Pub Date : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640715
P. Karthikayan, R. Pushpakumar
In this world, approximately 300 million are visually impaired, smart glasses helps the people who are Visually Impaired to enhance their life. With the help of this device they can navigate independently, feel convenient in the society, and also feel secure. They have many problems in their life, some of them are they cannot navigate independently, cheated in terms of money, Bus or Train number identification etc. In this system two features are implemented they are Currency Recognition and Traffic Light Detection. A Machine Learning (ML) Model is configured which consists of Convolution Neutral Network (CNN), image processing techniques, and Object detection model. Currency recognition extracts both visible and hided marks on the money for effective classification. Traffic light detection uses an image processing algorithm with standard object recognition methods. This system helps the Visually Impaired to cross the road without other's help. For the first feature i.e. Currency recognition, the output is the value of the currency that person has in his/her hand and for the second feature i.e. Traffic light detection, the output is whether the traffic light is red or green, if it is green then the number of seconds that person has to cross the road.
{"title":"Smart Glasses for Visually Impaired Using Image Processing Techniques","authors":"P. Karthikayan, R. Pushpakumar","doi":"10.1109/I-SMAC52330.2021.9640715","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640715","url":null,"abstract":"In this world, approximately 300 million are visually impaired, smart glasses helps the people who are Visually Impaired to enhance their life. With the help of this device they can navigate independently, feel convenient in the society, and also feel secure. They have many problems in their life, some of them are they cannot navigate independently, cheated in terms of money, Bus or Train number identification etc. In this system two features are implemented they are Currency Recognition and Traffic Light Detection. A Machine Learning (ML) Model is configured which consists of Convolution Neutral Network (CNN), image processing techniques, and Object detection model. Currency recognition extracts both visible and hided marks on the money for effective classification. Traffic light detection uses an image processing algorithm with standard object recognition methods. This system helps the Visually Impaired to cross the road without other's help. For the first feature i.e. Currency recognition, the output is the value of the currency that person has in his/her hand and for the second feature i.e. Traffic light detection, the output is whether the traffic light is red or green, if it is green then the number of seconds that person has to cross the road.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124257453","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640803
S. Srinivasan, P. Deepalakshmi
Machine Learning involves conceiving algorithms that enable computin The corporates and enterprises success are increasingly dependent on technology, system security, and its infrastructure. The corporates are committed to secure millions of customer’s data, clients, employees and other stakeholder’s information. Due to the increasing number of securities breaches, it proves information security fiascos may consequence trendy of substantial damage to a company’s reputation and customer’s trust. Also, the corporates that lose a substantial amount of revenue parched may face fines for failing to protect customer information. Therefore, it is imperative that organizations have proper security measures in place. To certify the superior configuration among the enterprises information system security plans and protecting customer in-formation, this proposal launches security research called cybersecurity along with how the malware analytics support cyber security in the space of Securing Internet of Things (SIoT) domain. The research is focusing on cyber security which essentially focuses on protecting the information with various analytics with auto malware deductions. Malware auto detections and analytics helps multifaceted in the development of logical data sets which is the combination from small to large data sets which expose data in concealed forms, unidentified associations, and preferences of customers to establish the cybersecurity of their enterprise.
{"title":"Malware Multi Perspective Analytics with Auto Deduction in Cybersecurity","authors":"S. Srinivasan, P. Deepalakshmi","doi":"10.1109/I-SMAC52330.2021.9640803","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640803","url":null,"abstract":"Machine Learning involves conceiving algorithms that enable computin The corporates and enterprises success are increasingly dependent on technology, system security, and its infrastructure. The corporates are committed to secure millions of customer’s data, clients, employees and other stakeholder’s information. Due to the increasing number of securities breaches, it proves information security fiascos may consequence trendy of substantial damage to a company’s reputation and customer’s trust. Also, the corporates that lose a substantial amount of revenue parched may face fines for failing to protect customer information. Therefore, it is imperative that organizations have proper security measures in place. To certify the superior configuration among the enterprises information system security plans and protecting customer in-formation, this proposal launches security research called cybersecurity along with how the malware analytics support cyber security in the space of Securing Internet of Things (SIoT) domain. The research is focusing on cyber security which essentially focuses on protecting the information with various analytics with auto malware deductions. Malware auto detections and analytics helps multifaceted in the development of logical data sets which is the combination from small to large data sets which expose data in concealed forms, unidentified associations, and preferences of customers to establish the cybersecurity of their enterprise.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121008202","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640851
K. Koti, Guna Sekhar Sajja, Dennis Arias-Chávez, R. Rajasekaran, Regin Rajan, D. Vijendra Babu
Image Deblurring is a common restoration issue. However, existing deep learning approaches have generalization and interpretability issues. This research work provides a framework capable of regulated, confidence-based noise removal in this project to address these issues. The framework is built on merging two denoised images, both of which were generated from the same noisy input. One of the two is denoised using generic algorithms (for example, Gaussian), making few assumptions about the input images and generalizing across all cases. The other uses deep learning to denoise data and performs well on known datasets. Also, this research work presents a series of strategies for seamlessly fusing the two components in the frequency domain. Also, this research work presents a fusion technique that protects users from out-of-distribution inputs and estimates the confidence of a deep learning denoiser to allow users to interpret the result. Further, this research work will illustrate the efficacy of the suggested framework in various use cases through experiments.
{"title":"Impact of Strength Picture on Convolving with Regulation","authors":"K. Koti, Guna Sekhar Sajja, Dennis Arias-Chávez, R. Rajasekaran, Regin Rajan, D. Vijendra Babu","doi":"10.1109/I-SMAC52330.2021.9640851","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640851","url":null,"abstract":"Image Deblurring is a common restoration issue. However, existing deep learning approaches have generalization and interpretability issues. This research work provides a framework capable of regulated, confidence-based noise removal in this project to address these issues. The framework is built on merging two denoised images, both of which were generated from the same noisy input. One of the two is denoised using generic algorithms (for example, Gaussian), making few assumptions about the input images and generalizing across all cases. The other uses deep learning to denoise data and performs well on known datasets. Also, this research work presents a series of strategies for seamlessly fusing the two components in the frequency domain. Also, this research work presents a fusion technique that protects users from out-of-distribution inputs and estimates the confidence of a deep learning denoiser to allow users to interpret the result. Further, this research work will illustrate the efficacy of the suggested framework in various use cases through experiments.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261423","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640934
G. Mani, P. Srinivas, G. Rao, Chitturi Prasad, Donepudi Priyanka, Naresh Cherukuri
Tor is a popular anonymity network used by millions to access internet services while maintaining their privacy. The main concept behind Tor is that a user can build a "circuit" of routers called relays, where each relay carries the client’s traffic to the next relay, without any single relay knowing the full extent of the path. Thus, anonymity is achieved, because no single relay can trace the client to the destination.However, a paper written in 2005 titled "Low-Cost Traffic Analysis of Tor" by Steven J. Murdoch and George Danez is demonstrated that a traffic analysis attack was possible against the Tor network. Any attacker could monitor the load on a relay in the Tor network by calculating the round trip time (RTT) to the relay, and when the RTT spiked, it was clear that the relay was being used. With this information, attackers could trace the path of a client in the Tor network and de-anonymize them.This paper was written in 2005, when Tor was still young. At the time of Murdoch and Danezis’ paper, the entire Tor network consisted of just fifty relays. As of the time of writing, there were well over 7,000 relays in the network, so the ecosystem of Tor is radically different. With all of the increased traffic, it is highly required to determine if this type of attack was still valid, and would not be masked by other traffic.Our results indicate that if a victim is downloading or streaming a large file as fast as Tor will allow them to, a decrease in bandwidth and an increase in round trip time (RTT) is usually observable on each relay in the circuit. This research work has also discovered the Tor guard relays, a special subset of relays that clients will pick as the first hop in their circuit are very susceptible to this kind of attack.
Tor是一个受欢迎的匿名网络，数百万人使用它来访问互联网服务，同时保护他们的隐私。Tor背后的主要概念是，用户可以建立一个称为中继的路由器“电路”，其中每个中继将客户端的流量传递给下一个中继，而无需任何一个中继知道路径的全部范围。这样就实现了匿名性，因为没有一个中继可以跟踪客户端到目的地。然而，2005年由Steven J. Murdoch和George Danez撰写的一篇题为“Tor的低成本流量分析”的论文证明了流量分析攻击是可能针对Tor网络的。任何攻击者都可以通过计算到中继的往返时间(RTT)来监视Tor网络中中继上的负载，当RTT达到峰值时，很明显该中继正在被使用。有了这些信息，攻击者就可以追踪Tor网络中客户端的路径，并将其去匿名化。这篇论文写于2005年，当时Tor还很年轻。在默多克和达内齐斯发表论文的时候，整个Tor网络只有50个中继。在撰写本文时，网络中有超过7,000个中继，因此Tor的生态系统完全不同。随着流量的增加，非常需要确定这种类型的攻击是否仍然有效，并且不会被其他流量掩盖。我们的结果表明，如果受害者下载或流式传输大文件的速度达到Tor允许的速度，则通常可以在电路中的每个中继上观察到带宽的减少和往返时间(RTT)的增加。这项研究工作还发现了Tor保护中继，这是一个特殊的中继子集，客户端将选择作为其电路中的第一跳，非常容易受到这种攻击。
{"title":"Traffic Analysis of High Throughput Traffic on Tor","authors":"G. Mani, P. Srinivas, G. Rao, Chitturi Prasad, Donepudi Priyanka, Naresh Cherukuri","doi":"10.1109/I-SMAC52330.2021.9640934","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640934","url":null,"abstract":"Tor is a popular anonymity network used by millions to access internet services while maintaining their privacy. The main concept behind Tor is that a user can build a \"circuit\" of routers called relays, where each relay carries the client’s traffic to the next relay, without any single relay knowing the full extent of the path. Thus, anonymity is achieved, because no single relay can trace the client to the destination.However, a paper written in 2005 titled \"Low-Cost Traffic Analysis of Tor\" by Steven J. Murdoch and George Danez is demonstrated that a traffic analysis attack was possible against the Tor network. Any attacker could monitor the load on a relay in the Tor network by calculating the round trip time (RTT) to the relay, and when the RTT spiked, it was clear that the relay was being used. With this information, attackers could trace the path of a client in the Tor network and de-anonymize them.This paper was written in 2005, when Tor was still young. At the time of Murdoch and Danezis’ paper, the entire Tor network consisted of just fifty relays. As of the time of writing, there were well over 7,000 relays in the network, so the ecosystem of Tor is radically different. With all of the increased traffic, it is highly required to determine if this type of attack was still valid, and would not be masked by other traffic.Our results indicate that if a victim is downloading or streaming a large file as fast as Tor will allow them to, a decrease in bandwidth and an increase in round trip time (RTT) is usually observable on each relay in the circuit. This research work has also discovered the Tor guard relays, a special subset of relays that clients will pick as the first hop in their circuit are very susceptible to this kind of attack.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"439 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116019077","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640706
Supriya L P, Rashmita Khilar
Affective computing is a form of machinery that enables the machine to respond to a human stimulus in some way, usually associated with sophisticated mood or emotional indications. This emotion based music player project is a novel approach that helps the user play songs automatically based on the user's emotions. This understands user's facial emotions and plays the songs according to their emotions. Music as a major impact on the regular life of human beings and in innovative, progressive technologies. Generally the operator needs to do with the challenge of looking for songs manually navigate through the playlist to choose from. At this point it suggests an effective and precise model, which would produce a playlist constructed on the user's present emotional state and behavior. Existing strategies to mechanize the method of creating the playlist are computationally moderate, less solid and some of the time includes the utilization of additional hardware. Discourse is the foremost antiquated and ordinary way of communicating considerations, feelings, and temperament and it requires tall specialized, time, and taken a toll. This proposed framework is based on extricating facial expressions in real-time, as well as extricating sound highlights from tunes to decipher into a specific feeling that will naturally produce a playlist so that the fetched of handling is moderately low. The Emotions are recognized using Support Vector Machine (SVM) . The webcam captures the user's image. It then extracts the user's facial features from the captured image. The music will be played from the pre- defined files, depending on the emotion.
{"title":"Affective Music Player for Multiple Emotion Recognition Using Facial Expressions with SVM","authors":"Supriya L P, Rashmita Khilar","doi":"10.1109/I-SMAC52330.2021.9640706","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640706","url":null,"abstract":"Affective computing is a form of machinery that enables the machine to respond to a human stimulus in some way, usually associated with sophisticated mood or emotional indications. This emotion based music player project is a novel approach that helps the user play songs automatically based on the user's emotions. This understands user's facial emotions and plays the songs according to their emotions. Music as a major impact on the regular life of human beings and in innovative, progressive technologies. Generally the operator needs to do with the challenge of looking for songs manually navigate through the playlist to choose from. At this point it suggests an effective and precise model, which would produce a playlist constructed on the user's present emotional state and behavior. Existing strategies to mechanize the method of creating the playlist are computationally moderate, less solid and some of the time includes the utilization of additional hardware. Discourse is the foremost antiquated and ordinary way of communicating considerations, feelings, and temperament and it requires tall specialized, time, and taken a toll. This proposed framework is based on extricating facial expressions in real-time, as well as extricating sound highlights from tunes to decipher into a specific feeling that will naturally produce a playlist so that the fetched of handling is moderately low. The Emotions are recognized using Support Vector Machine (SVM) . The webcam captures the user's image. It then extracts the user's facial features from the captured image. The music will be played from the pre- defined files, depending on the emotion.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"27 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114059939","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640858
Xue‐cheng Bian
Party building is the core driving force to lead the work of grass-roots tax departments forward. Strengthening the party building of grass-roots tax departments plays an extremely important role in promoting the tax cause. In this form, the party's grass-roots construction is also in a major transformation stage. The government, state-owned enterprises and colleges all attach great importance to the management of the construction of grass-roots party organizations. The software development environment of this system is visual studio 2015 and opencv 3.4.2. The core code is written by C + +, and the software interface is written by C #. In this paper, many cases are tested and the test results are counted. The test results show that the system can accurately detect and track moving targets.
党的建设是领导基层税务部门工作向前发展的核心动力。加强基层税务部门的党建工作，对促进税收事业的发展具有极其重要的作用。在这种形式下，党的基层建设也处于重大转型阶段。政府、国有企业和高校都十分重视基层党组织建设的管理工作。本系统的软件开发环境为visual studio 2015和opencv 3.4.2。核心代码用c++编写，软件接口用c#编写。本文对多个案例进行了测试，并对测试结果进行了统计。测试结果表明，该系统能够准确地检测和跟踪运动目标。
{"title":"Design and Application of Digital Party Building Cloud Platform based on C# and Opencv","authors":"Xue‐cheng Bian","doi":"10.1109/I-SMAC52330.2021.9640858","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640858","url":null,"abstract":"Party building is the core driving force to lead the work of grass-roots tax departments forward. Strengthening the party building of grass-roots tax departments plays an extremely important role in promoting the tax cause. In this form, the party's grass-roots construction is also in a major transformation stage. The government, state-owned enterprises and colleges all attach great importance to the management of the construction of grass-roots party organizations. The software development environment of this system is visual studio 2015 and opencv 3.4.2. The core code is written by C + +, and the software interface is written by C #. In this paper, many cases are tested and the test results are counted. The test results show that the system can accurately detect and track moving targets.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114157697","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640952
Sandhya Vidyashankar, G. Srinivasa
The rise of COVID-19 has precipitated an increased importance of cleaning and sanitation, ideally without human intervention. This paper proposes a solution to meet this emerging need by means of a low-cost fully autonomous robot equipped with pumps for sanitation spray. The robot is designed for disinfection of corridors such as those in grocery stores, hotels etc., using the readily available peroxide disinfectant. It is controlled using an Arduino Uno and can efficiently avoid obstacles. For further convenience, the robot design is modular to ensure protection of the electronics as well as ease of charging and unskilled operation.
{"title":"Low-cost Robot for Autonomous Disinfection of Corridors","authors":"Sandhya Vidyashankar, G. Srinivasa","doi":"10.1109/I-SMAC52330.2021.9640952","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640952","url":null,"abstract":"The rise of COVID-19 has precipitated an increased importance of cleaning and sanitation, ideally without human intervention. This paper proposes a solution to meet this emerging need by means of a low-cost fully autonomous robot equipped with pumps for sanitation spray. The robot is designed for disinfection of corridors such as those in grocery stores, hotels etc., using the readily available peroxide disinfectant. It is controlled using an Arduino Uno and can efficiently avoid obstacles. For further convenience, the robot design is modular to ensure protection of the electronics as well as ease of charging and unskilled operation.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114458281","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640710
D. Sandeep, G. Bethel
In this paper there is comparison of four different machine learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Fuzzy logic and Genetic algorithm on Wisconsin Breast Cancer Diagnosis (WBCD) dataset for the detection of breast cancer in women. The test accuracies are compared to show the efficient algorithm for the detection of breast cancer using those algorithms. The dataset is partitioned to 70% training data and 30% testing data. The results for the applied algorithms are CNN acquired 96.49% accuracy, RNN acquired 63.15% accuracy, fuzzy logic acquired 88.81% accuracy, and genetic algorithm acquired 80.399% accuracy.
{"title":"Accurate Breast Cancer Detection and Classification by Machine Learning Approach","authors":"D. Sandeep, G. Bethel","doi":"10.1109/I-SMAC52330.2021.9640710","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640710","url":null,"abstract":"In this paper there is comparison of four different machine learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Fuzzy logic and Genetic algorithm on Wisconsin Breast Cancer Diagnosis (WBCD) dataset for the detection of breast cancer in women. The test accuracies are compared to show the efficient algorithm for the detection of breast cancer using those algorithms. The dataset is partitioned to 70% training data and 30% testing data. The results for the applied algorithms are CNN acquired 96.49% accuracy, RNN acquired 63.15% accuracy, fuzzy logic acquired 88.81% accuracy, and genetic algorithm acquired 80.399% accuracy.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121882","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640721
Soham Parlikar, Gauri Karnik
Solar energy is an emerging source of electricity in today’s world, and It has been playing an eminent role in generating maximum energy to comply with everyday needs. Solar energy totally depends on the sun’s irradiation and the various sun path angles, so to achieve maximum efficiency, the solar panels need to be facing the direction with maximum solar irradiation. As solar panels are mainly placed on the top of buildings or terraces, to retain the elegance of the building, solar panels can be arranged in specific dynamically arranged patterns, which can be used to visualize the waving effect. This paper proposes a novel method to incorporate the use of 6 DoF parallel manipulators attached to linear movable XY axes, to achieve the tracking of sun path for gaining maximum efficiency and to depict various visual motions such as waves, swarm movement of solar panels in terms of architectural efficacy.
{"title":"Swarm solar rooftop system using 6 DoF parallel manipulators and two axes linear movement","authors":"Soham Parlikar, Gauri Karnik","doi":"10.1109/I-SMAC52330.2021.9640721","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640721","url":null,"abstract":"Solar energy is an emerging source of electricity in today’s world, and It has been playing an eminent role in generating maximum energy to comply with everyday needs. Solar energy totally depends on the sun’s irradiation and the various sun path angles, so to achieve maximum efficiency, the solar panels need to be facing the direction with maximum solar irradiation. As solar panels are mainly placed on the top of buildings or terraces, to retain the elegance of the building, solar panels can be arranged in specific dynamically arranged patterns, which can be used to visualize the waving effect. This paper proposes a novel method to incorporate the use of 6 DoF parallel manipulators attached to linear movable XY axes, to achieve the tracking of sun path for gaining maximum efficiency and to depict various visual motions such as waves, swarm movement of solar panels in terms of architectural efficacy.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122210656","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640902
Moin Hasan, Mohammad Anwarul Siddique
Cloud computing draws immense attraction of the researchers worldwide. It has now become a base paradigm of almost every growing organization. To carry out fruitful research, rigorous experimentation is always required. Commercially, large-scale cloud data centers consist of tens of thousands of physical servers to fulfil the users’ requests across the globe. Therefore, it is not feasible for every researcher to conduct the research experiments and test their proposed algorithms/methods/frameworks over the real cloud environment. Alternately, simulation experiments can be performed. To perform the simulation experiments, standard and research-oriented mathematical modelling of the cloud architecture is required which can be easily implemented using any of the programming languages. To this requirement, this article discusses such a mathematical model of cloud computing architecture consisting of different cloud entities. The discussed model can be easily implemented using any programming language or simulator to perform the research experiments.
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