Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972102
Sanai Divadkar, Akshat Sahu, Shalini Puri
The rise of digitalization and technology has substantially expanded the number of people with online news access, resulting in a significant shift in how information is consumed on social channels. The spread of fake news with ambiguity is a critical and harmful aspect of handling online news access. Such news should be identified quickly since it can harm an individual or organization's reputation and holds the capacity to influence one's actions which can be a potential threat to modern civilization. The proposed work in this paper presents an ambiguous fake news classification model using the decision tree, random forest, and SVM. It first pre-processed the known dataset, extracted its features, and then provided the training to all three classifiers. Further, the classifiers were tested against unknown datasets. The experiments were performed on the collected dataset of 40,000 records including fake and real news. It is observed that it achieved very promising experimental results of precision, recall, and accuracy. It obtained the best results with the decision tree, that is, 0.9977 for both precision and recall along with 99.67% accuracy.
{"title":"A Novel Approach to Ambiguous Fake News Classification through Machine Learning","authors":"Sanai Divadkar, Akshat Sahu, Shalini Puri","doi":"10.1109/GCAT55367.2022.9972102","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972102","url":null,"abstract":"The rise of digitalization and technology has substantially expanded the number of people with online news access, resulting in a significant shift in how information is consumed on social channels. The spread of fake news with ambiguity is a critical and harmful aspect of handling online news access. Such news should be identified quickly since it can harm an individual or organization's reputation and holds the capacity to influence one's actions which can be a potential threat to modern civilization. The proposed work in this paper presents an ambiguous fake news classification model using the decision tree, random forest, and SVM. It first pre-processed the known dataset, extracted its features, and then provided the training to all three classifiers. Further, the classifiers were tested against unknown datasets. The experiments were performed on the collected dataset of 40,000 records including fake and real news. It is observed that it achieved very promising experimental results of precision, recall, and accuracy. It obtained the best results with the decision tree, that is, 0.9977 for both precision and recall along with 99.67% accuracy.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117299871","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972201
G. Pooja, K. Rekha
The traditional attendance method involves instructors marking registers, which leads to human error and a lot of upkeep. In the existing system, time consumption is a significant problem. We have considered revolutionising it by using new digital techniques, such as FACE RECOGNITION. The proposed framework will result in increased accuracy and little manual labour. To address the issues of the traditional system, the project has been modernised. The proposed system is on face recognition and then recording attendance. The database of all the students in the class is maintained, and attendance is noted when the individual student's face matches one of the faces stored images; otherwise, the face is disregarded, and attendance is not marked. The multiple faces are detected in the camera simultaneously which helps in real time marking system. The proposed framework employed the HAAR features to find the face in the image using the HAAR cascading classifiers and it is implemented in the python.
{"title":"Automatic Attendance System Using Artificial Intelligence","authors":"G. Pooja, K. Rekha","doi":"10.1109/GCAT55367.2022.9972201","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972201","url":null,"abstract":"The traditional attendance method involves instructors marking registers, which leads to human error and a lot of upkeep. In the existing system, time consumption is a significant problem. We have considered revolutionising it by using new digital techniques, such as FACE RECOGNITION. The proposed framework will result in increased accuracy and little manual labour. To address the issues of the traditional system, the project has been modernised. The proposed system is on face recognition and then recording attendance. The database of all the students in the class is maintained, and attendance is noted when the individual student's face matches one of the faces stored images; otherwise, the face is disregarded, and attendance is not marked. The multiple faces are detected in the camera simultaneously which helps in real time marking system. The proposed framework employed the HAAR features to find the face in the image using the HAAR cascading classifiers and it is implemented in the python.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130374517","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972216
R. Menon, S. D. Kumar, CR Vismaya
Digital technology and World Wide Web have re-sulted in a growth in the number of digital documents. The ma-jority of the data is unstructured, and extracting information into a structured machine-readable format remains a difficult under-taking. Clustering, which automatically categorizes information into meaningful groupings, is one of the most important activ-ities. Several information extraction and information gathering applications use document clustering. Document clustering is an unsupervised method for dividing a big corpus of documents into smaller, meaningful, identifiable, and verifiable sub-groups. But capturing the semantics of the documents is still an open problem. A knowledge graph can represent the relationships between the entities in the document collection. But a knowledge graph gets extremely dense and high-dimensional as the amount of data increases, requiring significant processing resources. We aim to explore this problem by using Knowledge Graph Embedding (KGE), which maps the high-dimensional representation into a compute-efficient low-dimensional embedded representation and then cluster these embeddings using the Gaussian Mixture Model (GMM)-based clustering technique. Dimensionality reduction of the embeddings has been done using t-SNE. We have found that the silhouette coefficient has improved considerably for t-SNE based GMM clustering as compared to Kmeans clustering alone.
{"title":"GMM-based Document Clustering of Knowledge Graph Embeddings","authors":"R. Menon, S. D. Kumar, CR Vismaya","doi":"10.1109/GCAT55367.2022.9972216","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972216","url":null,"abstract":"Digital technology and World Wide Web have re-sulted in a growth in the number of digital documents. The ma-jority of the data is unstructured, and extracting information into a structured machine-readable format remains a difficult under-taking. Clustering, which automatically categorizes information into meaningful groupings, is one of the most important activ-ities. Several information extraction and information gathering applications use document clustering. Document clustering is an unsupervised method for dividing a big corpus of documents into smaller, meaningful, identifiable, and verifiable sub-groups. But capturing the semantics of the documents is still an open problem. A knowledge graph can represent the relationships between the entities in the document collection. But a knowledge graph gets extremely dense and high-dimensional as the amount of data increases, requiring significant processing resources. We aim to explore this problem by using Knowledge Graph Embedding (KGE), which maps the high-dimensional representation into a compute-efficient low-dimensional embedded representation and then cluster these embeddings using the Gaussian Mixture Model (GMM)-based clustering technique. Dimensionality reduction of the embeddings has been done using t-SNE. We have found that the silhouette coefficient has improved considerably for t-SNE based GMM clustering as compared to Kmeans clustering alone.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116334793","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972104
Jose Eduardo B. Cerillo, Rizza T. Loquias, S. Fenomeno
This paper presents the development of an Ant Colony Optimization (ACO)-based UAV flight plan generator for Automatic Electric Meter Reading (AMR) at elevated metering centers (EMC). The program's flight plan against a UAV human operator flight plans were compared for different missions and considering the following: coordinate location of EMCs, the number of electric meters within the EMC, the UAV's takeoff and landing location, the EMC's height, the UAV's position relative to the EMC during data collection, and the UAV's battery capacity. The generated flight plan captures the most EMC data in the shortest time possible, automatically. Tests conducted include the Shortest Route Test and the Largest Amount of Data per Unit Time test that compared the program's and human operator's flight plan development and mission completion times. Results revealed that the program's flight plan is 30.58 percent more efficient than the UAV human operator's during the Shortest Route Test and 28.10 percent more efficient during the Largest Amount of Data per Unit Time test.
{"title":"Automatic Flight Plan Generation for UAV-Assisted Elevated Meter Reading using Ant Colony Optimization","authors":"Jose Eduardo B. Cerillo, Rizza T. Loquias, S. Fenomeno","doi":"10.1109/GCAT55367.2022.9972104","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972104","url":null,"abstract":"This paper presents the development of an Ant Colony Optimization (ACO)-based UAV flight plan generator for Automatic Electric Meter Reading (AMR) at elevated metering centers (EMC). The program's flight plan against a UAV human operator flight plans were compared for different missions and considering the following: coordinate location of EMCs, the number of electric meters within the EMC, the UAV's takeoff and landing location, the EMC's height, the UAV's position relative to the EMC during data collection, and the UAV's battery capacity. The generated flight plan captures the most EMC data in the shortest time possible, automatically. Tests conducted include the Shortest Route Test and the Largest Amount of Data per Unit Time test that compared the program's and human operator's flight plan development and mission completion times. Results revealed that the program's flight plan is 30.58 percent more efficient than the UAV human operator's during the Shortest Route Test and 28.10 percent more efficient during the Largest Amount of Data per Unit Time test.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114799137","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972193
T. Porselvi, Sr Y Aouthithiye Barathwaj, S. Cs, S. V. Tresa Sangeetha, J. Shalini Priya
Predictive Analysis using deep learning techniques are emerging in several engineering domains. Artificial Neural Networks consists of network of layers to learn, process and predict from the data. Their implementation in electrical and electronics engineering has consistently helped in producing intelligent industries with effective results. The brushless direct current (BLDC)motor generates magnetic fields by switching DC current to the motor windings using electronic closed-loop controllers. BLDC motors require low maintenance, and exhibit high speed and sufficient torque capacity and hence are used in various applications. This motor has an edge over other motors because of its superior performance and ease with which the power converters can regulate its speed. This article describes a technique for varying the speed of a BLDC motor that involves altering the voltage of bridge converter, which feeds the motor winding. The speed control is carried out with a speed controller (PI-based). The motor is modelled in MATLAB/Simulink, and a PI controller is employed to provide the speed control. Simulated waveforms of EMF signals are achieved along with rotor speed, Hall Effect signals, electromagnetic torque, and PWMsignals. Artificial neural networks (ANN) are used to forecast the corresponding parameters, and they are fed with the gathered data to produce results that are reasonably close to the results from the simulations. Hence, both the simulation-based approach as well as the predictions from the data provided, yield satisfactory outcomes.
{"title":"Deep Learning Based Predictive Analysis of BLDC Motor Control","authors":"T. Porselvi, Sr Y Aouthithiye Barathwaj, S. Cs, S. V. Tresa Sangeetha, J. Shalini Priya","doi":"10.1109/GCAT55367.2022.9972193","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972193","url":null,"abstract":"Predictive Analysis using deep learning techniques are emerging in several engineering domains. Artificial Neural Networks consists of network of layers to learn, process and predict from the data. Their implementation in electrical and electronics engineering has consistently helped in producing intelligent industries with effective results. The brushless direct current (BLDC)motor generates magnetic fields by switching DC current to the motor windings using electronic closed-loop controllers. BLDC motors require low maintenance, and exhibit high speed and sufficient torque capacity and hence are used in various applications. This motor has an edge over other motors because of its superior performance and ease with which the power converters can regulate its speed. This article describes a technique for varying the speed of a BLDC motor that involves altering the voltage of bridge converter, which feeds the motor winding. The speed control is carried out with a speed controller (PI-based). The motor is modelled in MATLAB/Simulink, and a PI controller is employed to provide the speed control. Simulated waveforms of EMF signals are achieved along with rotor speed, Hall Effect signals, electromagnetic torque, and PWMsignals. Artificial neural networks (ANN) are used to forecast the corresponding parameters, and they are fed with the gathered data to produce results that are reasonably close to the results from the simulations. Hence, both the simulation-based approach as well as the predictions from the data provided, yield satisfactory outcomes.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124370096","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9971846
Viraj Nitin Vaidya, V. Ingale, Ashlesha Gokhale
PCI Express (Peripheral Component Interconnect) is a point-to-point, high-performance, serial interconnect protocol. PCIe outperforms older buses and offers greater bandwidth, making it a fantastic option for a wide range of applications. PCIe features layered architecture with three distinct layers. Packets are used to convey information between these layers. The verification IP of the physical layer in PCI Express is implemented in this paper. The Universal Verification Methodology is used for development of VIP of PCIe, which is written in System Verilog (UVM).
{"title":"Development of Verification IP of Physical Layer of PCIe","authors":"Viraj Nitin Vaidya, V. Ingale, Ashlesha Gokhale","doi":"10.1109/GCAT55367.2022.9971846","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971846","url":null,"abstract":"PCI Express (Peripheral Component Interconnect) is a point-to-point, high-performance, serial interconnect protocol. PCIe outperforms older buses and offers greater bandwidth, making it a fantastic option for a wide range of applications. PCIe features layered architecture with three distinct layers. Packets are used to convey information between these layers. The verification IP of the physical layer in PCI Express is implemented in this paper. The Universal Verification Methodology is used for development of VIP of PCIe, which is written in System Verilog (UVM).","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124080109","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9971842
K. Ramanjaneyulu, Sri. L Manju, M. Sohit, M. Vikas, S. Yaswanth
This Skeletal bone age estimation measures the development level and maturity of individuals. Investigating genetic, endocrinological, and growth abnormalities in children is a clinical practice. It also helps pediatrics to predict puberty entrance and growth, and identify genetic disorders. The Tanner-Whitehouse (TW) technique or the Greulich and Pyle (G&P) approach are often used for the radiological evaluation of the left hand. Both clinical approaches, however, have several drawbacks. In this research, we present a deep learning technique to automatically determine the age of skeletal bones to enhance and accelerate bone age estimates. This research also provides a comparison between manually crafted and deep learned features. The dataset utilized consisted of 12811 X-ray hand scans of people ranging in age from birth to 19 years old. The results showed a slight deviation between the manual and automatic evaluation of bone age.
这种骨骼年龄估计衡量的是个体的发育水平和成熟度。调查儿童的遗传、内分泌和生长异常是一项临床实践。它还有助于儿科预测青春期的进入和生长，并识别遗传疾病。taner - whitehouse (TW)技术或Greulich and Pyle (G&P)方法通常用于左手的放射学评估。然而，这两种临床方法都有一些缺点。在这项研究中，我们提出了一种深度学习技术来自动确定骨骼的年龄，以增强和加速骨骼年龄的估计。这项研究还提供了手工制作和深度学习特征之间的比较。使用的数据集包括12811个x射线手部扫描，年龄从出生到19岁不等。结果显示，人工和自动评估骨龄之间存在轻微偏差。
{"title":"Deep Learning-Based Bone Age Estimation Using X-Ray Hand Images","authors":"K. Ramanjaneyulu, Sri. L Manju, M. Sohit, M. Vikas, S. Yaswanth","doi":"10.1109/GCAT55367.2022.9971842","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971842","url":null,"abstract":"This Skeletal bone age estimation measures the development level and maturity of individuals. Investigating genetic, endocrinological, and growth abnormalities in children is a clinical practice. It also helps pediatrics to predict puberty entrance and growth, and identify genetic disorders. The Tanner-Whitehouse (TW) technique or the Greulich and Pyle (G&P) approach are often used for the radiological evaluation of the left hand. Both clinical approaches, however, have several drawbacks. In this research, we present a deep learning technique to automatically determine the age of skeletal bones to enhance and accelerate bone age estimates. This research also provides a comparison between manually crafted and deep learned features. The dataset utilized consisted of 12811 X-ray hand scans of people ranging in age from birth to 19 years old. The results showed a slight deviation between the manual and automatic evaluation of bone age.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126483144","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9971927
Suraj Naik, S. Kulkarni
Bifacial solar cells have the ability to generate more energy than mono-facial solar cells since both of their front and back surfaces can capture solar radiation. In some cases, a 5-20% increase in output power is claimed in the literature. There is currently no established method for quantifying underwater bifacial modules. This paper compares measurements of underwater bifacial modules in both natural and artificial lighting conditions. This article discusses PV characteristics in both natural and underwater environments. The test scenarios involve submerging solar panels at various depths in water containing 244 ppm TDS. A halogen lamp, which can effectively cover the infrared spectrum of lightning, was used to provide artificial lighting.
{"title":"Design and Analysis of Underwater Bifacial Solar Photovoltaic Cell","authors":"Suraj Naik, S. Kulkarni","doi":"10.1109/GCAT55367.2022.9971927","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971927","url":null,"abstract":"Bifacial solar cells have the ability to generate more energy than mono-facial solar cells since both of their front and back surfaces can capture solar radiation. In some cases, a 5-20% increase in output power is claimed in the literature. There is currently no established method for quantifying underwater bifacial modules. This paper compares measurements of underwater bifacial modules in both natural and artificial lighting conditions. This article discusses PV characteristics in both natural and underwater environments. The test scenarios involve submerging solar panels at various depths in water containing 244 ppm TDS. A halogen lamp, which can effectively cover the infrared spectrum of lightning, was used to provide artificial lighting.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128016078","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972185
Jalaj Tyagi, S. Yadav, Shakuntla Boora, Poonam Singhal
Uplifting of the Electrical vehicle technology allow drastic change toward the green energy system and make environment pollution free, although nowadays government taking many initiatives toward development of the Electric Vehicle (EV) technology and by 2030‘s electric vehicle should occupy all of the space of the Internal Combustion Engine (ICEs). EVs allow to move toward sustainability and also make environment free from carbon emission. As fossil fuel consumption is directly proportional to the amount of carbon emit into the environment. EVs work with the principle of the Electric system which can be directly link to the resources used in the generation of the electricity if the resources used to generate electricity could be renewable energy, then sustainability toward development of the environment pollution free can be attain 100 %. While discussing EVs give direct highlight on the Energy Storage and the type of energy storage using in the EVs. Generally, Lithium-Ion batteries increasing extensively in the EVs market due to their excellent performance. On the other hand, supercharge capacitor or ultra-capacitor also creating significant impact toward growth of the electric mobility market. As Ultra capacitor characteristic provide criteria to fit into the Electric mobility market such as high Efficiency, High Temperature stability, instantly charge and discharge without dropping in the performance. Generally, batteries have low specific power but high specific storage system can be attained with the implementation of the ultracapacitor to the Energy storage System and allow to develop the Hybrid topology of the Energy system which can be used to reduce the jerk load /power utilization in the vehicle in the terms of acceleration/deceleration and also flow of energy in the regeneration process. This paper provides an extensive implementation of the hybrid energy storage System (Battery along with Ultra capacitors)with regeneration of the energy toward energy storage.
{"title":"Implementation of Battery and Ultra capacitors Based storage for Electric Vehicle system","authors":"Jalaj Tyagi, S. Yadav, Shakuntla Boora, Poonam Singhal","doi":"10.1109/GCAT55367.2022.9972185","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972185","url":null,"abstract":"Uplifting of the Electrical vehicle technology allow drastic change toward the green energy system and make environment pollution free, although nowadays government taking many initiatives toward development of the Electric Vehicle (EV) technology and by 2030‘s electric vehicle should occupy all of the space of the Internal Combustion Engine (ICEs). EVs allow to move toward sustainability and also make environment free from carbon emission. As fossil fuel consumption is directly proportional to the amount of carbon emit into the environment. EVs work with the principle of the Electric system which can be directly link to the resources used in the generation of the electricity if the resources used to generate electricity could be renewable energy, then sustainability toward development of the environment pollution free can be attain 100 %. While discussing EVs give direct highlight on the Energy Storage and the type of energy storage using in the EVs. Generally, Lithium-Ion batteries increasing extensively in the EVs market due to their excellent performance. On the other hand, supercharge capacitor or ultra-capacitor also creating significant impact toward growth of the electric mobility market. As Ultra capacitor characteristic provide criteria to fit into the Electric mobility market such as high Efficiency, High Temperature stability, instantly charge and discharge without dropping in the performance. Generally, batteries have low specific power but high specific storage system can be attained with the implementation of the ultracapacitor to the Energy storage System and allow to develop the Hybrid topology of the Energy system which can be used to reduce the jerk load /power utilization in the vehicle in the terms of acceleration/deceleration and also flow of energy in the regeneration process. This paper provides an extensive implementation of the hybrid energy storage System (Battery along with Ultra capacitors)with regeneration of the energy toward energy storage.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122252185","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}
Pub Date : 2022-10-07DOI: 10.1109/GCAT55367.2022.9972090
P. Kumar, G. Murthy
On-board diagnostics (OBD) is an automotive term for a vehicle's ability to self-diagnose and report problems. OBD systems give car owners and technicians access to information on the condition of various vehicle subsystems. Modern automobiles are complex devices that include advances in electrical, electronic, and mechanical engineering. The conventional “trial-and-error” method of diagnosis may no longer be sufficient to handle the demand for car maintenance and repairs. As a result, it becomes necessary to implement a new mode of diagnosis with high efficiency on new generation cars to keep up with the technological trend. This paper describes about Automotive Sensor Tester (AST) which is a reliable and cost-effective diagnostic solution for automotive OEMs and vehicle service agencies. AST facilitates and improves diagnosis speed, total time taken for diagnosis, and provides a better GUI for service engineers to do easy operations.
{"title":"Implementation of Automotive Sensor Tester for Engineers at OEMs and Vehicle Service Agencies using Raspberry Pi","authors":"P. Kumar, G. Murthy","doi":"10.1109/GCAT55367.2022.9972090","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972090","url":null,"abstract":"On-board diagnostics (OBD) is an automotive term for a vehicle's ability to self-diagnose and report problems. OBD systems give car owners and technicians access to information on the condition of various vehicle subsystems. Modern automobiles are complex devices that include advances in electrical, electronic, and mechanical engineering. The conventional “trial-and-error” method of diagnosis may no longer be sufficient to handle the demand for car maintenance and repairs. As a result, it becomes necessary to implement a new mode of diagnosis with high efficiency on new generation cars to keep up with the technological trend. This paper describes about Automotive Sensor Tester (AST) which is a reliable and cost-effective diagnostic solution for automotive OEMs and vehicle service agencies. AST facilitates and improves diagnosis speed, total time taken for diagnosis, and provides a better GUI for service engineers to do easy operations.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":" 50","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132010540","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}
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