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An EEG-Based Brain-Computer Interface for Guiding Mobile robots 3

An EEG-Based Brain-Computer Interface for Guiding Mobile Rob...

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3rd international conference on Advances in Computing, Communication, Embedded and Secure Systems, ACCESS 2023

作者： Saluja, Kamal Gupta, Sunil Solanki, Vikas Debnath, Sanjoy Kumar Bansal, Ankit Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350346169

The term "robot"refers to an electromechanical device that, as a result of its incorporation of electronic and computer programming, may carry out tasks either independently or in conjunction with a human operator [1]. robots can be designed to perform functions in any order that the programmer specifies. robots have found uses in a broad variety of disciplines, including those connected to the military, healthcare, and industry, among a number of other fields. robots can be programmed to perform in either a mobile or stationary manner, and the choice of which mode to use is often dictated by the tasks that are intended to be carried out by the robots. It is extremely essential for a mobile robot to be able to traverse its environment in order for the robot to be capable of efficiently completing tasks, avoiding obstacles, and participating in other activities. This capability for navigation, which is dependent on sensors to supply environmental data as feedback signals, can be operator-independent or autonomous if "intelligence"is built into the computer code. Sensors are required to provide environmental data as feedback signals. Sensors are required to provide environmental data as return signals. This learning opportunity can be further used in affordable energy, agriculture, environmentally sound technologies, etc. © 2023 IEEE.

关键词： Brain computer interface

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Wheely: An Accessible Platform for Experimenting with Wheeled-Legged Quadrupedal robots 3

Wheely: An Accessible Platform for Experimenting with Wheele...

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3rd international conference on Computer, Control and robotics, ICCCR 2023

作者： Zhang, William Wang, Ke Weston High School Grade 10 Boston United States Imperial College London Robot Intelligence Lab London United Kingdom

ISBN: (纸本)9781665492126

Wheely is a small and inexpensive wheeled-legged quadruped robot made to be an accessible method of experimenting with wheeled-legged robots. The current robotics environment lacks economic wheeled-legged quadrupedal robots for low stakes experimentation and use. The robot uses low-cost and easy to acquire servo motors for a simple, but reliable build. With total costs within 600 dollars, Wheely is around 0.2 m tall and weighs roughly 3 kg. Wheely's simplistic and small-scale nature allows it to be deployed by a single operator and is modification friendly. Wheely is the combination of the best of two worlds, wheeled and legged locomotion, allowing efficient travel on both smooth and rugged terrain. Experiments on robot were conducted in a simulated environment using Pybullet. Wheely is capable of autonomously surmounting stairs 0.05 m tall, 25% of its normal body height, using open loop gaits generated using Bezier curves. On flat surfaces, Wheely can reach speeds of up to 0.09 m/s using wheeled and 0.04 m/s using legged locomotion. Wheely's relatively low-cost and accessible nature will allow for the proliferation of wheeled-legged quadruped technologies and freedom of experimentation. © 2023 IEEE.

关键词： Costs

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SteeringNET - A Deep-Learning based Obstacle Avoidance Approach for Autonomous Driving 3

SteeringNET - A Deep-Learning based Obstacle Avoidance Appro...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Perumal, P Shunmuga Kanchwala, Husain Wang, Yong Pandiyaraju, V. Krishnakumar, Nikil Saravanan, Rammesh Adhav Kollipara, Hemanth Kumari, Oshi Vellore Institute of Technology Vellore India Indian Institute of Technology Delhi India Binghamton University Binghamton United States University of Minnesota Twin-Cities United States The Ohio State University Columbus United States InsideFPV Surat India

ISBN: (纸本)9798350372120

In this paper, a deep-learning based model named SteeringNET is proposed for obstacles avoidance. Three categories of obstacles were chosen, namely, two-wheelers, cars, and buses. The Ego Vehicle (EGV) was defined using a kinematic model and integrated with the Adaptive Model Predictive Control (MPC) to simulate the obstacle avoidance strategies for human drivers. The dataset for the human driver obstacle avoidance trajectories was generated using MATLAB simulations. A total of 14040 trajectories: 5400, 2160 and 6480 for stationary two-wheeler, car, bus obstacles were obtained. Conventional MPC based models are computationally expensive for obstacle-free trajectory generation and are unsuitable for real-time applications. Our model readily predicts the throttle, steering angle values for negotiating different obstacles and the prediction time is significantly lesser than the Adaptive MPC. Four different versions of this model are implemented namely, Fully Connected Neural Network (FCNN), FCNN with custom loss, Long Short-Term Memory (LSTM) and LSTM with custom loss. The experimental results show that LSTM with custom loss algorithm outperforms the other three deep-learning models. © 2024 IEEE.

关键词： Trajectories

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Acoustic Scene Classification Using Deep C-RNN Based on Log Mel Spectrogram and Gammatone Frequency Cepstral Coefficients Features 3

Acoustic Scene Classification Using Deep C-RNN Based on Log ...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Khine, Kyawt Kay Su, Chaw Department of Information Technology Taunggyi Myanmar Faculty of Informationand Communication Technology Pyin Oo Lwin Myanmar

ISBN: (纸本)9798350372120

Acoustic scene classification, or ASC, has gained much interest recently due to its numerous applications. However, ASC's performance is significantly poorer than other audio processing domains, such as speech recognition and music classification. Many machine learning and acoustic signal processing techniques have been proposed for high-performing ASC systems. To investigate the acoustics scenes from various audio signal versions, this work assesses ASC based on the characteristics extracted from Mel Frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC). During the feature extraction step, each frequency call is extracted and parametrized using MFCC, GFCC, and combination features (M-GFCC) to segment the signals. This paper proposes a Deep Convolutional-Recurrent Neural Network (Deep C-RNN) strategy to categorize the efficacy of learning acoustics variations in the classification stage, making use of recent developments in Deep Learning techniques. Firstly, a combination of Mel-Gammatone filters is used in convolutional layers to extract high-level spectrum information. After that, the recurrent layers are used to extract the high-level characteristics' long-term temporal context. The method proposed in this paper is applied to a large dataset called Detection and Classification of Acoustic Scenes and Events (DCASE 2017). The system is implemented on the Matlab2023b platform and achieved an overall average accuracy score of 81.27%. © 2024 IEEE.

关键词： Recurrent neural networks

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Sustainable Seas RoboScrub: An Arduino based Sludge Cleaning System 3

Sustainable Seas RoboScrub: An Arduino based Sludge Cleaning...

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3rd international conference on Innovative Mechanisms for Industry applications, ICIMIA 2023

作者： Kayalvizhi, S. Akash, M. Gayathri, R. Harini, P. Easwari Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343632

The maritime industry heavily relies on various fluids stored in ship tanks, encompassing fuel, oils, sludge, sewage, and water. Over time, these fluids solidify, forming layers that necessitate regular cleaning. Traditional cleaning methods pose severe risks to human workers, despite safety measures, with the potential for accidents and explosions [F. The paper underscores the pressing need for a safer and more efficient sludge cleaning solution tailored for ships. To address this, the proposal introduces an innovative approach - an autonomous robot equipped with a specialized attachment explicitly designed for efficient sludge removal. Engineered to navigate and thoroughly clean all tank areas, this technology aims to significantly diminish risks, prevent accidents, curtail time delays, and optimize labor costs associated with sludge maintenance. The integration of this robotic solution not only enhances safety protocols but also revolutionizes the efficiency of sludge management practices in the maritime sector. © 2023 IEEE.

关键词： Maritime Safety Oil Transportation Ship Maintenance Sludge Removal Tank Cleaning robot

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HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements Classification from Motor Imagery EEG 3

HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements C...

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3rd IEEE international conference on robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Tasnimul Hossain, A.B.M. Aowlad Biswas, Shuvagata Tazrin, Farhana Khulna University of Engineering & Technology Department of Biomedical Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Electronics and Communication Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798331534400

Motor imagery-based BCI plays a vital role in controlling hand movements by processing and recognizing features from EEG signals associated with the imagination of those movements. In this paper, we present a Kolmogorov-Arnold Networks (KAN) based framework in order to classify the left and right-hand movements along with the absence of movement's intention from the electroencephalogram (EEG) signal. The emergence of KAN is expected to be a breakthrough concept in the artificial intelligence paradigm considering its learnable activation functions mechanism and interpretability opportunities. Preprocessing of the collected raw EEG data has been accomplished with band-pass filtering of EEG components of five well-matched channels and corresponding power spectral density feature extraction. We have used 15282 samples with annotated classes from a publicly available dataset to train, validate, and test the classifier. A comparative analysis of the performance of KAN and conventional Multi-Layer Perceptron (MLP) networks has been conducted in order to investigate the effectiveness of the KAN for this classification task. The proposed framework attains 96.14% classification accuracy for 3057 blind test samples, which is found to be better than the conventional MLP neural network approach (76.64% accuracy) and compatible with the existing techniques. The finding of this research might be useful in hand movement-related applications for robotics, prosthetics, and neuro-rehabilitation supports. © 2024 IEEE.

关键词： Multilayer neural networks

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Advances in Artificial intelligence, Big Data and Algorithms - Proceedings of the 3rd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2023

Advances in Artificial Intelligence, Big Data and Algorithms...

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3rd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2023

ISBN: (纸本)9781643684444

The proceedings contain 149 papers. The topics discussed include: effects of AI on smart agriculture: a case study of digital agriculture base;image retrieval-based product identification for automatic checkout systems;application of lightweight emotion recognition model in intelligent construction site monitoring;research on the application of smart wearable in the emotional management of the elderly;artificial intelligence technology in the field of broadcasting and hosting;intelligent inspection method for photovoltaic modules based on image processing and deep learning;application of AI algorithms in power system load forecasting under the new situation;research on the intelligent operation and maintenance control system of power distribution network based on big data technology;research progress of intelligent rail transit train control system;and design and implementation of intelligent potted plant management system based on Internet of Things.

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Advanced Lung Cancer Diagnosis and Treatment with Artificial intelligence: applications, Methods, and Future Directions 3

Advanced Lung Cancer Diagnosis and Treatment with Artificial...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Chaudhari, Pawan Dilip Gudadhe, Amit Maharashtra Wardha442001 India Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

AI technology revolutionizes the treatment of lung cancer and other related lung cancer diagnoses, hence becoming the game-changing technology in the diagnosis and treatment of this serious disease. As one of the most prevalent and deadliest cancers globally, early identification, precise diagnosis, and efficient planning for the treatment of lung cancer have always been difficult. The therapy using AI-based methods is introducing another novel way of addressing the problems concerning lung cancer via advanced imaging analysis, predictive modeling, and tailored plans of treatment, the most important among which is of course, imaging analysis. What is certainly most exciting among the applications of AI in lung cancer treatment is in the realm of imaging analysis. AI has been seen to be extremely clever in the interpretation of images rather than using machine learning or deep learning but has been much faster and more accurate than a human being while doing it. Besides, these systems also increase the general accurateness of diagnosis through a reduction of the error in diagnosis and consistent results. Alluring promises are made for AI soon for the treatment of lung cancer. In this paper, we discuss how AI has been transformed into imaging, diagnosis, and treatment planning and how this will improve patient outcomes and completely transform the way healthcare is delivered. We also consider barriers still to be cleared for realizing fully the potential benefits of AI. These include problems such as the quality of available data used in model interpretation and generalizability across different healthcare settings. Therefore, we end and suggest some future research on collaboration by emphasizing the safe, effective, and ethical entry of AI into normal clinical practice. © 2025 IEEE.

关键词： Lung cancer

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Unveiling the Future: Exploring the Impacts and Challenges of Artificial intelligence in Workplace applications 3

Unveiling the Future: Exploring the Impacts and Challenges o...

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3rd international conference for Advancement in technology, ICONAT 2024

作者： Pragith, S. Supriya, S. Sasikala, S. Sateesh, Rayala Swamy, Hemanth Karpagam, P. Vellore Institute of Technology Department of Computer Science Engineering Vellore India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering India Tagore Engineering College Department of ECE Chennai India MLR Institute of Technology Department of ECE Hyderabad India Motorola Solutions United States Dhanalakshmi College of Engineering Department of Cyber Security Chennai India

ISBN: (纸本)9798350354171

Unveiling the Future: Exploring the Impacts and Challenges of Artificial intelligence in Society' embarks on a comprehensive journey through the transformative landscape shaped by Artificial intelligence (AI). This abstract offers a nuanced examination of AI's profound implications, ranging from its disruptive potential to its ethical complexities, and the societal imperatives it underscores. Delving into the evolution of AI technologies, from foundational concepts to cutting-edge innovations, the abstract elucidates their growing significance across diverse sectors including healthcare, finance, transportation, and beyond. However, amidst the promises of efficiency and innovation, ethical concerns loom large. The abstract navigates through the ethical intricacies of AI, addressing issues of bias, accountability, and the erosion of privacy. Furthermore, it ventures into the societal ramifications of AI adoption, exploring its impact on employment dynamics, socioeconomic disparities, and the fabric of human interaction. By interrogating the dual narratives of promise and peril, this abstract offers a holistic understanding of AI's role in shaping the future of society. It underscores the imperative for thoughtful governance, ethical stewardship, and inclusive decision-making to ensure that AI serves as a force for collective progress rather than exacerbating existing divides. Through its interdisciplinary lens, this abstract serves as a roadmap for stakeholders across academia, industry, and policymaking to navigate the complex terrain of AI's integration into society, ultimately paving the way for a future where AI augments human capabilities while upholding fundamental values of fairness, equity, and justice. © 2024 IEEE.

关键词： Decision making

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Research and Development of Recycling Boats for Floating Garbage 3

Research and Development of Recycling Boats for Floating Gar...

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3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Ruixi, Ci Haoming, Cui Kexin, Liu Xintong, Liu Qiao, Xu Jinhan, Yan Beijing University of Technology Fan Gongxiu Honors College Beijing China Faculty of Information Technology Bjut Beijing China

ISBN: (纸本)9781665490788

In recent years, the problems of water garbage pollution and water bloom pollution have been widely concerned and discussed. On the one hand, due to the development of industrial activities in recent years, the discharge of garbage in the water body is increasing, which has seriously affected the water ecology. On the other hand, the pollution of water bloom in China is serious, which affects the maintenance of ecological environment and the development of freshwater aquaculture. At present, the equipment and technology for water garbage cleaning in China are still incomplete. In view of the critical situation of environmental pollution and the defects in the existing technology, the team designed and made a new type of water robot, which provides a new type of water surface garbage cleaning and water bloom management robot, which integrates identification, collection and transportation of garbage, and has many functions such as water bloom management and water quality detection. It provides an effective solution to the problem of water quality resources. © 2023 IEEE.

关键词： robots

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