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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

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Automated Biofloc Technology for Fish Farming with GSM based Monitoring System

Automated Biofloc Technology for Fish Farming with GSM based...

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Robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 ieee international conference on

作者： Md Mehedi Hassain Muhammad Osman Gani Abdur Rahman S. M. Rahbar Abdullah Hasnat Dept. of Electrical & Electronics Engineering International Islamic University Chittagong Chittagong Bangladesh Dept. of Electrical & Electronics Engineering East Delta University Chittagong Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

Biofloc technology mitigates aquaculture’s environmental impact by using microbial flocs to convert organic waste into nutrient rich feed. To enhance water quality management, our research focuses on a GSM based monitoring system for real time data collection and analysis. The system integrates pH, temperature, and ultrasonic sensors with an Arduino Uno microcontroller, GSM module, servo, and pump motors to monitor and regulate water quality. The system measures timely and crucial data on water quality, including parameters such as temperature, pH levels, and the state of the feeding box. The pH and temperature sensors provide analog readings, while the ultrasonic sensor monitors feeding box levels. Food management is controlled by a servo motor that operates the feeding box, and a pump motor maintains water quality. The system uses temperature and pH sensors for rapid hazard detection, minimizing ammonia and nitrite buildup risks. The GSM module enables real time data connectivity, allowing users to track and control system operations remotely. This study empowers fish farmers and hobbyists with real-time water quality data, promoting informed decision-making to enhance aquatic health and productivity. It offers valuable insights to the broader aquaculture community.

关键词： Temperature sensors GSM Temperature measurement Water quality Fish Real-time systems Acoustics sensors Servomotors Aquaculture

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Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality

Unmasking Data Secrets: An Empirical Investigation into Data...

引用

AI Engineering - Software Engineering for AI (WAIN), ieee/ACM Workshop on

作者： Gilberto Recupito Raimondo Rapacciuolo Dario Di Nucci Fabio Palomba Sesa Lab - University of Salerno Salerno Italy University of Salerno Salerno Italy

ISBN: (数字)9798400705915

ISBN: (纸本)9798350352191

Artificial Intelligence (AI) is rapidly advancing with a data-centered approach suitable for various domains. Nevertheless, AI faces significant challenges, particularly in data quality. Data collection from diverse sources can introduce quality issues that may threaten the development of AI-enabled systems. A growing concern in this context is the emergence of data smells –issues specific to the data used in building AI models, which can have long-term consequences. In this paper, we aim at enlarging the current body of knowledge on data smells, by proposing a two-step investigation into the matter. First, we updated an existing literature review in an effort of cataloguing the currently existing data smells and the tools to detect them. Afterward, we assess the prevalence of data smells and their correlation with data quality metrics. We identify a novel set composed of 12 data smells distributed across three additional categories. Secondly, we observe that the correlation between data smells and data quality is notably impactful, exhibiting a pronounced and substantial effect, especially in highly diffused data smell instances. This research sheds light on the complex relationship between data smells and data quality, providing valuable insights into the challenges of maintaining AI-enabled *** CONCEPTS• Software and its engineering → Software maintenance tools.

关键词： Measurement Software maintenance Correlation Data integrity Taxonomy distributed databases Reliability

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Online reduced-order kernel regression for data processing in sensor network 3

Online reduced-order kernel regression for data processing i...

引用

3rd ieee international conference on Data Stream Mining and Processing, DSMP 2020

作者： Lyubchyk, Leonid Kostiuk, Olga National Technical University Kharkiv Polytechnic Institute Computer Mathematics and Data Analysis Dept Kharkiv Ukraine

ISBN: (纸本)9781728132143

Online data processing in sensor networks problem is of particular relevance in connection with the widespread use of such systems for restoring physical fields from local measurements, for example, in environmental monitoring systems. In order to reduce model dimensionality, clustering of sensors net is carried out previously. In this paper, we consider the problem of restore fields of complex structure using data from sensor network. Nonlinear distributed regression kernel-based method is applied using sequential regularization based on optimal estimates concordance. A generalization of this approach to non-stationary case is also considered, for which recurrent regularized kernel-based learning algorithms are proposed, using both moving average and sliding window approaches. © 2020 ieee.

关键词： E-learning

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Hardware Design of Integrated Platform of Optical Fiber sensor Based on Temperature Distribution 3

Hardware Design of Integrated Platform of Optical Fiber Sens...

引用

3rd ieee international conference on Information systems and Computer Aided Education, ICISCAE 2020

作者： Jun, Lu Cheng, Yuansheng Wuhan Donghu University Wuhan China Middle Changjiang River Bureau of Hydrology and Water Resources Survry Wuhan China

ISBN: (纸本)9781728183039

The distributed fiber sensing technology can calculate the temperature and strain distribution on the fiber by detecting the scattered light intensity along each position of the fiber. Brillouin optical time domain analyzer is a distributed optical fiber sensing technology, which is suitable for long distance, large range and high sensitivity distributed optical fiber sensing system, and can achieve accurate real-time measurement of temperature and strain on the optical fiber. It has important research significance and practical value. In this paper, brillouin scattering effect and BOTDA sensing principle in optical fiber are studied. Based on the signal characteristics of BOTDA sensing system, a distributed optical fiber sensing system test platform is designed. © 2020 ieee.

关键词： Optical fibers

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Optimal Coordination of Overcurrent Relay Using Rao-1 Algorithm 3

Optimal Coordination of Overcurrent Relay Using Rao-1 Algori...

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3rd international conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2021

作者： Batool, Samia Ahmad, Sadiq Shoukat, Abdullah Mobeen, Faiza COMSATS University Islamabad Department of Electrical and Computer Engineering Wah Cantonment Pakistan

ISBN: (纸本)9781665416412

The main objective of protection schemes in power system is to identify and remove the faulty part as quickly as possible. Coordinating the distribution systems, which are frequently protected with overcurrent (OC) relays is extremely difficult. Modern power systems use variety of distributed generators (DG) to make the operation of the system reliable, but the coordination of OC relays is a huge challenge for design protection engineers in these DG integrated distribution systems. This paper puts forward a method to develop a mechanism for coordination of over current OC relays in the distribution networks that is optimal, efficient, and accurate. The Rao-I, a metaphor-less optimization technique is used and compared with particle swarm optimization algorithm (PSO) in terms of convergence and accuracy. When DG is penetrated, a proper coordination of primary and backup relay is chosen to avoid relay malfunctions and unwanted outages. Finally, the Rao-1 Algorithm produced substantially more precise values resulting in a faster convergence time and more optimal coordination time. © 2021 ieee.

关键词： distributed power generation

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Artificial Intelligence sensor for “Big Five” Personality Analysis

Artificial Intelligence Sensor for “Big Five” Personality ...

引用

international conference on Micro/Nano sensors for AI, Healthcare, and Robotics (NSENS)

作者： Qiaojiao Wang Jiahui Lin Xiaodong Yu Xiaomeng Yang Dannii Yuen-Lan Yeung Wen Jung Li Department of Mechanical Engineering City University of Hong Kong Hong Kong China Department of Social and Behavioural Sciences City University of Hong Kong Hong Kong China

ISBN: (数字)9798350375213

ISBN: (纸本)9798350375220

Behavior measurement has played a significant role in research within the field of personality psychology, providing objective and quantifiable data that helps us gain deeper insights into individuals’ behavioral characteristics and psychological states. However, assessing personality through gait analysis remains a significant challenge. In this study, we developed a dynamic monitoring system for gait parameter analysis. The inertial measurement unit embedded in the system consists of a three-axis accelerometer and a three-axis rotation-rate gyroscope. The sensor was placed on the participants’ ankle to investigate the relationship between walking gait and personality. Foot motion data, including acceleration and angular velocity, was collected during the natural walking process. Additionally, with the 60-item Big Five Inventory-2 (BFI-2), participants’ personality traits were assessed. Classifiers with different learning algorithms were used to examine the relationship between foot motion features and various personality traits. The results showed that the Random Forest (RF) algorithm performed best in classifying the five dimensions of personality, and the accuracy for the agreeableness dimension reached an impressive 89.66%. This research provides a new tool for objective and in-depth understanding of personality through artificial intelligence sensors.

关键词： Legged locomotion Radio frequency Psychology Medical services Robot sensing systems Classification algorithms Artificial intelligence

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Efficient energy smart sensor for fall detection based on accelerometer data and CNN model

Efficient energy smart sensor for fall detection based on ac...

引用

international conference on Embedded & distributed systems (EDiS)

作者： Brahim Achour Idir Filali Malika Belkadi Mourad Laghrouche LARI Laboratory University of Tizi Ouzou Algeria LAMPA Laboratory University of Tizi Ouzou Algeria

ISBN: (数字)9798350397543

ISBN: (纸本)9798350397550

Fall detection helps to provide medical assistance quickly and to avoid the aggravation of injuries. In this paper, we propose a new noninvasive and energy-efficient smart sensor for fall detection. The sensor is based on accelerometer data and is attached to 20 building workers. To reduce power consumption, a new method of data selection is proposed. This method is based on the use of sensor timers, which allows for the reduction of 91% of the acquired data and 94% of the transmitted data. Regarding the classification, a new classification approach is proposed. Indeed, each data segment is displayed as a graph. Then, a convolution neural network is trained to detect the presence or absence of falls in each graph. An accuracy of 98% was obtained. This result exceeds that obtained in several studies and shows the effectiveness of the proposed approach.

关键词： Accelerometers Energy consumption Power demand Neural networks Energy efficiency Data models Convolutional neural networks

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Electromyogram Based Bot-assistive Device for Paralyzed People

Electromyogram Based Bot-assistive Device for Paralyzed Peop...

引用

3rd ieee international conference on Emerging Smart computing and Informatics (ieee-ESCI)

作者： Stanley, P. Kingston Sonavane, Amit Kumar K. David, Shibin Anand, R. S. Sagayam, K. Martin Daniel, P. Vijay Elngar, Ahmed A. Karunya Inst Technol & Sci Dept Robot Engn Coimbatore Tamil Nadu India Grocery Outlet Inc Emeryville CA USA Karunya Inst Technol & Sci Dept Comp Sci Coimbatore Tamil Nadu India Karunya Inst Technol & Sci Dept Mech Engn Coimbatore Tamil Nadu India Karunya Inst Technol & Sci Dept Elect & Commun Engn Coimbatore Tamil Nadu India Karunya Inst Technol & Sci Dept Biomed Engn Coimbatore Tamil Nadu India Beni Suef Univ Fac Comp & Artificial Intelligence Bani Suwayf 62511 Egypt

ISBN: (纸本)9781728185194

Electromyogram based wheelchair (EBW) is considered as the best module for the handicapped and paralyzed people in the medical arena. In the developing countries, the people are not even aware of such kind of innovations in the field of wheelchairs. This is due to the cost and complexity in the technological part of the equipment. During the preparation of such biomedical equipment, the designer cannot neglect the inculcation of the basic components such as the strength of the material through which the product is going to be designed. However, the need of EMG based wheelchair is basically useful for paralyzed people. Those people have to face difficulty in suffering pain until the end of their life. Further, the drawback in such system is its cost and availability even in the remote and for the middle class people. Hence, this device provides the paralyzed people an easy way of accessing the wheelchair by using their muscles in their own way. The modified device works in the fashion where the user can move the wheelchair by their own muscle movements. This article reports the ease of use in the wheelchair with comfortable muscular movements.

关键词： Assistive Bot EMG sensor Paralyzed people Embedded Processor

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Remote sensor Networks for Chilli Crop Disease Prediction Using Thermal Image Processing Techniques 3

Remote Sensor Networks for Chilli Crop Disease Prediction Us...

引用

3rd international conference on Communication systems, computing and IT Applications, CSCITA 2020

作者： Syed, Shafaque Fatma Varghese, Ditty Tripathy, Amiya Kumar Don Bosco Institute of Technology Department of Computer Engineering Mumbai India

ISBN: (纸本)9781728123394

Chilli is one of the most important crops to the Indian economy as India is the largest producer and exporter of chilli, so it is essential that the crop is grown in a healthy and suitable environment. As chilli crops are highly susceptible to infection by pests, fungi or bacteria and any changes in the environmental conditions have an adverse effect on the crop, a methodology needs to be devised so as to monitor the growth of the plant and ensure proper growth conditions. This paper discusses a methodology that focuses on monitoring the stress level of the plant as a primary way of identifying if the plant is at a risk of a disease or not. Using image processing and a wireless sensor network, the crop is monitored and sensor values of various climatic conditions are generated. A machine learning algorithm takes these sensor values as input and predicts if the crop is healthy or not, which will help the farmer make effective decisions so as to increase the yield of the crop. © 2020 ieee.

关键词： Crops

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Concentration Detection of Continuous-Flow Magnetic Nanoparticles Using Giant Magnetoresistance sensor 3

Concentration Detection of Continuous-Flow Magnetic Nanopart...

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3rd international Symposium on Material and Electrical Engineering conference, ISMEE 2021

作者： Xuan, Manh Vu Ngoc, Thao Pham Quoc, Tuan Vu Minh, Hieu Nguyen Hoang, Nam Nguyen Quang, Loc Do Duc, Trinh Chu Thanh, Tung Bui National Center for Technological Progress Ministry of Science and Technology Center for Microelectronics and Information Technology Hanoi Viet Nam Vnu University of Engineering and Technology Hanoi Faculty of Electronics and Telecommunications Hanoi Viet Nam Institute of Physics Vietnam Academy of Science and Technology Hanoi Viet Nam Vnu University of Science Vietnam National University Nano and Energy Center Hanoi Viet Nam Vnu University of Science Vietnam National University The Faculty of Physics Hanoi Viet Nam

ISBN: (纸本)9781665423625

Giant magnetoresistance (GMR) sensors offer great sensitivity and integration capabilities on devices, especially microfluidic systems. This approach allows fast identification and real-time analysis of the detection of the biomolecules conjugated with the magnetic nanoparticles (MNPs), which are essential requirements for biomedical applications. This study integrated the GMR sensor with microchannel and signal processing circuits to determine MNPs concentration in a continuous flow using Helmholtz magnetic field source. The most significant advantage of this technique consists of modifying and integrating the GMR sensor to enhance the output signal and the system's sensitivity at a shallow concentration of MNPs. The high sensitivity was experimentally determined as 3.018V/(***-1) with a low detection limit (LOD) of about 19 μ***-1. This proposed system is appropriate to integrate into point-of-care microfluidic devices to detect biomolecule concentrations in real-time diagnostics. © 2021 ieee.

关键词： Microchannels

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