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Gas Discrimination & Quantification using sensor Array with 3D Convolution Regression Dual Network 11

Gas Discrimination & Quantification using Sensor Array with ...

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and applications (IDAACS)

作者： Pareek, Vishakha Chaudhury, Santanu Singh, Sanjay CSIR Cent Elect Engn Res Inst Pilani 333031 Rajasthan India Acad Sci & Innovat Res AcSIR Ghaziabad 201002 India Indian Inst Technol Delhi Delhi 110016 India

ISBN: (纸本)9781665426053

Smart sensor system design requires intelligent data processing, which analyzes raw time-series sensor data to efficiently and precisely discriminate and quantify target gases. The work presented here utilizes the response of twin gas sensor arrays for gases such as ethanol, ethylene, methane, and carbon monoxide to discriminate and quantify the target gases. We propose a 3D convolution neural-based regression dual network (3D-CNRDN) for both gas quantification and discrimination. The spatiotemporal correlation of sensor array responses inspired us to design the deep neural network for the gas concentration estimation model. The sensor array set is spatially correlated, and all the twin array responses are temporally related. 3D-CNRDN uses raw time-series gas sensor array data. The data is fed to the network as the 3D pattern, which contains 2D spatial information varying with third dimension time to recognize patterns that eventually predict the concentration. The model evaluation shows that the proposed methods are an effective technique for gas quantification and identification with RMSE = 0.3179 and classification accuracy 94.37%. Furthermore, the proposed method outperforms and provides higher discrimination accuracy and lower RMSE than other machine learning and deep learning methods.

关键词： 3DCNN Gas sensor sensor Array Quantification

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A review on recent techniques developed for energy conservation in Wireless sensor Networks

A review on recent techniques developed for energy conservat...

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International Symposium on advanced Computing and Communication (ISACC)

作者： Habila Basumatary Rajib Chowdhuri Mrinal Kanti Deb Barma Department of Computer Science and Engineering Tezpur University Assam India Department of Computer Science and Engineering National Institute of Technology Agartala India Department of Computer Science and Engineering National Institute of Technology Agartala Agartala India

In modern days, with the fastest growing technology trends, the benefits of Wireless sensor Networks (WSNs) are also increasing rapidly. In these networks, very small-sized wireless sensor nodes are used widely which are capable of sensing and doing computations. These sensor nodes are resource-limited in nature i.e., they have limited storage capacity, power supply, computation capability, bandwidth, etc. WSNs are mostly used in outdoor application areas like environmental monitoring, land mines detections or different military applications where the power supply to the sensor nodes does the major role. In these applications, without any external power supply, the sensor nodes run the whole network by collecting data from its surroundings and also communicate these data to the end-user. Hence, conserving energy for the sensor nodes is one of the most challenging tasks in WSNs. In this paper, we have done detailed study on the existing literature which are proposed with the objective to improve the energy efficiency issue in WSNs. Here, we have selectively highlighted some of the recently proposed methodologies to understand the present research scenario. We have also shown comparative analysis on the techniques and tools which are used to propose these works and their variation of the results are discussed accordingly.

关键词： Wireless communication Wireless sensor networks Power supplies Military computing Routing Energy efficiency Routing protocols

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advanced Low-Power SRAM Design Techniques at 16nm Node: Combining Multi-Threshold Voltage, MOSFET Stacking, and Body Biasing

Advanced Low-Power SRAM Design Techniques at 16nm Node: Comb...

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International conference on Computing and Networking Technology (ICCNT)

作者： Rahul Sharma Prakash Kodali Department of Electronics and Communication Engineering National Institute of Technology Warangal Telangana India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Low power SRAM is indispensable for a multitude of applications, spanning embedded systems, systems-on-chip (SoC), and wireless electronic devices. This paper unveils an advanced 10T SRAM cell optimized with 16nm CMOS technology, meticulously designed to curtail both static and dynamic power consumption. Employing sophisticated techniques such as body biasing, multiple threshold voltages, and MOSFET stacking, this design also incorporates a control signal and a VDD supply of 0.8 volts to maximize power efficiency. The resultant SRAM cell showcases remarkable power savings, rendering it exceptionally suitable for power-sensitive applications. Comprehensive simulations conducted via Cadence tools highlight that this optimized 10T SRAM cell significantly surpasses conventional SRAM designs in power efficiency and performance.

关键词： Wireless communication MOSFET Wireless sensor networks Stacking Noise SRAM cells CMOS technology Threshold voltage Transistors Thermal stability

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WSN for Food Product Quality Control 11

WSN for Food Product Quality Control

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and applications (IDAACS)

作者： Romanov, Volodymyr Galelyuka, Igor Voronenko, Oleksandr Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Prosp Acad Glushkova 40 UA-03187 Kiev Ukraine

ISBN: (纸本)9781665426053

Quality control of food products, including beverages, during the production process is an important task that can be successfully solved by information technology. Currently, quality control of wine, beer, juices and other beverages is carried out using biochemical control, which takes a time and requires the application of complex analytical devices under the control of qualified personnel. The development of information technologies, biosensors, sensor networks makes it possible to solve the problem of quality control of various beverages in express mode. The main contribution of this paper is the design and prototyping of wireless amperometric biosensors and wireless sensor network (WSN) on their base to monitor the concentration of various components in beverages. The WSN architecture was modified for technological process of winemaking. Wireless biosensors were tested with different types of enzymes on different concentration of solutions. Such tests confirm the possibility to use the wireless biosensors on some stages of technological process of winemaking. The upgrading wireless nodes by sensing unit with particular enzymes will allow covering all technological process.

关键词： smart sensor wireless sensor network beverages quality control

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Innovative System for Environmental Monitoring with Connected sensors and Data Analysis for Chemical Pollutants

Innovative System for Environmental Monitoring with Connecte...

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Intelligent systems and advanced applications (ICISAA), International conference on

作者： A Suganya Mahesh A. Suryawanshi Manisha V. Bagal Ruchira Rawat S. Kaliappan G. Manikandan Department of Information Technology Karpagam College of Engineering Coimbatore Tamil Nadu India Department of Chemical Engineering Bharati Vidyapeeth College of Engineering CBD Navi Mumbai India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Division of Research and Development Lovely Professional University Phagwara Punjab India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

The Chemical Pollutants system, which combines sophisticated data processing capabilities with networked sensors to identify and control chemical pollutants, transforms environmental monitoring. It collects real-time data on pollutants using extremely accurate sensors, which are then evaluated using cloud infrastructure and a reliable wireless connection. Predictive insights using machine learning algorithms provide notable improvements: 97% accuracy in sensor data, 3 seconds of data transmission latency, and $\mathbf{99.5\%}$ system uptime. There are now 1200 daily active users, and the prediction model’s accuracy is $\mathbf{92\%}$. Environmentally, it resulted in a 30% decrease in PM2.5 levels, a halving of high pollution alerts to 10 per month, and an 85% increase in public awareness. The number of policy changes tripled to four each year, while community engagement quadrupled to twelve. The results highlight the system’s contribution to improving the timeliness and quality of environmental data, influencing public health and policy, and highlighting its efficacy and potential for wider environmental management use.

关键词： Chemical sensors Accuracy Pollution Pollution control Predictive models sensor systems sensors Pollution measurement Environmental monitoring Chemicals

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Multimodal Wearable Sensing systems based on Higher-Order Parity-Time Symmetry

Multimodal Wearable Sensing Systems based on Higher-Order Pa...

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International conference on Electromagnetics in advanced applications (ICEAA)

作者： Zhilu Ye Minye Yang Mohamed Farhat Pai-Yen Chen University of Illinois at Chicago Chicago IL USA King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Parity-time (PT) symmetry, a salient landmark in the realm of non-Hermitian physics, reveals that non-conservative Hamiltonians upholding both parity (P) and time-reversal (T) operators may present entirely real eigenspectra [1]–[3]. The advent of PT symmetry has facilitated a plethora of applications, ranging from wireless sensor telemetry and power transmission to dynamic wave manipulation and cloaking [1], [2]. In particular, PT-symmetric systems have exhibited formidable efficacy in ultra-sensitive wireless sensing [3]. It has been observed that the eigen frequencies of such a system bifurcate at an exceptional point (EP), where they demonstrate remarkable sensitivity to minuscule perturbations. This phenomenon culminates in superlative sensitivity, considerably outstripping that of traditional $LC$ resonator-based sensors. Nonetheless, despite these appreciable benefits, current $PT -$symmetric systems are limited to the detection of singular resistive or capacitive parameters. These systems fall short in identifying and discerning each parameter when resistive and capacitive variations coexist. This constraint curtails the applicability of $PT -$symmetric systems in certain real-world scenarios. For instance, in wearable biomedical monitoring situations, multiple biomarkers may vary simultaneously, thereby necessitating more multiplexed detection systems.

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An Introductory Approach to Time-Series Data Preparation and Analysis 15

An Introductory Approach to Time-Series Data Preparation and...

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15th Annual conference of the Prognostics and Health Management Society, PHM 2023

作者： Baumann, Edward Buba, Hayley Cox, Taylor Hsu, Charles Trident Systems Inc. FairfaxVA22030 United States

ISBN: (纸本)9781936263059

Machine learning (ML)/Artificial Intelligence (AI) has widespread applications and has revolutionized many industries due to advanced and matured sensor technologies, as well as large-scale data collection efforts. One of the key tasks for effective ML/AI operations is the extraction and identification of useful and usable data to identify complex interrelationships and solve problems efficiently. The usefulness of the data is the value and meaning of the data within the desired model, while the usability of the data refers to the ease of use of data in a model. Complex supervised and unsupervised ML models, which used to be the domain of cutting-edge scientists and academics, can now be invoked as basic function calls in public domain packages within Python, R, MATLAB, and other languages. While these functions require effective data preprocessing to overcome the unpredicted impacts of data quality in the real world (e.g. missing data, environmental noise, synchronizing at different sampling rates, etc.), their ease of use means they are often called with little to no understanding of the underlying math or ways to efficiently work through the data set. The approachability provided by the packages enables users to dive into complex problem sets with little advance preparation. However, in doing so there is a lack of understanding which will inevitably cause problems, skew results, or force the user to take a less efficient path to get to a similar answer. Each package provides relatively simple examples that deal with specific public data sets, yet not many provide the background knowledge and comprehensive methods required for building the inputs for extensive and effective time-series data modeling. Typically, the complex nature of time-series sensor data requires an in-depth understanding of signals analysis and domain subject expertise to use in ML/AI predictive models. This paper will provide the reader an overview of the problems associated with time-series s

关键词： Time series

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Research on Intelligent Early Fire Warning System Using Adaptive Neuro-Fuzzy Inference System in Green Seaport

Research on Intelligent Early Fire Warning System Using Adap...

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Smart systems for applications in Electrical Sciences (ICSSES), International conference on

作者： Thach Nguyen Dinh Hung Nguyen Van Tuan Dinh Anh Faculty of Navigation Vietnam Maritime University Hai Phong Vietnam Faculty of Electrical - Electronics Engineering Vietnam Maritime University Hai Phong Vietnam

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

Transportation and storage in warehouses and seaports are increasingly popular and have increased sharply in recent years. Strict fire and explosion prevention requirements must be met with the diversity of goods, incredibly flammable and explosive goods during transportation. Therefore, fire and explosion monitoring and early warning systems in these areas are increasingly developed with innovative technology and artificial intelligence applied in general alarm systems. This paper proposes and tests an early warning system for fire and explosion at seaports based on advanced fire alarm technology. Traditional addressable fire alarm systems integrating stations for collecting real-time gas concentration quality are being studied. At the same time, an early warning system for fire and explosion is built based on the Adaptive Neuro-Fuzzy Interference System (ANFIS) model and data processing algorithms from fire alarm cabinets. The system results were tested in the laboratory and deployed in practice, reaching 92%, and they strongly supported fire prevention and fighting at smart seaports in Vietnam.

关键词： Adaptive systems Prevention and mitigation Interference Alarm systems Seaports Smart systems Real-time systems sensor systems Artificial intelligence Monitoring

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Computational Analysis of No-Core Fiber sensor for Detecting Aging Traces in Transformer Oil

Computational Analysis of No-Core Fiber Sensor for Detecting...

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advanced Telecommunication and Networking Technologies (ATNT), IEEE International conference on

作者： Nurul Farah Adilla Zaidi Nur Najahatul Huda Saris Muhammad Yusof Mohd Noor Mohd Rashidi Salim Sumiaty Ambran Marinah Othman Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Malaysia Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur Malaysia Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia Negeri Sembilan Malaysia

ISBN: (数字)9798350353501

ISBN: (纸本)9798350353518

The presence of aging traces in transformer oil poses a significant concern for industries heavily dependent on power transformers, as it can potentially lead to breakdowns that disrupt critical business processes. This paper introduces a computational analysis study of a no-core fiber (NCF) sensor for detecting aging traces in transformer oil. Employing the Wave Optics Module in COMSOL Multiphysics 5.5®, the computational analysis study delves into the efficacy of the no-core fiber (NCF) sensor in detecting transformer oil with refractive indices spanning from 1.46 RIU to 1.55 RIU, encompassing the typical aging range of transformer oil. The study explores various parameters, including electric field distribution, mode field diameter, and effective mode index, across a spectrum of refractive index (RI) values. The findings highlight the potential of the sensor for effectively evaluating and analyzing aging traces in transformer oil by observing the RI and electric field intensity changes. This research lays the groundwork for future applications of the sensor in real-time scenarios especially for high-RI implementation conditions, offering a promising avenue for enhancing the reliability and longevity of power transformer systems.

关键词： Optical fiber sensors Electric potential Oils Aging Oil insulation Optical fiber networks Real-time systems Power transformers Indexes Electric fields

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Redefining Biomedical Waste Management Through advanced Smart Bin Technology

Redefining Biomedical Waste Management Through Advanced Smar...

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Soft Computing for Security applications (ICSCSA), International conference on

作者： Rubia Gandhi R R Shanmugapriya M Sridevi G Subramaniam M D. Kavitha M.Siva Ramkumar Sri Ramakrishna Engineering College Coimbatore Tamil Nadu Department of CSE(IoT) SNS College of Engineering Coimbatore India Department of ECE SNS College of Technology Coimbatore India

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515737

Improper biomedical waste management poses significant health and environmental risks. This paper focuses on developing effective strategies to mitigate the contamination associated with medical waste disposal. By addressing the issue of unsafe disposal practices, such as open burning and landfilling, this research study aims to reduce the spread of infectious diseases. The research will explore innovative solutions to safely manage medical waste, contributing to a healthier and cleaner environment.

关键词： Technological innovation Protocols Light emitting diodes sensor systems Real-time systems Safety Security Waste disposal Sustainable development Radiofrequency identification

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