electromyogram or EMG signal. There are two recording methods, namely intramuscular EMG and surface EMG or sEMG which are easier and more convenient to implement but have lower resolution. Analysis of the EMG record data will be better if the right method is chosen, one of which is the selection of feature extraction methods. This study performs basic finger motion classification with a limited number of electrodes, namely 4 electrodes. The purpose of this research is to compare the variation of features in the time or frequency domain that will be used for classification using artificial neural networks (ANN) and long short-term memory (LSTM). Data acquisition was carried out with the Ganglion Board device on 6 subjects aged 20-22 years who conducted experiments with two kinds of movements, namely opening and holding all fingers alternately. The results of this study indicate that the use of time domain features for classification with ANN produces better accuracy than LSTM. This can happen because the duration of the movement in this study is quite short, which is only for two seconds. The results of the use of the frequency domain feature show that the use of LSTM produces better accuracy, especially on the mean power and median frequency characteristics. © 2022 IEEE.

关键词： Frequency domain analysis

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A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization 7

A Study on Text Feature Selection Using Ant Colony and Grey ...

引用

7th International Conference on Informatics and Computing, ICIC 2022

作者： Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri Universitas Gadjah Mada Doctoral Program Dept. of Computer Science and Electronics Indonesia Universitas Mulawarman Faculty of Engineering Dept. of Informatics Samarinda Indonesia Universitas Gadjah Mada Faculty of Mathematics and Natural Sciences Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous characteristics and high-element dimensions. Many pattern classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The Ant Colony Optimization (ACO) and Grey Wolf Optimizer (GWO) for FS are the main topics of our thorough assessment of the literature on the Swarm Intelligence (SI) algorithm. Furthermore, it illustrates how the hybrid SI technique is used in FS across various sectors. The hybrid SI technique uses applicable data from various FS methods to find feature subsets with smaller sizes and better classification performance than those found by regular FS algorithms. © 2022 IEEE.

关键词： Ant colony optimization

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Integrating Noise Classification and Speech Enhancement Model for Hearing Aids 21

Integrating Noise Classification and Speech Enhancement Mode...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Hung, Ying-Hsiu Chang, Yen-Ching Lai, Shin-Chi Juang, Wen-Ho Sheu, Ming-Hwa Lee, Jeng-Dao National Yunlin University of Science and Technology Dept. Electronics Engineering Douliu Taiwan National Formosa University Doctoral Degree Program in Smart Industry Technology Research and Development Huwei Taiwan National Formosa University Dept. Automation Engineering Smart Machinery and Intelligent Manufacturing Research Center Huwei Taiwan National Formosa University Dept. Computer Science and Information Engineering Huwei Taiwan National Formosa University Dept. Automation Engineering Huwei Taiwan

ISBN: (纸本)9798350377088

As the global population ages, the number of elderly people needing hearing aids is increasing. This paper proposed an architecture designed to enhance speech based on noise conditions. After noise types are identified by a Convolutional Neural Network (CNN) noise classification model, these noise conditions are combined with the noisy speech and input into a conditional Generative Adversarial Network (cGAN) for speech enhancement. The CNN noise classification model achieves an average recognition accuracy of nearly 92%, with a Kappa value as high as 0.88. The cGAN speech enhancement achieves lower error values in the Mel-Cepstral Distortion (MCD) measure. Although some parts of the human voice may be filtered out, the results demonstrate the potential development of the proposed algorithm. © 2024 IEEE.

关键词： Generative adversarial networks

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Design of a Multilingual Translation System with Personalized Voice Characteristics 21

Design of a Multilingual Translation System with Personalize...

引用

21st International System-on-Chip Design Conference, ISOCC 2024

作者： Chen, Chen-Hua Lai, Guan-Yu Lee, Chuan Wu, Chang-Yu Liu, Kuan-Lin Lai, Shin-Chi Doctoral Degree Program in Smart Industry Technology Research and Development Huwei Taiwan National Formosa University Dept. of Automation Engineering Huwei Taiwan National Yunlin University of Science and Technology Dept. Electronics Engineering Douliu Taiwan National Formosa University Dept. Automation Engineering Smart Machinery and Intelligent Manufacturing Research Center Huwei Taiwan

ISBN: (纸本)9798350377088

This study combines AI voice synthesis with IoT to create a real-time multilingual translation system. Front-end devices capture the speaker's voice, which is then played back in both original and translated forms, enabling consecutive interpreting. This system is ideal for multilingual scenarios. After digitization, audio signals undergo speech-to-text conversion, multilingual translation, and text-to-speech processing. Speech synthesis matches the speaker's voice characteristics, allowing listeners to hear the translation in the speaker's voice. Both voice-to-text conversion and translated audio playback use Wi-Fi for data transmission, facilitating future applications. In validation, the average translation and transmission time for each speech segment were 410 ms and 3.38 s, respectively. The synthesized voice similarity analysis achieved an accuracy of 88%, showcasing the method's potential for system integration and development. © 2024 IEEE.

关键词： Wi-Fi

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UFCity: A Software Architecture to Create Data Ecosystem in Smart Cities

UFCity: A Software Architecture to Create Data Ecosystem in ...

引用

International Workshop on Secure Internet of Things (SIoT)

作者： Danne Pereira Angelo Brayner Doctoral program in computer science Federal University of Ceara Fortaleza Brazil Dept. computer science Federal University of Ceara Fortaleza Brazil

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Practical Implementation of Q-Learning and Object Detection for Mobile Robot Path Planning

Practical Implementation of Q-Learning and Object Detection ...

引用

2024 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2024

作者： Valcourt, John P. Chandler, Franya M. Avrelus, Chamma Lee, Jou-Yi Güllü, Ali Ihsan Shah, Syed H. Yuan Ze University Dept. of Computer Science and Engineering Taoyuan Taiwan Yuan Ze University International Bachelor Program in Ece Taoyuan Taiwan Yuan Ze University Mechanicai/Industrial Engineering Taoyuan Taiwan Yuan Ze University International Bachelor Program in Engineering Taoyuan Taiwan Gebze Technical University Defense Electronics Engineering Kocaeli Turkey

ISBN: (纸本)9798350362572

Expanding on an earlier study that assessed the performance of a Q-learning approach for solving the path planning problem for mobile robots, this research implemented the RL approach in a real-world setting employing the RoboMas-ter EP Core. The robotic system also included object detection and recognition through the robot's sensors and a pre-trained YOLOv9 model. The robot navigated to predefined target points while avoiding stationary obstacles. The Q-learning algorithm was trained using the Google Colaboratory platform. Experi-ments conducted at various speeds identified an optimal speed and high success rates in obstacle avoidance and target region accuracy were achieved. Additionally, the object detection sys-tem demonstrated strong performance in real-time applications. Despite these successes, challenges such as high friction and multitasking inefficiencies were identified. Future research should address these limitations by enhancing control systems and the robot's multitasking capabilities, as well as using a computer with better processing power to improve overall system performance further. © 2024 IEEE.

关键词： Robot programming

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A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization

A Study on Text Feature Selection Using Ant Colony and Grey ...

引用

International Conference on Informatics and Computing (ICIC)

作者： Joan Angelina Widians Retantyo Wardoyo Sri Hartati Doctoral Program dept. of Computer Science and Electronics Universitas Gadjah Mada Dept. of Informatics Faculty of Engineering Universitas Mulawarman Samarinda Indonesia Dept. of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9798350345728

关键词： Ant colony optimization Text categorization Pattern classification Filtering algorithms Feature extraction Classification algorithms Particle swarm optimization

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Borneo Smart Forest Information System for Management of Dipterocarp Plants in Kalimantan Rainforest

Borneo Smart Forest Information System for Management of Dip...

引用

Information Technology International Seminar (ITIS)

作者： Masna Wati Novianti Puspitasari Ummul Hairah Joan Angelina Widians Anindita Septiarini Ade Fiqri Tjikoa Dept. of Informatics Faculty of Engineering Universitas Mulawarman Samarinda Indonesia Dept. of Informatics Universitas Mulawarman Doctoral Program Dept. of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9798350398205

Kalimantan’s tropical rainforest is home to indigenous plants of the Dipterocarpaceae family (tribe), which is renowned for having the most endemic species. Dipterocarp is a family of pantropical plants, many of which are used in the wood industry. This study aims to provide information on the potential of Dipterocarp in Kalimantan forests. Education and conservation efforts for Dipterocarp trees, a prominent component of the forest ecosystem, are crucial in light of the significant harm done to Kalimantan’s rainforests. The authors develop the Borneo Smart Forest information system. This system digitally organizes data on the diversity of Dipterocarp in the Kalimantan rainforest based on Web and QR-Code technology. Borneo Smart Forest (BSF) system for monitoring plant inventory and plant markers can be read by smartphones using QR codes. It gives visitors a comprehensive overview of the plants. A QR code is a printed, two-dimensional barcode with limited space for data storage. This technology allows the plant to show earlier administrator-made additions to the inventory information system. The QR code will direct the user to the BSF website, which has data about the plants. The development of this system is one of the efforts to support the achievement of Dipterocarp conservation.

关键词： Seminars Memory Forestry QR codes Vegetation Wood industry Information technology

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Integrating Noise Classification and Speech Enhancement Model for Hearing Aids

Integrating Noise Classification and Speech Enhancement Mode...

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International SoC Design Conference, ISOCC

作者： Ying-Hsiu Hung Yen-Ching Chang Shin-Chi Lai Wen-Ho Juang Ming-Hwa Sheu Jeng-Dao Lee Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan Dept. Computer Science and Information Engineering National Formosa University Huwei Taiwan Dept. Automation Engineering National Formosa University Huwei Taiwan

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

关键词： Accuracy Noise Noise reduction Speech recognition Speech enhancement Hearing aids Classification algorithms Convolutional neural networks Human voice Older adults

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