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IoT-Based Water Quality Monitoring and Detection System 1

2nd International Conference on Emerging Trends in Expert Applications and Security, ICETEAS 2023

作者： Kanchana, M. Gopirajan, P.V. Sureshkumar, K. Sudharsanan, R. Suganthi, N. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Campus Chennai603203 India Department of Information Technology Saveetha Engineering College Chennai602105 India Department of Information Technology SRM Institute of Science and Technology Ramapuram Chennai600089 India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai600089 India

ISBN: (数字)9789819919093

ISBN: (纸本)9789819919086

This paper suggests Internet of things (IoT) and Arduino-based tele-water quality monitoring systems integrated with the web application. The most critical component of the Wireless Sensor Network includes a microcontroller for processing the circuit's sensor data, a communication system between and within node communication, and a few other sensors such as pH, Microbial Fuel Cell (MFC), humidity, and temperature. All data is collected at the Arduino (data which is sensed by the sensors) by using remote monitoring and Internet of things technology (ESP8622MOD). The real-time data is transmitted, and that data is displayed by sending through the cloud in a human interface format on a server device (pc/mobile) by the web or mobile applications. The main objective is to get a water monitoring system with high mobility (the ability to check water more freely, the ability to check wherever required), high frequency, and low power (as it is compatible, we can take and check quickly). Therefore, our main objective is that our system will immensely help people with small water reservoirs, water mines, and villagers/ framers with fields to become conscious/aware of polluted water and stop contaminating the water. The deciding parameters of water, whether toxic or drinkable, are decided by the potential level of hydrogen value. If the hydrogen value is less than five, it is acidic, and if the hydrogen value is above 7.5, then it is primary. The MFC sensor, if the analogy sensor, senses any electricity from the cathode and anode ends (0–200 indicates acidic water, 200–300 is normal water, and above 300 is essential to water);by this water, we decide whether water toxic in nature and temperature and humidity also plays a role in determining the quality, it can result in an effect on the level of O2. Also, the capacity of organisms to resist certain pollutants, so different conditions should have different water temperatures. © 2023, The Author(s), under exclusive license to Spr

关键词： Internet of things

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Towards Precision Agriculture: Harnessing Deep Learning for Accurate Plant Disease Diagnosis

Towards Precision Agriculture: Harnessing Deep Learning for ...

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2024 International Conference on Communication, computing and Internet of Things, IC3IoT 2024

作者： Senthil Pandi, S. Reshmy, A.K. Vinodh Kumar, S. Kumar, P. Rajalakshmi Engineering College Department of CSE Chennai India Srm Institute Of Science And Technology School Of Computing Department Of Cintel Kattankulathur Chennai India

ISBN: (纸本)9798350352689

To a large extent, food plants are responsible for satisfying the dietary requirements of the world's population. Nevertheless, the danger posed by plant illnesses and diseases is significant, despite the fact that diagnoses are frequently based on the symptoms that may be observed. Studies are currently being conducted to investigate novel ways with the interest of developing more efficient strategies for protecting plants. Recent developments in technology have resulted in the creation of more convenient alternatives to the labor-intensive procedures that have been used in the past. The application of deep learning techniques, which are particularly useful in solving picture categorization issues, has emerged as a potentially fruitful route. The attention-based few-shot learning technique was utilized in this research project to accurately diagnose plant illnesses based on photographs of leaves. The photos were then classified into two distinct groups: healthy and sick. After being trained on a database that contains images of plant leaves, the suggested network model exhibits an impressively high level of accuracy, which is 95.96%. © 2024 IEEE.

关键词： Diagnosis

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A Hand Gesture-Operated System for Rehabilitation Using an End-to-End Detection Framework

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第2期5卷 698-708页

作者： Dutta, H Pallab Jyoti Bhuyan, M.K. Neog, Debanga Raj Macdorman, Karl F. Laskar, R.H. Department of Electronics and Electrical Engineering Indian Institute of Technology Assam Guwahati781039 India Department of Electronics and Electrical Engineering and Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Assam Guwahati781039 India Mehta Family School of Data Science and Artificial Intelligence Indian Institute ofTechnology Assam Guwahati781039 India School of Informatics and Computing Indiana University IN46202 United States Department of Electronics and Communication Engineering National Institute of Technology Assam Silchar788010 India

In this article, we propose a hand gesture-operated system as an AI application to relieve discomfort and restore function in hand and arm movements caused by injuries and nerve and muscle complications. The system trains patients with hand exercises, such as performing hand gestures accurately, traversing within specified bounds, and operating a hand gesture calculator. However, the system requires accurate hand gesture detection, which is impeded by background clutter and variations in illumination and in the hand's size and angle. To address this, we developed a robust hand detection module that uses a single-stage transformer deep network. The transformer network encodes global information and uses bipartite matching to reduce the frequency of spurious detections. It drives a regression head and a classification head to localize the hand gesture in a bounding box and assign it a class label. Hand keypoints are also detected to support drawing, path traversal, and calculator use. The approach is evaluated on two benchmark datasets: 1) OUHANDS and 2) NUS. The method yields 89.6% accuracy for OUHANDS and 100% for NUS. These results indicate that precise hand detection can support a robust system for rehabilitation through hand exercises. Our experiments confirm that the users' hand function progressively improved. © 2023 IEEE.

关键词： Deep neural networks

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Self-Aware Fog Layer toward Scalable Resource Allocation and Dynamic Queuing 5

Self-Aware Fog Layer toward Scalable Resource Allocation and...

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5th International Conference on Emerging Smart computing and Informatics, ESCI 2023

作者： Kalingarani, G. Selvaraj, P. Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamilnadu Kattankulathur603203 India

ISBN: (纸本)9781665475242

The Internet is overwhelmed with innovative IoT -assisted devices. It is predicted that the number of online-connected devices will be more than 50 billion in 2030. Such IoT devices would need support from enabling technologies to consume less memory and lower the computation cost. The cloud-based services might further increase point-to-point latency. The unprecedentedly high volumes of real-time data generated by IoT devices may suffer from this delay issue. This work proposes a novel cognitive Fog computing-based data processing approach that manages the data influx caused by the sensor devices at the edge router. The proposed cognitive Fog based architecture has empowered edge devices, with the features such as Location awareness, low latency, portability, proximity to end users, diversity, and real-time response. A scalable resource allocation with a dynamic queuing technique was proposed. The simulation results have shown that the proposed architecture boosts the performance of the IoT Fog-based applications more than the existing approaches. © 2023 IEEE.

关键词： Internet of things

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Deep learning:Applications,architectures,models,tools,and frameworks:A comprehensive survey

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 581-606页

作者： Mehdi Gheisari Fereshteh Ebrahimzadeh Mohamadtaghi Rahimi Mahdieh Moazzamigodarzi Yang Liu Pijush Kanti Dutta Pramanik Mohammad Ali Heravi Abolfazl Mehbodniya Mustafa Ghaderzadeh Mohammad Reza Feylizadeh Saeed Kosari School of Computer Science and Technology Harbin Institute of Technology(Shenzhen)ShenzhenChina Department of Cognitive Computing Institute of Computer Science and EngineeringSaveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennaiIndia Department of Computer Science Islamic Azad UniversityTehranIran Computer Engineering Department Bu‐Ali Sina UniversityHamedanIran Department of Mathematics and Statistics Iran University of Science and TechnologyTehranIran Department of Mathematics and Statistics University of Northern British ColumbiaBCCanada Peng Cheng Laboratory ShenzhenChina Deprtment of Technology Jodhpur Institute of Engineering&TechnologyJodhpurIndia Department of Computer Engineering Sadjad University of TechnologyMashhadIran Department of Electronics and Communications Engineering Kuwait College of Science and TechnologyDoha DistrictKuwait Department of Artificial Intelligence Smart University of Medical SciencesTehranIran Department of Industrial Engineering Shiraz BranchIslamic Azad UniversityShirazIran Institute of Computing Science and Technology Guangzhou UniversityGuangzhouChina

Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new *** using DL,the extraction of advanced data representations and knowledge can be made *** effective DL techniques help to find more hidden *** learning has a promising future due to its great performance and *** need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively.A survey on DL ways,advantages,drawbacks,architectures,and methods to have a straightforward and clear understanding of it from different views is explained in the ***,the existing related methods are compared with each other,and the application of DL is described in some applications,such as medical image analysis,handwriting recognition,and so on.

关键词： data mining data privacy deep learning

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Customisable sound absorption properties of functionally graded metallic foams

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Journal of Materials science & Technology 2022年第13期108卷 196-207页

作者： Jun Wei Chua Xinwei Li Tao Li Beng Wah Chua Xiang Yu Wei Zhai Department of Mechanical Engineering National University of Singapore117575Singapore Agency for Science Technology and Research(A^(*)STAR)Singapore Institute of Manufacturing Technology138634Singapore Agency for Science Technology and Research(A^(*)STAR)Engineering MechanicsInstitute of High-Performance Computing1 Fusionopolis Way138632Singapore

In this study,functionally graded foam made of Inconel 625 superalloy was successfully produced using the template replication method,with open-cell polyurethane foams as a *** products have a similar pore morphology as the templates and adjacent layers were successfully sintered together by particle *** absorption experiments on graded metallic foams reveal that the sound absorption at particular frequency ranges can be improved by various permutations of foam *** graded foam of two distinct pore sizes,a mathematical equation was proposed to predict the location of the intersection point of the sound absorption curves,thereby aiding in graded foam *** increase in sound absorption coefficients by resonance-like effects can be introduced before the intersection points by placing the foam layer of smaller pore size nearer to the sound *** sound absorption performances can be further customized when the thickness proportion of the pore sizes is changed and when the number of distinct pore sizes used is *** sound absorption performance at lower frequencies is generally boosted by resonance-like effects when the layer of foam with the largest pore size is placed furthest from the sound *** the same composition of foam with a fixed thickness proportion of pore sizes,one can introduce resonance-like effects to improve the sound absorption performance compared to other permutations while possibly satisfying weight requirements in practical *** study provides valuable insights and mathematical guidelines in the design and manufacturing of functionally graded metallic foam for specific applications.

关键词： Template replication method Functionally graded foam Sound absorption Transfer matrix method Composite metal foam

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Advancing Multilingual Communication NLP based Translational Speech to Speech Dialogue System for Indian Languages 1

Advancing Multilingual Communication NLP based Translational...

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1st IEEE International Conference on Electronics, computing, Communication and Control Technology, ICECCC 2024

作者： Agarwal, Umansh Gupta, Rishika Saranya, G. School of Computing College of Engineering and Technology SRM Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur Chennai603203 India

ISBN: (纸本)9798350371802

Today it is more crucial than ever to remove language barriers in the linked world of today. This study compares and contrasts on-demand live translation services with an emphasis on effectiveness and accuracy. It presents a workable approach to smooth multilingual communication, with a focus on Indian languages. A state-of-the-art on-call speech translation system built on a sentence-level Neural Machine Translation (NMT) model is revealed in this work. The NMT approach translates individual sentences, as opposed to previous algorithms that work with full documents, guaranteeing accuracy and context awareness. NMT, BERT, and XL Net are also compared, emphasizing their unique qualities and areas of use. To facilitate easy communication in chosen languages, this model supports Hindi, Tamil, Telugu, Malayalam, Urdu, Bengali, and English. This helps address the linguistic variety of India. Its versatility and efficacy are a result of intensive training on a wide range of language pairings, highlighting the contribution of technology to intercultural communication. The study emphasizes how the NMT-based on-call voice translation system improves commu-nication accessibility in our multicultural, globalized society by bridging linguistic gaps, particularly in Indian languages. In addition, a unique application of multithreading has been employed to lower latency by concurrently executing the transcription and translation operations. Research shows that when multithreading is used, the time required for a translation decreases to 93.82 seconds from an initial 137 seconds. This helps to some extent with the latency issue © 2024 IEEE.

关键词： Neural machine translation

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MLSTM: A Novel Modified Long Short-Term Memory Networks for Melody Synthesis Melody Generation

MLSTM: A Novel Modified Long Short-Term Memory Networks for ...

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International Conference on Advanced Communications and Machine Intelligence, MICA 2023

作者： Ganguly, Tanudeep Sharma, Sushmita Deb, Suman Ezugwu, Absalom El-Shamir Saha, Apu Kumar Department of Computer Science and Engineering National Institute of Technology Agartala Tripura Agartala India Department of Computer Science and Engineering Indian Institute of Information Technology Agartala Tripura Agartala India Unit for Data Science and Computing North-West University Potchefstroom2520 South Africa

ISBN: (纸本)9789819762217

This research elaborates a melody synthesis model utilizing a Modified Long Short-Term Memory (mLSTM) neural network, trained on Kern dataset, preprocessed into Musical Instrument Digital Interface (MIDI) files. After receiving a seed melody as input 01, the model predicts the note that will come next by looking at the notes that have come before it. The model can learn the structures and patterns seen in classical music by using MIDI files as the training dataset. Categorical cross-entropy loss function is used to train the model over several epochs with early halting. To regulate how random the predictions are, the model makes use of a temperature parameter. The assessment demonstrates that the produced tunes have a variety of traits and are aesthetically pleasing to human ears. To justify the performance of the proposed method some criteria were considered and expert evaluation was done. The evaluation shows that the model has generated the melodies that are pleasing to the ear and have a similar structure to the training dataset. The model has several uses, including prediction and music composition. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Long short-term memory

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A Study on Word Embeddings in Local LLM-based Chatbot Applications

A Study on Word Embeddings in Local LLM-based Chatbot Applic...

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2024 International Conference on Innovation and Intelligence for Informatics, computing, and Technologies, 3ICT 2024

作者： Hariprasath, S. Paramarthalingam, Arjun Sundaramurthy, Shanmugam Cirillo, Stefano Department of Computer Science and Engineering University College of Engineering Kakuppam Villupuram India Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Campus Chengalpattu603203 India Department of Computer Science University of Salerno Salerno Italy

ISBN: (纸本)9798331533137

Large Language Models (LLMs) have revolutionized natural language processing, but their deployment often requires substantial computational resources and constant network connectivity. There is a growing need for efficient, locally-runnable LLMs with improved word embeddings for various applications, including chatbots. This study focuses on developing a Large Language Model (LLM) capable of running locally without network connections to generate solutions for given queries using improved word embeddings. In this work, two pre-trained models are used and further trained separately to enhance embedding results. The system incorporates additional features such as document-based chat functionality. Our approach develops a dynamic and adaptive NLP system that can assimilate new data from various sources when connected to a network, ensuring up-to-date word embeddings that capture the latest semantic nuances and language trends. The study compares FastText, GloVe, and Word2Vec models, finding that fastText outperforms the others in text generation within the specified time frame. While fastText may require more time to generate larger content, its efficacy in producing better results makes it the preferred choice for this application. ©2024 IEEE.

关键词： Semantics

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Adaptive Control Strategy for PMSM Current Loop Based on Parameter Identification 2

Adaptive Control Strategy for PMSM Current Loop Based on Par...

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2nd International Conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Wei, Yisu Chen, Meng Zhang, Jiarong Shenyang Ligong University School of Information Science and Engineering Shenyang China Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China

ISBN: (纸本)9798350368888

This study explores the importance and impact of current loop controller parameters in permanent magnet synchronous motor control systems. Parameter variations during motor operation, such as changes in temperature and operating current, can directly affect the control performance of the current loop and the overall stability of the system. This underscores the critical role of real-time and accurate motor parameter acquisition in current loop control to enhance controller dynamic performance and system stability. On the other hand, adaptive control methods offer a robust strategy to effectively handle variations in system parameters and external disturbances, demonstrating their value and extensive application potential in practical scenarios. Therefore, conducting research on adaptive control strategies for permanent magnet synchronous motors based on precise system parameters is of practical significance. © 2024 IEEE.

关键词： Permanent magnets

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