2021 International Conference on Industrial Electronics Research and Applications (ICIERA)最新文献

A systematic survey on various energy harvesting systems for WSN applications 系统综述了用于无线传感器网络的各种能量收集系统

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726530

Suman Arora, Geeta Nijhawan, Gourav Verma, Ruchi Patel

引用次数: 1

Analysis of Real Time Video Summarization using Subtitles 基于字幕的实时视频摘要分析

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726769

P. G. Shambharkar, R. Goel

引用次数: 2

Design of First Order Active Low Pass Filter using 22nm Gate All Around Silicon-on-Insulator Schottky Barrier MOSFET 利用22nm栅极全绝缘体硅肖特基势垒MOSFET设计一阶有源低通滤波器

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726717

Anika Saxena, M. Kumar, R.K. Sharma, R. Gupta

引用次数: 1

Design of a Hybrid Renewable Energy Operated Commercial Establishment 混合可再生能源运营商业设施的设计

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726744

Nikhil Dubey, Sakshi Dawar, Preyansh Jain, Anant Kumar, Ravi Sharma

{"title":"Design of a Hybrid Renewable Energy Operated Commercial Establishment","authors":"Nikhil Dubey, Sakshi Dawar, Preyansh Jain, Anant Kumar, Ravi Sharma","doi":"10.1109/ICIERA53202.2021.9726744","DOIUrl":"https://doi.org/10.1109/ICIERA53202.2021.9726744","url":null,"abstract":"Industrial sector is the major contributor in the rapidly increasing energy consumption demand in correlation with increasing technological advances. Grid connected hybrid renewable energy systems (HRESs) are the effective solution for commercial or industrial establishments due to their long-term cost effectiveness, elimination of grid supply dependability and decreased Environmental impact. This paper presents the design of a renewable energy power system with optimized load minimization for a commercial establishment with provision of surplus energy production that can be utilized to claim monetary incentives offered by Net-Metering or for other high-powered applications. The paper considers a typical office in New Delhi, India to develop a techno-economic profile. The proposed model is novel in its combination and coordination of multiple generation systems, i.e., Photovoltaic (PV) panels, Semi-Transparent Solar System, Wind energy conversion system (WECS), Battery energy storage system (BESS) in conjunction with load minimization using HVAC and innovative IoT application. HOMER (Hybrid Optimization Model for Electric Renewable) was used in combination with MATLAB/Simulink for economic analysis, size optimization, technical evaluation, and simulation of the model.","PeriodicalId":220461,"journal":{"name":"2021 International Conference on Industrial Electronics Research and Applications (ICIERA)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121620047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A three-stage CMOS operational amplifier with high gain and phase margin 具有高增益和相位裕度的三级CMOS运算放大器

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726738

P. Chandra, Urvashi Bansal

引用次数: 2

Development of Modified AC Bridge Network for Accurate Measurement of Passive Parameter of a Temperature Sensor 用于温度传感器无源参数精确测量的改进交流桥网的研制

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726741

M. Bandyopadhyay, S. Chattopadhyay, N. Mandal

{"title":"Development of Modified AC Bridge Network for Accurate Measurement of Passive Parameter of a Temperature Sensor","authors":"M. Bandyopadhyay, S. Chattopadhyay, N. Mandal","doi":"10.1109/ICIERA53202.2021.9726741","DOIUrl":"https://doi.org/10.1109/ICIERA53202.2021.9726741","url":null,"abstract":"The Resistance Temperature Detector (RTD), acts as a resistive transducer, in which a small resistance changes linearly according to the change of temperature in industry. The inferential technique of temperature measurement by resistance temperature detector needs bridge circuit to measure the temperature in terms of resistance. But the effect of stray capacitances generally produce errors in measurement using bridge network. Wagner-earth technique is very useful to eliminate these errors but this method is suitable for intermittent measurement and not acceptable for direct as well as continuous measurement. In this paper, an AC Wheatstone bridge circuit has been modified by operational amplifiers, so that stray capacitances are assumed to be minimised and with the additional linear potentiometer which provides the variable sensitivity in the bridge measurement. For a constant and selected value of bridge sensitivity potentiometer, the change of resistance with the change of temperature has been observed and found satisfactory with respect to good accuracy, linearity and repeatability. A comparative study of this technique with the laboratory standard instrument has also been reported in this paper.","PeriodicalId":220461,"journal":{"name":"2021 International Conference on Industrial Electronics Research and Applications (ICIERA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130882227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mental Stress Assessment using Wavelet Transform Features of Electrocardiogram Signals 基于心电信号小波变换特征的心理压力评估

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726532

S. Saini, Rashmi Gupta

{"title":"Mental Stress Assessment using Wavelet Transform Features of Electrocardiogram Signals","authors":"S. Saini, Rashmi Gupta","doi":"10.1109/ICIERA53202.2021.9726532","DOIUrl":"https://doi.org/10.1109/ICIERA53202.2021.9726532","url":null,"abstract":"Mental stress is an unavoidable part of our daily life now-a days and its presence in long term causes adverse affects on mental and physical health of person. In the presence of a stress event, there is an unbalance in activities of autonomic nervous system (ANS) that further results in a irregular heart function. The variations in resulting heart function in the presence of mental stress can be measured as bioelectric signals using electrocardiogram (ECG) and its temporal and morphological features used as a significant marker of stress. In this work, we used discrete wavelet decomposition to extract frequency components of ECG signal and calculated standard deviation (SD), entropy, and total energy for selected frequency components significant to the variations caused by stress events. The feature set is formed using calculated parameters and a multiclass logistic regression (MLR) model is trained to classify the mental stress in three different levels. The proposed method is validated with classification accuracy = 90.8% using Physionet data base containing ECG recording under different stress events. The presented work demonstrates the use of ECG signal as a significant marker for automatic assessment of mental stress.","PeriodicalId":220461,"journal":{"name":"2021 International Conference on Industrial Electronics Research and Applications (ICIERA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127854425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comprehensive Study of Various Bypass Switches and Their Applications on PV Array for Hotspot Reduction 各种旁路开关及其在光伏阵列上减热点应用的综合研究

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726757

A. Verma, Diwaker Pathak, P. Gaur

引用次数: 0

High gain Self-diplexing SIW leaky wave Antenna 高增益自双工SIW漏波天线

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726735

H. Kumar, Garima Srivastava

引用次数: 0

Energy Anomaly Detection and Modelling on Smart Premises using SDAR 基于SDAR的智能住宅能量异常检测与建模

2021 International Conference on Industrial Electronics Research and Applications (ICIERA) Pub Date : 2021-12-22 DOI: 10.1109/ICIERA53202.2021.9726730

Sachin Gupta, Bhoomi Gupta

{"title":"Energy Anomaly Detection and Modelling on Smart Premises using SDAR","authors":"Sachin Gupta, Bhoomi Gupta","doi":"10.1109/ICIERA53202.2021.9726730","DOIUrl":"https://doi.org/10.1109/ICIERA53202.2021.9726730","url":null,"abstract":"Energy as a commodity is facing a globally prevalent shortage with the ever increasing gap between the demand and supply. The strain on the non-renewable conventional energy resources is evident from the multitude of industries in the manufacturing hubs of China that have come to standstill in the face of non-availability of coal. The phenomenon is particularly acute in all developing countries with an unbalanced approach to the energy management vis-a-vis distribution losses. The Internet of Things (IoT) ecosystem enabled smart homes and industrial premises have shown promising application towards achieving energy efficiency via creation of dynamically adjusting demand based systems. It is possible to predict the energy consumption requirements based on application of Machine Learning (ML) based models on statistical data obtained from energy sensors. The data streams from IoT devices however, more often than not throw up surprises in the form of outliers and changes which can affect the Machine learning based time series forecasting. The problem is more accentuated in the case of non-stationary time series sources where it is imperative to ascertain whether an anomaly is momentarily affecting the time series as an outlier or it is a permanent change never returning to the original trend. This paper uses a sequentially discounting auto regression (SDAR) learning algorithm to detect and classify the anomalies in energy consumption usage for model accuracy. Specifically, we have applied the online SDAR algorithm on energy consumption IoT dataset from kaggle as a demonstration to distinguish between outliers and permanent changes over the time series which can be used for interpretability and increasing model accuracy while prediction of energy consumption. We were able to forecast sudden changes in the energy consumption requirements well in advance, based on the previous years' usage patterns as the results indicate.","PeriodicalId":220461,"journal":{"name":"2021 International Conference on Industrial Electronics Research and Applications (ICIERA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125076194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1