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Empowering self-sustained agriculture: an IoT field tracking model driven by fog computing

Discover Internet of Things 2025年第1期5卷 1-18页

作者： Singh, Gurpreet Singh, Jaspreet Juneja, Sapna Gulzar, Yonis Gupta, Deepali Ghafoor, Kayhan Zrar Kumar, Mukesh Department of Computer Science and Engineering Chandigarh University Punjab Chandigarh140413 India KIET Group of Institutions Delhi-NCR Uttar Pradesh Ghaziabad201206 India Department of Management Information Systems College of Business Administration King Faisal University Al-Ahsa31982 Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Information and Communication Technology Eng Erbil Polytechnic University 42VQ+756 120 Meter St Erbil Erbil Governorate Iraq Mechanical Engineering College of Engineering Assosa University Assosa5220 Ethiopia

Increasing availability of cost effective IoT (Internet of Things) devices have led to the development of IoT- based farm management systems. Smart Agriculture is a demanding approach that employs the use of technology-enabled information and communication to monitor farms. In India, somewhere around 60% of the organization’s operations mostly dependent on agriculture directly or indirectly. A nation’s advancement is typically influenced by concerns with agriculture. The most effective approach to addressing agriculture’s challenges is always to improve traditional agricultural practices as well as modernize them into smart agriculture. The smart agriculture technique offers beneficial data collection, highly precise control as well as automated monitoring strategies. This research proposed a IoT assisted fog-based model that promises to provide the cost-effective smart agriculture system. Fog platform brings computation and storing nearer at the network’s the border, allowing for the efficient processing of data produced by IoT devices across smart agricultural systems. The bibliometric evaluation of the Web of Science database for the adoption of the IoT-Fog base infrastructure in the creation of smart agriculture systems is also highlighted in this paper. The proposed solution when implemented as well as when contrasted with existing IoT-based agriculture system exhibit better efficiency. The result revealed that proposed system brings down response time, error rate and standard deviation to significant level and improves the accuracy of current system exponentially. © The Author(s) 2025.

关键词： Agricultural robots

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Experimental Assessment of Containers Running on Top of Virtual Machines

arXiv

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arXiv 2024年

作者： Aqasizade, Hossein Ataie, Ehsan Bastam, Mostafa Department of Computer Engineering University of Mazandaran Babolsar Iran Distributed Computing Systems Research Group University of Mazandaran Babolsar Iran

Over the past two decades, the cloud computing paradigm has gradually attracted more popularity due to its efficient resource usage and simple service access model. Virtualization technology is the fundamental element of cloud computing that brings several benefits to cloud users and providers, such as workload isolation, energy efficiency, server consolidation, and cost reduction. This paper examines the combination of operating system-level virtualization (containers) and hardware-level virtualization (virtual machines). To this end, the performance of containers running on top of virtual machines is experimentally compared with standalone virtual machines and containers based on different hardware resources, including the processor, main memory, disk, and network in a real testbed by running the most commonly used benchmarks. Paravirtualization and full virtualization as well as type 1 and type 2 hypervisors are covered in this study. In addition, three prevalent containerization platforms are examined. © 2024, CC BY.

关键词： Virtual machine

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Kid Activity Recognition: A Comprehensive study of kid activity recognition with monitoring activity level using YOLOv8s Algorithms 3

Kid Activity Recognition: A Comprehensive study of kid activ...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Bisla, Tiya Shukla, Ritik Dhawan, Mansi Islam, Md. Rahatul Koyasu, Takao Teramoto, Keisuke Kataoka, Yui Horio, Keiichi Dronacharya Group of Institution Dept. of Computer Science & Engineering Greater Noida India Kyushu Institute of Technology Graduate School of Life Science and Systems Engineering Fukuoka Japan Kyushu Women's Junior College Fukuoka Japan Aichi University of Education Aichi Japan Fukuoka Kodomo Junior College Fukuoka Japan

ISBN: (纸本)9798350372120

Recognizing human activities and behavior is a cutting-edge field of research because of the complexity and limited availability of data. Our research involves the use of the trending YOLOv8s deep learning algorithm for the classification of active states (sitting, standing, running, laying, and jumping). The research focuses on the detection of a child's activities in the kindergarten playroom. To train the model, we created the KAR (Kids Action Recognition) dataset using our own sources. We labeled over 6,489 images in the dataset using ***. Each image is annotated with activity labels and the location of the student (in a room or on a mat). This assisted in presenting insights on the student's vitality level and physical involvement over a period of approximately an hour. We analyzed the whole activity and compared it with the times. Standing in the room and mat, standing in the room, and jumping in the room and mat are most of the activities of the kid. The model achieved an impressive overall accuracy of 88.7 %. We conducted all the training in a Google collaborative environment with A-100 GPU specifications. The results demonstrate that the model can identify and classify each activity with high precision. © 2024 IEEE.

关键词： Graphics processing unit

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On Configuration Sequences in Feature Models 24

On Configuration Sequences in Feature Models

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18th International Working Conference on Variability Modelling of Software-Intensive systems, VaMoS 2024

作者： Meixner, Kristof Feichtinger, Kevin Greiner, Sandra Rabiser, Rick Cdl Sqi Ise Tu Wien Austria Crc 1608 Kastel Dependability of Software-intensive Systems Karlsruhe Institute of Technology Germany Software Engineering Group Institute of Computer Science University of Bern Switzerland Cdl VaSiCS Lit Cps Lab Jku Linz Austria

ISBN: (纸本)9798400708770

Feature models are the de-facto standard in product line engineering to capture the commonalities and variability of systems. However, feature models provide little user guidance during configuration and are unable to represent configuration sequences. A configuration sequence refers to the specific order and combination of features that can be selected when configuring a product line. While mechanisms, such as staged configuration and configuration workflows, exist, we argue that the effort to implement these mechanisms does not pay off for small feature models. This paper motivates the use of configuration sequences for feature models to support better user guidance even for a single feature model. We highlight the need for such user guidance and configuration sequences with a real-world use case. © 2024 ACM.

关键词： Configuration Sequence Feature Models User Guidance.

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Investigation on Structures of Axial Gap Type Magnetic Multiple Spur Gear for In-Wheel Motor System of Electric Vehicle

Investigation on Structures of Axial Gap Type Magnetic Multi...

引用

2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023

作者： Kamijo, Taiga Aiso, Kohei Akatsu, Kan Aoyama, Yasuaki Shibaura Institute of Technology Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan Yokohama National University Division of Intelligent Systems Engineering Department of Faculty of Engineering Yokohama Japan Center for Technology Innovation - Materials Hitachi Ltd. Research & Development Group Ibaraki Japan

ISBN: (纸本)9798350314274

A novel drive system using Magnetic Multiple Spur Gear (MMSG) and multiple high-speed motors is characterized by small size, lightweight, and high efficiency even at high-speed region, it is expected to apply to in-wheel motor systems. However, there is a risk of contact between the rotors when applied to in-wheel motor system. In this study, a novel axial-gap MMSG is proposed to solve this problem, stabilize the air gap between the high-speed and low-speed rotors, and effectively utilize the magnets, and its performance is evaluated by finite element analysis. © 2023 IEEE.

关键词： Electric vehicles

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Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Communication Network Layer State Estimation Measurement Mod...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Mathieu, Reynold Boamah, Sharon Cooper, Austin Agnew, Dennis McNair, Janise Bretas, Arturo University of Florida Department of Electrical and Computer Engineering GainesvilleFL United States Distributed Systems Group Pacific Northwest National Laboratory RichlandWA United States G2Elab Grenoble INP CNRS Universite Grenoble Alpes Grenoble38000 France

ISBN: (纸本)9798350313604

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in the generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing an enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlights potential aspects of th

关键词： Smart power grids

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Microgrid Frequency Stability: A Proactive Scheme Based on Dynamic Predictions

Microgrid Frequency Stability: A Proactive Scheme Based on D...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Paramo, Gian Bretas, Arturo Meyn, Sean University of Florida Department of Electrical and Computer Engineering GainesvilleFl United States G2Elab Grenoble INP CNRS Université Grenoble Alpes Grenoble38000 France Distributed Systems Group Pacific Northwest National Laboratory Richland99354 United States

ISBN: (纸本)9798350313604

The dynamic nature of microgrids introduces challenges in the context of frequency stability. This work presents a framework where the future state of microgrid frequency is predicted and corrective actions are optimized. Predictions are generated through Bayesian filters leveraging synchronized data acquired via PMUs. Taking a proactive approach makes it possible to optimize corrective actions considering dynamic system conditions. Testing is conducted via Matlab simulations. The performance of the solution presented in this work is compared to traditional load-shedding schemes and to predictive solutions found in literature. The results indicate that the proposed framework outperforms both. Some of the advantages of this framework include a reduction in amount of load dropped during compensation, the use of adaptive parameters which eliminates the need to simulate contingency conditions, and dynamic uncertainty quantification provided the particle filter. © 2024 IEEE.

关键词： MATLAB

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SRG Analysis of Lur’e systems and the Generalized Circle Criterion

arXiv

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arXiv 2024年

作者： Krebbekx, Julius P.J. Tóth, Roland Das, Amritam Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Lab HUN-REN Institute for Computer Science and Control Budapest Hungary

Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from some pitfalls that limit its applicability in analysing practical nonlinear systems. We overcome these pitfalls by modifying the SRG of a linear time invariant operator, combining the SRG with the Nyquist criterion, and apply our result to Lur’e systems. We thereby obtain a generalization of the celebrated circle criterion, which deals with broader class of nonlinearities, and provides (incremental) L2-gain performance bounds. We illustrate the power of the new approach on the analysis of the controlled Duffing oscillator. © 2024, CC BY.

关键词： Frequency domain analysis

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The Jade Gateway to Exergaming: How Socio-Cultural Factors Shape Exergaming Among East Asian Older Adults

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Proceedings of the ACM on Human-computer Interaction 2024年第CHI PLAY期8卷 1-34页

作者： Hadi Mogavi, Reza Son, Juhyung Yang, Simin Wang, Derrick M. Choong, Lydia Alhilal, Ahmad Zhou, Peng Yuan Hui, Pan Nacke, Lennart E. HCI Games Group Stratford School of Interaction Design and Business University of Waterloo WaterlooON Canada Guangzhou China Hong Kong University of Science and Technology Hong Kong Aarhus University Aarhus Denmark The Hong Kong University of Science and Technology University of Helsinki Hong Kong The Department of Systems Design Engineering University of Waterloo Canada The Cheriton School of Computer Science University of Waterloo Canada

Exergaming, blending exercise and gaming, improves the physical and mental health of older adults. We currently do not fully know the factors that drive older adults to either engage in or abstain from exergaming. Large-scale studies investigating this are still scarce, particularly those studying East Asian older adults. To address this, we interviewed 64 older adults from China, Japan, and South Korea about their attitudes toward exergames. Most participants viewed exergames with a positive inquisitiveness. However, socio-cultural factors can obstruct this curiosity. Our study shows that perceptions of aging, lifestyle, the presence of support networks, and the cultural relevance of game mechanics are the crucial factors influencing their exergame engagement. Thus, we stress the value of socio-cultural sensitivity in game design and urge the HCI community to adopt more diverse design practices. We provide several design suggestions for creating more culturally approachable exergames. © 2024 Owner/Author.

关键词： Game design

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Leveraging Empowerment to Model Tool Use in Reinforcement Learning

Leveraging Empowerment to Model Tool Use in Reinforcement Le...

引用

IEEE International Conference on Development and Learning, ICDL

作者： Faizan Rasheed Daniel Polani Nicola Catenacci Volpi Adaptive Systems Research Group School of Physics Engineering and Computer Science University of Hertfordshire Hatfield UK

Intrinsic motivation plays a key role in learning how to use tools, a fundamental aspect of human cultural evolution and child development that remains largely unexplored within the context of Reinforcement Learning (RL). This paper introduces “object empowerment” as a novel concept within this realm, showing its role as information-theoretic intrinsic motivation that underpins tool discovery and usage. Using empowerment, we propose a new general framework to model the utilization of tools within RL. We explore how maximizing empowerment can expedite the RL of tasks involving tools, highlighting its capacity to solve the challenge posed by sparse reward signals. By employing object empowerment as an intrinsically motivated regulariser, we guide the RL agent in simple grid-worlds towards states beneficial for learning how to master tools for efficient task completion. We will show how object empowerment can be used to measure and compare the effectiveness of different tools in handling an object. Our findings indicate efficient strategies to learn tool use and insights into the integration and modeling of tool control in the context of RL.

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