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A Fairness-aware Coverage Algorithm for Drone Swarms 7

A Fairness-aware Coverage Algorithm for Drone Swarms

7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Bezas, Konstantinos Tsoumanis, Georgios Koritsoglou, Kyriakos Oikonomou, Konstantinos Tzallas, Alexandros T. Giannakeas, Nikolaos Tsipouras, Markos Angelis, Constantinos T. Department of Informatics and Telecommunications University of Ioannina Campus of Arta Greece Department of Informatics Ionian University Corfu Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Drones have evolved over the past years to a level that they have become more efficient and, at the same time, have miniature sizes and advanced environment sensing capabilities. As a result, drone swarms are being applied in various applications nowadays, as they can sense and process information from the surrounding environment to achieve higher level of functionality. For example, drone swarms are employed in disaster control and large area monitoring to prevent catastrophic events such as wild fires. For drone swarms to operate properly, a critical aspect is their remote command and control capabilities. Since swarms can possibly consist of an increased number of drones, it is important that they hold a certain degree of autonomy. In the current work, a Coverage Path Planning (CPP) algorithm is proposed for unknown area exploration. The proposed algorithm discovers the Wireless Sensor Network (WSN) nodes within the area and, then, it collects their data under a data collection scheme being used. For evaluating the proposed algorithm, a simulated environment is developed to assess its effectiveness in terms of fairness in data collection from the WSN nodes. Fairness, in the current case, measures the percentage of data collected from the WSN nodes and is calculated multiple times during the experiments. Two coverage paths are considered here, the parallel lines and the spiral lines. The results showcase that the coverage path affects the fairness index while the parallel lines seem to provide more consistent data collection than the spiral, the latter increasing the fairness index. © 2022 IEEE.

关键词： Drones

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(POSTER) A Holistic IoT-Enabled Approach for Indoor Air Quality Control

(POSTER) A Holistic IoT-Enabled Approach for Indoor Air Qual...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Fotios Kalioras Gabriel Filios Stylianos Karatzas Sotiris Nikoletseas Department of Computer Engineering and Informatics University of Patras Greece Department of Computer Engineering and Informatics University of Patras Computer Technology Institute and Press “Diophantus” Greece Department of Civil Engineering University of Patras Greece

Indoor air quality (IAQ) is an important yet often overlooked aspect of public health, with poor IAQ contributing to a significant number of diverse health problems worldwide. Existing air quality standards have failed to fully address the problem, however emerging technologies in the field of IoT have demonstrated promise in effectively addressing this issue. This concept paper advocates a hybrid hierarchy system for IAQ monitoring that incorporates both offline and online connectivity. The system utilizes sensing elements that can perform a wide range of functions, including autocalibration, pollution event detection, and more, autonomously from the network. By combining a gateway device, the system's capabilities are enhanced, providing increased data granularity, additional calibration and sensing options as well as connection with Building Management Systems (BMS). Furthermore, by connecting the gateway to the cloud, the system can perform more advanced data analysis and machine learning, providing users with insights into not only air quality but also general environmental quality. Key features of the envisioned system include the integration of subjective perception of pollution via crowdsourcing, a TinyML technology at the edge, digital twins, and an optimised redundancy of sensors that can alleviate poor accuracy and drift as well as capture the spatial dispersion of pollution.

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Knowledge Management Trends for Measuring Academic Performance: A New Conceptual Framework 4

Knowledge Management Trends for Measuring Academic Performan...

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4th International Conference on Electrical engineering and informatics, ICon EEI 2024

作者： Yanti, Novi Defit, Sarjon Okfalisa Universitas Islam Negeri Sultan Syarif Kasim Riau Faculty of Science and Technology Department of Informatics Engineering Pekanbaru Indonesia Universitas Putra Indonesia Yptk Padang Faculty of Computer Science Department of Information Technology Padang Indonesia

ISBN: (纸本)9798331540791

Research in the area of knowledge management for improving academic performance has been on the rise in recent years. The effectiveness of knowledge management in improving the quality of decision-making in higher education is a new challenge in the drive for university performance improvement. Therefore, this paper tries to propose one conceptual framework used to measure academic performance in universities. By applying knowledge management process integrated with Business Intelligence System with data-driven analysis concept. This can provide new insights into the theme of academic knowledge management processes for future research opportunities. The model developed is based on comprehensive research developments on research trends and mapping of knowledge management articles and academic performance as well as a systematic literature review. This literature review examines the current state, clusters, and main topics of research related to knowledge management based on authors, sources, cited articles, countries of article authors, and journals that are productive in producing articles. Herein, 429 articles are utilized as metadata taken from the Scopus database published in 2018-2024. Hence, the data analysis of scientific articles is then reviewed using a bibliometric approach and article mapping with using tool VOSviewers to get a network visualization image. The findings of bibliometric analysis point to a rise in publications and a strong level of interest among academics in the field of knowledge management for performance evaluation in higher education institutions. © 2024 IEEE.

关键词： Research and development management

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Real-Time Safety Helmet Detection in Construction Site Using Deep Learning

Real-Time Safety Helmet Detection in Construction Site Using...

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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Arna Fariza Tita Karlita Muhammad Iqbal Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

Construction is a high-risk industry where workers are frequently exposed to potential injuries, particularly head injuries. Safety helmets serve as a critical defense, yet many workers neglect their use due to low safety awareness, increasing their vulnerability. This study proposes a real-time safety helmet detection system using an edge computing device, the NVIDIA Jetson Nano, to enable immediate data processing. The system employs YOLOv5 object detection models to classify individuals as wearing or not wearing safety helmets. A comparative evaluation between YOLOv5-small and YOLOv5-nano models was conducted, demonstrating that YOLOv5-nano outperforms YOLOv5-small in terms of real-case video analysis and testing dataset performance. This approach highlights the potential of lightweight deep-learning models for enhancing safety compliance in construction environments.

关键词： YOLO Deep learning Computational modeling Streaming media Helmets Real-time systems Safety Injuries Edge computing Testing

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Enhancing Cryptocurrency Value Prediction: A Comparative Study of Novel Random Forest and K-Nearest Neighbor Algorithms for Improved Accuracy 5

Enhancing Cryptocurrency Value Prediction: A Comparative Stu...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Kiruthiga, S. Balamanigandan, R. Mahaveerakannan, R. Jenifer, A. Mary Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science Engineering Tamil Nadu Chennai602105 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Saveetha University Department of Spatial Informatics Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350379945

The effectiveness of the Novel Random Forest (RF) Algorithm for predicting cryptocurrency prices was evaluated and compared to the K-Nearest Neighbor (KNN) Algorithm. Machine learning methods were used to develop the two algorithms, and a pretest power analysis was conducted using two groups with the iteration of 10 at 85% of G-power and the setup parameters are alpha = 0.05 and beta = 0.85. Hence the P value is less than 0.005 (P © 2024 IEEE.

关键词： k-nearest neighbors

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Precise Long Passing Skill on Middle Size League Robot Soccer ERSOW Using Teammate Detection and Pivot Motion

Precise Long Passing Skill on Middle Size League Robot Socce...

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International Electronics Symposium (IES)

作者： Rohman Aditiya Mochamad Mobed Bachtiar Iwan Kurnianto Wibowo Dana Yoga Setya Ikhwandi Febrian Tirto Wicaksono Septian Bagus Jumantoro Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798350391992

ISBN: (纸本)9798350392005

The ERSOW robot, a competitor in robot soccer leagues, struggles with its current long-distance passing technique. This method, reliant on robot localization to feed robot orientation adjustments, suffers from accumulating odometry errors and unintended deviations in the ball's trajectory. This research proposes a novel approach to optimize the ERSOW robot's long-distance passing skills, addressing these limitations. The proposed solution incorporates two key elements: ball pivoting movements and a vision system. Ball pivoting maneuvers enable the robot to maintain control of the ball's position during orientation adjustments, minimizing deviations caused by robot movement. Additionally, the integration of a vision system allows the robot to continuously track the receiving teammate's location in real-time. This real-time information enables adjustments to the passing trajectory, mitigating the negative effects of odometry errors. The effectiveness of the proposed approach was evaluated through experimentation. The results demonstrate a success rate of 100% for kickoff passes with an average completion time of 1.21 seconds at a distance of 400 cm and 95.83% for corner passes with an average completion time of 2.44 seconds at a distance of 600 cm. This suggests that 600 cm is the optimal passing distance for achieving successful long passes.

关键词： Tracking Machine vision Real-time systems Robot localization Trajectory Odometry Collision avoidance

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Integrating Stereotype User Models for Adaptive Scenarios in Game Playing within Immersive Virtual Environments

Integrating Stereotype User Models for Adaptive Scenarios in...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Panagiotis Strousopoulos Christos Troussas Akrivi Krouska Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica

Stereotypes constitute a widely used technique for creating user models. This paper explores the potential of stereotype-based models in virtual environments in order to enhance user engagement and learning outcomes. The focus is on an application, named Beekeeper World, which employs adaptive scenarios that respond to user actions. These scenarios, referred to as stereotype user models, represent predefined behavior patterns that Beekeeper World uses to respond to specific user actions. In the game context, these stereotypes are triggered by particular player interactions involving the ecological dynamics of bees and spiders. The first one challenges the player when s/he fails to protect a bee by strengthening the enemy spider. The second stereotype is a way of helping the player by pausing the spiders' spawning when s/he cannot defend the bees. These stereotypes can be instrumental in creating predictable, consistent behavior in Beekeeper World. They provide a framework for the system to respond to various user inputs in a consistent manner. This consistency can be crucial in maintaining the desired user engagement, as it ensures that the system's responses align with the user's expectations based on their previous interactions. Furthermore, these stereotypes can contribute to the complexity and challenge of the game, as they require the player to understand and adapt to these patterns in order to succeed, thereby promoting strategic thinking and problem-solving skills.

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Towards an Effective Tool Wear Monitoring System with an AI Model Management Platform 22

Towards an Effective Tool Wear Monitoring System with an AI ...

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22nd IEEE International Conference on Industrial informatics, INDIN 2024

作者： Chen, Jian Wen Tsai, Meng Shiun Hung, Che Lun Department of Computer Science National Tsing Hua University Hsinchu Taiwan Department of Mechanical Engineering National Taiwan University Taipei Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan

ISBN: (纸本)9798331527471

Automated monitoring of tool wear is crucial for maintaining product quality. Furthermore, implementing AI techniques for real-time tool monitoring involves not only developing models but also managing their versions, avoiding the issue of models becoming less accurate as the properties of the machinery change over time. Consequently, this study develops a tool wear prediction system integrated with an artificial intelligent (AI) model management platform. First, this system uses various machine learning models to extract diverse signal features from sensor fusion, thereby boosting the accuracy of tool wear prediction. Secondly, the AI Models Management Platform comprises the C# programming language, Neural Networks Processing Unit (NPU) board, and Docker on both user and server sides, enhancing industrial processes and enabling real-time analysis of sensor data. According to these results, the Ensemble Learning method within the machine learning model demonstrates superior performance, yielding an average root mean squared error (RMSE) of 0.000185 mm2. Additionally, AI model management platform efficiently handle various model versions and streamline data training processes, empowering users to select suitable models and thereby enhancing system robustness. © 2024 IEEE.

关键词： C (programming language)

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Generative AI, IoT, and blockchain in healthcare: application, issues, and solutions

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Discover Internet of Things 2025年第1期5卷 1-23页

作者： Mazhar, Tehseen khan, Sunawar Shahzad, Tariq khan, Muhammad Amir Saeed, Mamoon M. Awotunde, Joseph Bamidele Hamam, Habib School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Science International Islamic University Islamabad44000 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Sana’a Yemen Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Science and Information Technology School Education Department Government of Punjab 31200 Layyah Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa Av. Grandes Ecoles LibrevilleBP 1989 Gabon Bridges for Academic Excellence Spectrum Tunis Tunisia

This article discusses Blockchain and Generative AI in healthcare, including their uses, difficulties, and solutions. Blockchain technology improves EHR security, privacy, and interoperability, while smart contracts streamline supply chain management and administrative procedures. Blockchain verifies and secures IoT data, improving medical care and treatment, according to case studies. Generative AI systems like ChatGPT have transformed healthcare by personalizing therapy, diagnostics, and predictive analytics. AI systems can examine massive databases to diagnose diseases early, anticipate dangers, and personalize therapies. By providing timely information, boosting treatment adherence, and giving continuous support, AI-powered virtual health assistants have enhanced patient involvement. Generative AI has additionally enhanced medical research and drug development, cutting the time and expense of introducing new medicines. Generative AI and Blockchain provide safe patient data storage, high-quality AI training datasets, and efficient healthcare operations. Scalability, energy usage, and interoperability issues remain. Scalable Blockchain designs and standardized data integration and exchange protocols are suggested by this study. These technologies could improve medical research and therapy by making them safer, more effective, and more individualized. © The Author(s) 2025.

关键词： Electronic health record

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Enhancing The Attractiveness of Coloring Books Using Live Texturing Augmented Reality

Enhancing The Attractiveness of Coloring Books Using Live Te...

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2023 International Conference on informatics engineering, Science and Technology, INCITEST 2023

作者： Maulana, Hanhan Anshor, Jajang Saeful Kanai, Hideaki Universitas Komputer Indonesia Department of Informatics Engineering and Computer Science Bandung Indonesia Japan Andvanced Institute of Technology and Science The School of Knowledge Science Ishikawa Japan

ISBN: (纸本)9798350317862

This study aims to build live texturing augmented reality to enhance the attractiveness of coloring books. This research has four main stages, namely data gathering, object preparations, software development and evaluations. This study uses UNITY 3D in building a Live Texturing Augmented Reality System. The AR method used is the Marker method. Users can color the marker. The 3D object will follow the color given to the marker in real time. This system is expected to increase children's attraction to coloring. It is hoped that children's understanding of color can also be improved. Furthermore, this system is expected to help children in deciding on color selection so that children's creativity is getting better. © 2023 IEEE.

关键词： Augmented reality

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