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检索条件"任意字段=5th International Conference on Informatics in Control, Automation and Robotics"

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Research on Reading Recognition Method of Pointer Meters Based on Deep Learning Combined with Rotating Virtual Pointer

Research on Reading Recognition Method of Pointer Meters Bas...

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Information Science, Computer Technology and Transportation (ISCTT), international conference on

作者： Xiaoliang Meng Fudong Cai Jinjun Wang Changfeng Lv Huanyun Liu Hongyuan Liu Minwei Shuai Electric Power Automation Division Shandong Senter Electronic Co. Ltd Zibo China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China Jinan Xintongda Electronic Technology Co. Ltd Jinan China

ISBN: (数字)9781728185750

ISBN: (纸本)9781728185767

there are still a large number of pointer meters in substations, which mainly rely on manual inspection to detect the readings of pointer meters. In order to solve the above problems, this paper proposes a pointer meter keypoints detection method based on deep learning combined with virtual pointer rotation to determine the meter readings. this method first uses the deep learning algorithm to train data set of pointer meters and obtain the keypoints information of pointer meters. According to the keypoints information, we can further determine the center of rotation and radius of the pointer meter, then the real position of the pointer meter can be determined. Finally, according to the meter range information, as well as the real pointer angle and the meter range angle, we can calculate the readings of the pointer meter. the experiment results show that the proposed method can quickly and accurately obtain the pointer position, and further identify the meter readings. the proposed method can reduce the uncertainty caused by manual inspection and have a great impact on intelligent development of substations.

关键词： Meters Deep learning Substations Uncertainty Manuals Inspection Meter reading

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RoboMag: A Magnetic Actuation System Based on Mobile Electromagnetic Coils With Tunable Working Space

RoboMag: A Magnetic Actuation System Based on Mobile Electro...

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international conference on Advanced robotics and Mechatronics (ICARM)

作者： Xingzhou Du Lidong Yang Jiangfan Yu Kai Fung Chan Philip Wai Yan Chiu Li Zhang Technology Centre for Innovative Medicine The Chinese University of Hong Kong (CUHK) Hong Kong China The Chinese University of Hong Kong (CUHK) Hong Kong China CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

Magnetic field is regarded as a safe and efficient method for controlling minimally invasive medical robots remotely, and magnetic actuation system based on mobile electromagnetic coils are preferred due to the enlarged working space and fast response. Enhanced flexibility on coils' positions will further enable the system to deal with possible constraints inside the workspace, while design and control of such flexible systems remain challenging. In this work, a magnetic actuation system based on three mobile electromagnetic coils with decoupled movements is designed and the performance is demonstrated. the system consists of three 4-axis robotic arms that can adjust the relative positions of three mobile coils independently. the prototype of RoboMag is designed and able to program magnetic field at a required point inside a hemispherical space with a diameter of 152 mm. A method to drive the mobile-electromagnetic-coil-based systems with flexible movements is proposed. To begin with, a model of the robotic platform is built to place the coils to demanded position. A numerical model of a single coil is constructed and average error of magnetic field is reduced to 3.30% after calibration. Afterwards, a method based on coordinate transformation is proposed for the entire system to produce demanded magnetic torque and force at a required position. Experiments are conducted to demonstrate the system's capability on generating magnetic torque and force to actuate medical device analog.

关键词： Coils Magnetic resonance imaging Robot kinematics Manipulators Magnetic moments Magnetic devices

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Recognizing Malaysia Traffic Signs with Pre-Trained Deep Convolutional Neural Networks

Recognizing Malaysia Traffic Signs with Pre-Trained Deep Con...

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international conference on Cybernetics, robotics and control (CRC)

作者： Dickson Neoh Tze How Khairul Salleh Mohamed Sahari Yew Cheong Hou Omar Gumaan Saleh Basubeit Universiti Tenaga Nasional Kajang Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Selangor Malaysia Department of Electrical & Electronics Engineering Universiti Tenaga Nasional Kajang Selangor Malaysia

ISBN: (数字)9781728146201

ISBN: (纸本)9781728146218

An essential component in the race towards the self-driving car is automatic traffic sign recognition. the capability to automatically recognize road signs allow self-driving cars to make prompt decisions such as adhering to speed limits, stopping at traffic junctions and so forth. Traditionally, feature-based computer vision techniques were employed to recognize traffic signs. However, recent advancements in deep learning techniques have shown to outperform traditional color and shape based detection methods. Deep convolutional neural network (DCNN) is a class of deep learning method that is most commonly applied to vision-related tasks such as traffic sign recognition. For DCNN to work well, it is imperative that the algorithm is given a vast amount of training data. However, due to the scarcity of a curated dataset of the Malaysian traffic signs, training DCNN to perform well can be very challenging. In this demonstrate that DCNN can be trained with little training data with excellent accuracy by using transfer learning. We retrain various pre-trained DCNN from other image recognition tasks by fine-tuning only the top layers on our dataset. Experiment results confirm that by using as little as 100 image samples for 5 different classes, we are able to classify hitherto traffic signs with above 90% accuracy for most pre-trained models and 98.33% for the DenseNet169 pre-trained model.

关键词： Computer vision Deep learning Convolutional neural networks Object recognition Image classification

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A Rule Based Expert System to Advise on Air-Filtering Plants for Indoor Spaces in UAE 19

A Rule Based Expert System to Advise on Air-Filtering Plants...

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Proceedings of the 2019 5th international conference on Systems, control and Communications

作者： Grishma Jayesh Doshi Joseph D. Stevens Saima Tariq Khan Murdoch University Dubai U.A.E.

ISBN: (纸本)9781450372640

the purpose of this study was to develop an expert system that recommends types of plants that help remove toxic substances to improve air quality in a given ***, it is usually horticultural experts who suggest the right plants as per the environment, where feasible. there is also a significant gap in research related to any such smart systems as revealed in the literature *** led to the creation of the Plant Recommender Expert System (PRES) - an intelligent system that accesses expert knowledge by utilizing a set of inputs (e.g. expected humidity, average temperature, etc.) to recommend the type(s) of plants that should be purchased to suit the conditions of any given *** to office environments within the United Arab Emirates (UAE), PRES was successfully evaluated using several case studies with known outcomes.

关键词： Agro-informatics Sustainable Environments Decision Support Expert Systems Air Quality

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TotCareBot: A Comprehensive Approach Towards Enhancing Early Childhood Education through robotics

TotCareBot: A Comprehensive Approach Towards Enhancing Early...

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international conference on Circuits, Communication, control and Computing

作者： Manjula R Chougala Sushma B Akshata S Bhayyar Abhay Bhandarkar P N Pavithra Dept. of Computer Science and Engineering Ramaiah Institute of Technology Bangalore India Department of Computer Science Engineering Ramaiah Institute of Technology Bengaluru India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528546

Robots have emerged as versatile tools with significant potential to enhance teaching and learning environments, including classrooms, laboratories, play homes, crèches, and even at home. their engaging nature can captivate young children, boosting motivation and interest. this paper proposes a methodology for an Educational Robot (ER) designed for play homes. the ER is capable of moving around the classroom, monitoring children, analyzing their emotions, responding appropriately, and alerting the teacher when necessary. the proposed system aims to leverage the positive impact of expressive behaviors in robots, such as storytelling and pampering. Our findings indicate that expressive robot narration is as effective as that of a human displaying similar behaviors and even surpasses a static, inexpressive human narrator. Furthermore, the robot excels in conveying educational content, although its limited emotional expression slightly reduces its effectiveness in narrating emotionally rich stories. this research underscores the potential of ERs to create dynamic and interactive learning experiences for young children, fostering both their cognitive and emotional development.

关键词： Educational robots Education Laboratories Circuits Boosting Behavioral sciences Robots Erbium Monitoring

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Interval-Valued Fuzzy Bézier Surface Approximation

Interval-Valued Fuzzy Bézier Surface Approximation

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international conference on Artificial Intelligence and Data Sciences (AiDAS)

作者： Nor Ashikin Sahrom Mohammad Izat Emir Zulkifly Siti Nur Idara Rosli Department of Mathematics Faculty of Science Universiti Teknologi Malaysia Johor Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Cawangan Negeri Sembilan Kampus Kuala Pilah Negeri Sembilan Malaysia

ISBN: (数字)9798331528553

ISBN: (纸本)9798331528560

In the field of geometry and computer-aided design Bézier surfaces are well known for their flexibility and effectiveness, in depicting shapes. However, dealing with real-world data and model parameters often involves uncertainty and imprecision that regular Bézier surfaces struggle to handle. this piece introduces the idea of interval-valued fuzzy Bézier Surface Approximation, an approach that combines logic and interval arithmetic to tackle uncertainty in surface modeling. In this paper, interval-valued fuzzy Bézier surface approximation is introduced. the interval-valued fuzzy control net relation is defined and introduced. Next, the surface blending function is obtained by blending the interval-valued fuzzy control net with the Bernstein blending function. Lastly, the data points or interval-valued fuzzy control net relation of the basis function is illustrated using the approximation method with the interval-valued fuzzy concept and features to produce an interval-valued fuzzy Bézier surface. the application of Bézier surfaces can be extended to handle a wide range of complex modeling and offers a more precise and dependable tool for engineering, graphics, and data visualization applications.

关键词： Solid modeling Fuzzy control Uncertainty Machine learning algorithms Shape Computational modeling Data visualization Data models Surface fitting Robustness

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How Electromyography Readings from the Human Forearm are Made Cryptic, Trivial, or Non-Trivial Information for Use in Synthetic Systems

How Electromyography Readings from the Human Forearm are Mad...

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2015 5th international conference on Biomedical Engineering and Technology

作者： A.Y.Bani Hashim Z.Fu Z.Jamaludin I.S.Mohamad Department of Robotics & Automation Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Faculty of Mechanical Engineering Universiti Teknikal Malaysia Melaka

the success of reading potentials generating from human muscle activities is evident that proves that the human body's neural system is naturally electronics. Now, modern engineering is accepting it as one field of engineering science. Due to this, the concept of a cyborg is beginning to realize as products such as exoskeletons and neuroprostheses. the object of this work, however, is to view from a different perspective as to how this is beneficial to the functions beyond the mentality of today's applications. We hypothesized that the recorded potentials from muscle activities may be regarded similar as to the signals that jump between synapses in the biological neurons. We suggest that these signals, instead of mere electrical in nature, their waveforms might include emotion characteristics from uniquely combined muscle activities and feeling. the system codes the signals where the newly created information may be made cryptic, trivial, or nontrivial depending on how they are going to be utilized in the synthetic systems. So that the artificial system could sense, for instance, the emotion of the human host.

关键词： Electromyography neurons forearm muscle

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Identifying Ripeness in Chokanan Mango Fruit Using K-Nearest Neighbor

Identifying Ripeness in Chokanan Mango Fruit Using K-Nearest...

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international conference on Artificial Intelligence and Data Sciences (AiDAS)

作者： Nur Athirah Syafiqah Noramli Raihana Md Saidi Hajar Izzati Mohd Ghazalli College of Computing Informatics & Mathemathics MARA University of Technology Malacca Malaysia

ISBN: (数字)9798331528553

ISBN: (纸本)9798331528560

Chokanan are popularly grown in Malaysia for both local consumption and export markets which is a sweet mango variety originating from thailand, India, Bangladesh, and Pakistan. the evaluation of mango fruit maturity is crucial for quality control, supply chain management, and consumer satisfaction. However, existing methods suffer from several limitations, including time-consuming procedures, subjectivity, and potential inaccuracies. In this study, we utilize an approach using the K-Nearest Neighbor (KNN) algorithm to recognize the maturity level of Chokanan mango fruit. the proposed approach involves the extraction of relevant features from images of mango fruits, followed by the training of the KNN classifier using a labelled dataset. the trained model is then utilized to classify unseen mango fruit samples into different maturity classes. the experimental results indicate that the developed system shows strong potential in accurately recognizing the maturity level of mango fruits, achieving a high classification accuracy. While the system demonstrated a high level of accuracy in the tests conducted, further validation and testing are needed to confirm its effectiveness across broader conditions. these findings suggest promising potential for improving mango maturity recognition, reducing effort, and enhancing overall fruit quality assessment.

关键词： Training Accuracy Supply chain management Quality control Nearest neighbor methods Feature extraction Quality assessment Planning Object recognition Testing

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Integration of MITL for Cobots Workflow in a Manipulating Application

Integration of MITL for Cobots Workflow in a Manipulating Ap...

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international conference on Emerging Technologies and Factory automation (ETFA)

作者： Sofia Hustiu Andrei-Iulian Iancu Florian-Alexandru Brasoveanu Department of Automatic Control and Applied Informatics “Gheorghe Asachi” Technical University of Iasi Romania

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Cooperative machines are the essence of automated systems that provide solutions in various domains, one example being the manufacturing industry. Specifically, the ability to synchronize the mission of each robot represents a crucial decision-making factor in this domain. this paper provides a path-planning solution for an application with two collaborative robots (also known as cobots) that should fulfill individual missions under the Metric Interval Time Logic (MITL) formalism. this formalism allows us to embody spatial and time requirements. this work provides two contributions in this field, based on the two phases of the planning solution: (a) a synchronization mechanism based on a high-level planner, developed on a previously defined model denoted Composed Time Petri net, that joins both the mission of the robots and its capabilities of movement and (b) experimental validation of the high-level planner based on a low-level path execution implemented on Robot Operating System (ROS) that facilitates the execution of the planned path to validate the simulated event sequence. the Composed Time Petri net is model-checked through simulations in the ROMEO tool, while the corroboration of the results is based on an experiment with two cobots: UR5 and LM3 with individual MITI missions, that are collaborating in a manipulating application: UR5 should pick and place pieces, while LM5 should pick up a tool, e.g., welding gun, to glue the pieces. A video with the results can be inspected here [1].

关键词： Service robots Welding Space missions Petri nets Collaborative robots Planning Trajectory Safety Synchronization Robots

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Hydration Assessment Among Foreign University Students

Hydration Assessment Among Foreign University Students

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international Symposium on Computational Intelligence and informatics

作者： Ogbolu Melvin Omone Miklós Kozlovszky Tamás Ferenci Iklaga Gabriel Inalegwu BioTech Research Center EKIK Óbuda University Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Faculty of Science Eötvös Loránd Research University Budapest Hungary

ISBN: (数字)9781728156255

ISBN: (纸本)9781728156262

Background: Adequate food intake and adequate water intake (AWI) plays a vital role in body development, human health and total wellbeing. Water intake (WI) is one of the major and crucial nutrients for health promotion and disease prevention. Beverage consumption is also a medium through which water is consumed but the content of the beverage is very important to staying hydrated and living healthy. Despite this, there is a viaduct in proper knowledge about the exact amount of total water intake (TWI) and hydration status among students in Obuda University. Aim: the primary aim of this study is to bring an awareness among Obuda University students about how important water is to health and staying hydrated which further enhance a good study performance. To check if the students suffer from any dehydration-related symptoms and to conduct descriptive analysis on which channels they acquire information about hydration. therefore, we focus on water drinking habits by investigating if Obuda University students from Africa, Asia and Europe adheres to hydration policy as regards to the recommended daily total water intake (TWI) according to the European Food Safety Authority (EFSA) for Europeans and the World Health Organization (WHO) for Africans and Asians, and to explore if they are well hydrated. Methods: A cross-platform survey was distributed to extort data about drinking habits and the awareness of hydration among the students. the questions contained in the survey took approximately 5 minutes to complete. there were 385 responses but 323 were qualified for the investigation. Data analysis was conducted using SPSS v26 and descriptive statistics are presented throughout the study. Results: there were 323 young-aged participants between the ages of 18-35 years from Africa, Asia, and Europe included in the study. Between 10%-22% of the population were aware of the TWI by both EFSA and WHO which induce that many among the student population are suffering from dehydrati

关键词： Adequate water intake Beverage consumption Drinking habits Hydration Total water intake Water intake Water Intake Students Hydration drinking habits European Food Safety Authority World Health Organisation Awareness Beverages

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