Pub Date : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028942
S. K. Bhagat, L. Saikia, G. M. Meseret, M. Behera, Satish Kumar Ramoji, N. Babu, B. Dekaraja
This article presents the effect of a precise wind turbine system (PWTS) and accurate model of HVDC link on multi-area AGC systems. The proposed system comprises one thermal and PWTS unit in all the areas. A novel secondary controller known as tilt-integral-double derivative (TIDD) has been developed. In order to fine-tune the controller and other variables, the bird swarm algorithm (BSA) has been used effectively. The comparison of system dynamics responses with PID, TID, and TIDD controller concluded that the system with TIDD outperformed. The study of PWTS integration on system dynamics concluded that PWTS improves the system’s dynamic performance. Moreover, the integration AHVDC link with AC tie-line revealed significantly improved in dynamics responses. Further, the sensitivity analysis has been performed to test the proposed TIDD controller’s robustness under different loading conditions.
{"title":"Effect of PWTS and AHVDC link on Multi-Area AGC System Considering TIDD Controller","authors":"S. K. Bhagat, L. Saikia, G. M. Meseret, M. Behera, Satish Kumar Ramoji, N. Babu, B. Dekaraja","doi":"10.1109/SILCON55242.2022.10028942","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028942","url":null,"abstract":"This article presents the effect of a precise wind turbine system (PWTS) and accurate model of HVDC link on multi-area AGC systems. The proposed system comprises one thermal and PWTS unit in all the areas. A novel secondary controller known as tilt-integral-double derivative (TIDD) has been developed. In order to fine-tune the controller and other variables, the bird swarm algorithm (BSA) has been used effectively. The comparison of system dynamics responses with PID, TID, and TIDD controller concluded that the system with TIDD outperformed. The study of PWTS integration on system dynamics concluded that PWTS improves the system’s dynamic performance. Moreover, the integration AHVDC link with AC tie-line revealed significantly improved in dynamics responses. Further, the sensitivity analysis has been performed to test the proposed TIDD controller’s robustness under different loading conditions.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127098868","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028865
Kriti Thakur, A. Jain
DC micro grid provides power locally with minimum transmission losses. However, due to presence of converters, dc micro grid suffers from the nonlinearities which led to instability of the system. It imposes challenge to integrate dc micro grid with the distribution network. Therefore, in this paper, the transient stability of the DC microgrid has been investigated considering linear load, nonlinear load, nonlinear load with DG and pole to ground fault. Due to the high-order and nonlinear nature of the dc microgrid system, the nonlinear decoupling method has been adopted for a more efficient analysis of the transient stability of dc microgrids. The nonlinear decoupling technique can resolve nonlinear difficulties, which is extremely appropriate for the transient stability assessment of dc microgrids. From the results, it is observed that in the case of nonlinear loads, the introduction of DG as an active power compensation in the system can considerably improve the overall active power in the system. Also, in case of fault, DG works as a backup and supplies power to the load. The simulation results also reflects that in some circumstances, adding and removing large loads and changes in voltage levels are not invertible. One of these changes in system dynamics could result in system instability.
{"title":"Transient Stability Assessment of DC Microgrid using Nonlinear Decoupling Approach","authors":"Kriti Thakur, A. Jain","doi":"10.1109/SILCON55242.2022.10028865","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028865","url":null,"abstract":"DC micro grid provides power locally with minimum transmission losses. However, due to presence of converters, dc micro grid suffers from the nonlinearities which led to instability of the system. It imposes challenge to integrate dc micro grid with the distribution network. Therefore, in this paper, the transient stability of the DC microgrid has been investigated considering linear load, nonlinear load, nonlinear load with DG and pole to ground fault. Due to the high-order and nonlinear nature of the dc microgrid system, the nonlinear decoupling method has been adopted for a more efficient analysis of the transient stability of dc microgrids. The nonlinear decoupling technique can resolve nonlinear difficulties, which is extremely appropriate for the transient stability assessment of dc microgrids. From the results, it is observed that in the case of nonlinear loads, the introduction of DG as an active power compensation in the system can considerably improve the overall active power in the system. Also, in case of fault, DG works as a backup and supplies power to the load. The simulation results also reflects that in some circumstances, adding and removing large loads and changes in voltage levels are not invertible. One of these changes in system dynamics could result in system instability.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132754264","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028822
Rakesh Kumar, A. De
A twin-band microstrip antenna with CSRR in the ground plane suitable for 5G wireless technology is presented in this article. The antenna radiates from 26.9GHz to 27.5 GHz with center frequency at 27.3GHz and from 29.3GHz to 29.9GHz with center frequency at 29.5GHz with peak realized gain of 7.25dB and 7.45dB respectively. The antenna applies twin slots on the patch and CSRR in the ground plane for improved stability and gain. The antenna is fabricated on RT Duroid 5880 of thickness 0.8 mm. The simulation is carried out in HFSS, which employs the method of finite element. For getting the optimized result, HFSS’s optometric analysis is also used.
{"title":"Design of High Gain, Twin-band Antenna with CSRR for 5G Applications","authors":"Rakesh Kumar, A. De","doi":"10.1109/SILCON55242.2022.10028822","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028822","url":null,"abstract":"A twin-band microstrip antenna with CSRR in the ground plane suitable for 5G wireless technology is presented in this article. The antenna radiates from 26.9GHz to 27.5 GHz with center frequency at 27.3GHz and from 29.3GHz to 29.9GHz with center frequency at 29.5GHz with peak realized gain of 7.25dB and 7.45dB respectively. The antenna applies twin slots on the patch and CSRR in the ground plane for improved stability and gain. The antenna is fabricated on RT Duroid 5880 of thickness 0.8 mm. The simulation is carried out in HFSS, which employs the method of finite element. For getting the optimized result, HFSS’s optometric analysis is also used.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"34 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115662497","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028890
Banala Saritha, Mohammad Azharuddin Laskar, R. Laskar, Madhuchhanda Choudhury
Deep learning is attracting tremendous prominence as an adequate replacement for i-vectors in the speaker identification task. Deep neural networks have attained much attention in the end-to-end (E2E) speaker identification domain. Earlier, DNN trained on handcrafted speech features like Mel-filter banks and Mel-frequency cepstral coefficients. Later, as the raw speech signal is lossless, processing raw waveforms have become an active research area in E2E speaker identification, automatic music tagging, and speech recognition fields. Convolutional neural networks (CNNs) have recently shown promising results when fed directly with raw speech samples. CNN analyzes waveforms to discover low-level speech representations rather than conventional handcrafted features, which may enable the system to handle speaker properties like pitch and formants more efficiently. An efficient design of neural networks is vital to achieving this. The CNN architecture proposed in this paper promotes the deep convolutional layers to develop more efficient filters for end-to-end speaker identification systems. The proposed architecture converges quickly and outperforms conventional CNN on raw waveforms. This research work has been tested on the Librispeech dataset and improved the Speaker identification accuracy by 10% and decreased the validation loss by 32%.
{"title":"Raw Waveform Based Speaker Identification Using Deep Neural Networks","authors":"Banala Saritha, Mohammad Azharuddin Laskar, R. Laskar, Madhuchhanda Choudhury","doi":"10.1109/SILCON55242.2022.10028890","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028890","url":null,"abstract":"Deep learning is attracting tremendous prominence as an adequate replacement for i-vectors in the speaker identification task. Deep neural networks have attained much attention in the end-to-end (E2E) speaker identification domain. Earlier, DNN trained on handcrafted speech features like Mel-filter banks and Mel-frequency cepstral coefficients. Later, as the raw speech signal is lossless, processing raw waveforms have become an active research area in E2E speaker identification, automatic music tagging, and speech recognition fields. Convolutional neural networks (CNNs) have recently shown promising results when fed directly with raw speech samples. CNN analyzes waveforms to discover low-level speech representations rather than conventional handcrafted features, which may enable the system to handle speaker properties like pitch and formants more efficiently. An efficient design of neural networks is vital to achieving this. The CNN architecture proposed in this paper promotes the deep convolutional layers to develop more efficient filters for end-to-end speaker identification systems. The proposed architecture converges quickly and outperforms conventional CNN on raw waveforms. This research work has been tested on the Librispeech dataset and improved the Speaker identification accuracy by 10% and decreased the validation loss by 32%.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114730685","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028796
Shyambabu Pandey, Pankaj Dadure, Morrel V. L. Nunsanga, Partha Pakray
Quantum computing is a fast-emerging field that follows the laws of quantum mechanics to solve complex problems for classical systems. In the last few years, several researchers have emerged in quantum computing in accordance with the artificial intelligence field. Natural language processing is one of the prominent subfields of artificial intelligence. Quantum computing can be applied to the applications of natural language processing for better performance. One of the vital applications of natural language processing is Parts-Of-Speech (POS) tagging. It is prerequired for many natural language processing applications. In this paper, we have performed POS tagging of the Mizo language using classical Long short-term memory (LSTM). Subsequently, quantum-enhanced long short-term memory (QLSTM) has also been used to perform POS tagging of the Mizo language. The approaches mentioned above have been tested on the Mizo-tagged corpus, and experimental results have shown that quantum computing approaches such as QLSTM need the inclusion of new technologies to achieve significant results.
{"title":"Parts of speech tagging towards classical to quantum computing","authors":"Shyambabu Pandey, Pankaj Dadure, Morrel V. L. Nunsanga, Partha Pakray","doi":"10.1109/SILCON55242.2022.10028796","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028796","url":null,"abstract":"Quantum computing is a fast-emerging field that follows the laws of quantum mechanics to solve complex problems for classical systems. In the last few years, several researchers have emerged in quantum computing in accordance with the artificial intelligence field. Natural language processing is one of the prominent subfields of artificial intelligence. Quantum computing can be applied to the applications of natural language processing for better performance. One of the vital applications of natural language processing is Parts-Of-Speech (POS) tagging. It is prerequired for many natural language processing applications. In this paper, we have performed POS tagging of the Mizo language using classical Long short-term memory (LSTM). Subsequently, quantum-enhanced long short-term memory (QLSTM) has also been used to perform POS tagging of the Mizo language. The approaches mentioned above have been tested on the Mizo-tagged corpus, and experimental results have shown that quantum computing approaches such as QLSTM need the inclusion of new technologies to achieve significant results.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128112284","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028834
Bedabrata Biswas, F. Talukdar, G. S. Baghel
The resistive Metal oxide semiconductor (MOS) type gas sensor has limitations like low selectivity, low sensitivity, high temperature, and high-power consumption. To resolve these problems, a capacitive gas sensor is introduced in this paper. The sensor is designed carefully by taking care of the fringing field effect. The mathematical modeling of the equivalent circuit of the sensor has been shown. The gas sensing setup has been explained in detail. Finally, the model is simulated in MATLAB and COMSOL.
{"title":"Design and Simulation of a Capacitive MOS Gas Sensor","authors":"Bedabrata Biswas, F. Talukdar, G. S. Baghel","doi":"10.1109/SILCON55242.2022.10028834","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028834","url":null,"abstract":"The resistive Metal oxide semiconductor (MOS) type gas sensor has limitations like low selectivity, low sensitivity, high temperature, and high-power consumption. To resolve these problems, a capacitive gas sensor is introduced in this paper. The sensor is designed carefully by taking care of the fringing field effect. The mathematical modeling of the equivalent circuit of the sensor has been shown. The gas sensing setup has been explained in detail. Finally, the model is simulated in MATLAB and COMSOL.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129348295","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028808
Atharva Deshpande, Shathanaa Rajmohan
Social networking services have emerged as the main sources for real-time information about events happening. It has been observed that pertinent information gleaned from tweets during catastrophic events can be helpful in a variety of ways. Therefore, it is necessary to create an automated microblog summarization system. The proposed approach JOWTS, confluence of a wide range of evolutionary computation techniques such as the well-known differential evolutionary algorithm JADE (DE/current-to-pbest/1), Opposition-based Learning (OBL) and Whale Optimization Algorithm (WOA), employs multi-objective optimization for microblog summarization. The summarization task is formulated as a multi-objective optimization problem and combination of objectives such as tweet length & importance of tweets (through tf-idf technique) in a dataset are optimized at the same time. For evaluation, datasets relevant to disaster events are employed and the results are compared to different alternative methodologies utilizing ROUGE measures. When compared against the contemporary evolutionary techniques, it was observed that JOWTS improves ROUGE-1, 2, L scores by 3.86%, 8.53% and 4.69% respectively.
{"title":"JOWTS: A differential evolution based approach for Microblog Summarization with advanced population enhancement techniques","authors":"Atharva Deshpande, Shathanaa Rajmohan","doi":"10.1109/SILCON55242.2022.10028808","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028808","url":null,"abstract":"Social networking services have emerged as the main sources for real-time information about events happening. It has been observed that pertinent information gleaned from tweets during catastrophic events can be helpful in a variety of ways. Therefore, it is necessary to create an automated microblog summarization system. The proposed approach JOWTS, confluence of a wide range of evolutionary computation techniques such as the well-known differential evolutionary algorithm JADE (DE/current-to-pbest/1), Opposition-based Learning (OBL) and Whale Optimization Algorithm (WOA), employs multi-objective optimization for microblog summarization. The summarization task is formulated as a multi-objective optimization problem and combination of objectives such as tweet length & importance of tweets (through tf-idf technique) in a dataset are optimized at the same time. For evaluation, datasets relevant to disaster events are employed and the results are compared to different alternative methodologies utilizing ROUGE measures. When compared against the contemporary evolutionary techniques, it was observed that JOWTS improves ROUGE-1, 2, L scores by 3.86%, 8.53% and 4.69% respectively.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128622004","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028813
Kiran Venneti, Hrishikesh Kashyap, R. Murugan, N. Jagan Mohan, Tripti Goel
Age-related Macular Degeneration (AMD) is a retina macular degenerative disease that affects elderly persons. Diagnoses of AMD can be accomplished via manual inspection of typical fundus images. But physicians are limited in their ability to process the full extent of data fundus images provide and their diagnoses are subject to differences in interpretation. This paper proposes an image processing algorithm using a lightweight convolution neural network to improve speed and standardization in AMD diagnosis. The first step in lightweight CNN is a feature extraction algorithm that automatically processes a fundus image to extract important retinal features. In the second step, the proposed method classifies the AMD based on the features extracted in the first step. The proposed network has been trained and tested with STARE and RFMiD fundus databases available publicly. The proposed network has obtained 97.39% and 98.97% accuracy with STARE and RFMiD databases, respectively. The results indicate that the proposed model is lightweight and is better than other state-of-the-art techniques, taken for considerations.
{"title":"AMDNet: Age-related Macular Degeneration diagnosis through retinal Fundus Images using Lightweight Convolutional Neural Network","authors":"Kiran Venneti, Hrishikesh Kashyap, R. Murugan, N. Jagan Mohan, Tripti Goel","doi":"10.1109/SILCON55242.2022.10028813","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028813","url":null,"abstract":"Age-related Macular Degeneration (AMD) is a retina macular degenerative disease that affects elderly persons. Diagnoses of AMD can be accomplished via manual inspection of typical fundus images. But physicians are limited in their ability to process the full extent of data fundus images provide and their diagnoses are subject to differences in interpretation. This paper proposes an image processing algorithm using a lightweight convolution neural network to improve speed and standardization in AMD diagnosis. The first step in lightweight CNN is a feature extraction algorithm that automatically processes a fundus image to extract important retinal features. In the second step, the proposed method classifies the AMD based on the features extracted in the first step. The proposed network has been trained and tested with STARE and RFMiD fundus databases available publicly. The proposed network has obtained 97.39% and 98.97% accuracy with STARE and RFMiD databases, respectively. The results indicate that the proposed model is lightweight and is better than other state-of-the-art techniques, taken for considerations.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128350391","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028843
Mani Sarmah, S. Saxena, S. Mukherjee
In today’s tech world, there are several crowdfunding platforms that enable both investors and organizations with a smooth flow of transactions, creating a huge hype in the market. However, security concerns and a fear of fraud are the biggest blow suffered by users on such networks. The history of crowdfunding platforms demonstrates the massive frauds that the public has been subjected to in recent years. This paper provides a completely decentralized method for creating a crowdfunding platform over the Ethereum Blockchain in the proposed system. A lot of attention has been attracted by Blockchain technology as a result of the rise of cryptocurrencies and decentralized apps. A common paradigm among them is the newly emerging Blockchain-based crowdfunding, which eliminates centralized cloud servers and uses smart contracts to fulfill each and every transaction. Blockchain, a promising decentralized paradigm, can be used to provide technological advancements like decentralization and accountability in addition to fixing the problems with current crowdfunding methods. The fundamental objective of the solution is to encourage accountability, transparency, and traceability for all stakeholders so that they always have complete control over their investments.
{"title":"A Decentralized Crowdfunding Solution on top of the Ethereum Blockchain","authors":"Mani Sarmah, S. Saxena, S. Mukherjee","doi":"10.1109/SILCON55242.2022.10028843","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028843","url":null,"abstract":"In today’s tech world, there are several crowdfunding platforms that enable both investors and organizations with a smooth flow of transactions, creating a huge hype in the market. However, security concerns and a fear of fraud are the biggest blow suffered by users on such networks. The history of crowdfunding platforms demonstrates the massive frauds that the public has been subjected to in recent years. This paper provides a completely decentralized method for creating a crowdfunding platform over the Ethereum Blockchain in the proposed system. A lot of attention has been attracted by Blockchain technology as a result of the rise of cryptocurrencies and decentralized apps. A common paradigm among them is the newly emerging Blockchain-based crowdfunding, which eliminates centralized cloud servers and uses smart contracts to fulfill each and every transaction. Blockchain, a promising decentralized paradigm, can be used to provide technological advancements like decentralization and accountability in addition to fixing the problems with current crowdfunding methods. The fundamental objective of the solution is to encourage accountability, transparency, and traceability for all stakeholders so that they always have complete control over their investments.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122256808","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 : 2022-11-04DOI: 10.1109/SILCON55242.2022.10028974
Aiswarya T, Sumi M, H. I
The advent of Radio Frequency Identification (RFID) applications has gained a lot of attention recently among manufacturers, developers and end-users. In essence, RFID has touched a wide range of identification, item tracking and sensing applications. However, because of the high cost of silicon-based integrated circuits, Chipped RFID’s widespread adoption is sometimes hampered.This problem may be solved by creating design approaches and strategies for improving performance for Chipless RFID implementation.This article goes through a handful of the key applications that Chipless can directly support.
{"title":"Applications of Chipless RFID in Different Sectors:A Review","authors":"Aiswarya T, Sumi M, H. I","doi":"10.1109/SILCON55242.2022.10028974","DOIUrl":"https://doi.org/10.1109/SILCON55242.2022.10028974","url":null,"abstract":"The advent of Radio Frequency Identification (RFID) applications has gained a lot of attention recently among manufacturers, developers and end-users. In essence, RFID has touched a wide range of identification, item tracking and sensing applications. However, because of the high cost of silicon-based integrated circuits, Chipped RFID’s widespread adoption is sometimes hampered.This problem may be solved by creating design approaches and strategies for improving performance for Chipless RFID implementation.This article goes through a handful of the key applications that Chipless can directly support.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132840795","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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