Pub Date : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987364
Shannmukha Naga Raju Vonteddu, P. Nunna, P. Subramanian, V. Gopu, M. Nagarajan, G. Diwakar
In electric vehicles (EV), one or more electric motors are operated by energy stored in rechargeable batteries. In response to the increased interest in EVs, research into their modelling and simulation has operational variables alter depending on driving conditions, making it difficult to retain control. In the MATLAB/Simulink environment, the transfer function model of the EV is used for design and analysis purposes. In this work, the advanced Back Propagation Neural Network-based Proportional Integral Derivative (BPNN-PID) controller is designed to control the speed of the EV. To identify the effectiveness of the BPNN-PID controller the two conventional controllers fuzzy and PID are used. The error metrics are used to analyse the controller performance. The error metrics employed in this work are Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Frror (ITAE).
{"title":"PID Controller based on BP Neural Network for Speed Control of Electric Vehicle","authors":"Shannmukha Naga Raju Vonteddu, P. Nunna, P. Subramanian, V. Gopu, M. Nagarajan, G. Diwakar","doi":"10.1109/I-SMAC55078.2022.9987364","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987364","url":null,"abstract":"In electric vehicles (EV), one or more electric motors are operated by energy stored in rechargeable batteries. In response to the increased interest in EVs, research into their modelling and simulation has operational variables alter depending on driving conditions, making it difficult to retain control. In the MATLAB/Simulink environment, the transfer function model of the EV is used for design and analysis purposes. In this work, the advanced Back Propagation Neural Network-based Proportional Integral Derivative (BPNN-PID) controller is designed to control the speed of the EV. To identify the effectiveness of the BPNN-PID controller the two conventional controllers fuzzy and PID are used. The error metrics are used to analyse the controller performance. The error metrics employed in this work are Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Frror (ITAE).","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"27 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129498433","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987252
Shweta Sharma, Poonam Tanwar, Ankur Yadav, B. K. Sairam, Sahil Jaswal
Artificial intelligence (AI) is a technique in which computers are designed to do tasks just like humans, they are designed to think, walk, talk and do anything that a living thing can do. Machine Learning (ML) is a field of research devoted to understanding and ’learning’ building methods, that is, methods that improve data to improve the performance of a particular set of tasks. This study is concerned with combining data of pollutants, meteorological, and traffic data with statistical temporal-spatial feature engineering to provide multi-step-ahead air quality forecasts for 24 and 48 hours. It examines a multivariate time series approach to modeling and forecasting the pollution of PM2.5, PM10, and NO2 at three air quality stations in India. The data-driven approach is thus believed to be an excellent complement for the knowledge-driven model.
{"title":"Critical Review of Air Quality Prediction using Machine Learning Techniques","authors":"Shweta Sharma, Poonam Tanwar, Ankur Yadav, B. K. Sairam, Sahil Jaswal","doi":"10.1109/I-SMAC55078.2022.9987252","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987252","url":null,"abstract":"Artificial intelligence (AI) is a technique in which computers are designed to do tasks just like humans, they are designed to think, walk, talk and do anything that a living thing can do. Machine Learning (ML) is a field of research devoted to understanding and ’learning’ building methods, that is, methods that improve data to improve the performance of a particular set of tasks. This study is concerned with combining data of pollutants, meteorological, and traffic data with statistical temporal-spatial feature engineering to provide multi-step-ahead air quality forecasts for 24 and 48 hours. It examines a multivariate time series approach to modeling and forecasting the pollution of PM2.5, PM10, and NO2 at three air quality stations in India. The data-driven approach is thus believed to be an excellent complement for the knowledge-driven model.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127496205","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987247
Chong Jun Yoon, R. Lakshmanan, S. Selvaperumal, H. M. Rosli
The main aim of this research work is to develop an integrated approach for protection system using sensor-based microcontroller and IOT techniques. In this proposed method, a Graphical User Interface using NodeRed was developed to demonstrate the proposed system. The performance of the developed system is evaluated by testing the accuracy of current and temperature according to overload. The proposed system has 90% of accuracy of current. The proposed system consists of manually control and automatically control to cut the three phase power supply to protect the induction motor. Finally, the system proved to be very convenient in protecting and monitoring the state of three phase induction motor.
{"title":"IoT based Overload Protection System for Three Phase Induction Motor","authors":"Chong Jun Yoon, R. Lakshmanan, S. Selvaperumal, H. M. Rosli","doi":"10.1109/I-SMAC55078.2022.9987247","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987247","url":null,"abstract":"The main aim of this research work is to develop an integrated approach for protection system using sensor-based microcontroller and IOT techniques. In this proposed method, a Graphical User Interface using NodeRed was developed to demonstrate the proposed system. The performance of the developed system is evaluated by testing the accuracy of current and temperature according to overload. The proposed system has 90% of accuracy of current. The proposed system consists of manually control and automatically control to cut the three phase power supply to protect the induction motor. Finally, the system proved to be very convenient in protecting and monitoring the state of three phase induction motor.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127513975","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987309
S. Sunori, M. Lohani, Dr Sudhanshu Maurya, M. Manu, S. Arora, Amit Mittal, P. Juneja
At present, electric vehicle has become a subject of curiosity for a common man, and an area of research and innovation for numerous researchers and inventors worldwide. The point of attraction is the features owned by an electric vehicle that are not there in the conventional vehicles. The difference between these two is all about the dc battery taking the position of IC engine. This paper addresses the model identification of an electric vehicle. The raw data set with numerous input and output values has been used for identifying the mathematical model of the process. Four different mathematical models have been identified using the MATLAB. Finally their fitness is compared.
{"title":"Model Identification of Electric Vehicle System","authors":"S. Sunori, M. Lohani, Dr Sudhanshu Maurya, M. Manu, S. Arora, Amit Mittal, P. Juneja","doi":"10.1109/I-SMAC55078.2022.9987309","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987309","url":null,"abstract":"At present, electric vehicle has become a subject of curiosity for a common man, and an area of research and innovation for numerous researchers and inventors worldwide. The point of attraction is the features owned by an electric vehicle that are not there in the conventional vehicles. The difference between these two is all about the dc battery taking the position of IC engine. This paper addresses the model identification of an electric vehicle. The raw data set with numerous input and output values has been used for identifying the mathematical model of the process. Four different mathematical models have been identified using the MATLAB. Finally their fitness is compared.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"110 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132865632","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987403
Yojan Chitkara
The proliferation of portable applications has become a driving force for low power design making it crucial in the development of new processor architectures. Accompanying this is a scaling down of processor nodes which has caused many small channel effects to become more prominent eventually leading to a slow-down in CPU scaling. Smaller nodes in theory could provide better performance at higher frequencies but the apparent slow down has led to a saturation in performance and clock frequencies. This has led to the adoption of heterogeneous computing as a sustainable alternative in computing environments. Graphics Processor Units have gained popularity as a powerful “CPU Co-processor” by reducing the immense workloads on these Processing Units in the computing environments. However, such systems currently lack an effective methodology for power and performance modelling for design optimization. This research study presents a review on the basics of a Graphics Processing unit and the requirement of modelling for power and performance using statistical techniques that help optimize its design to obtain better perf-per-watt results. Methodologies used to obtain prioritized features that affect the power consumed and remove any correlations in data to prevent skewing are also discussed to build an effective Power Model.
{"title":"A Review on Statistical Power Modelling for a Graphics Processing Unit (GPU)","authors":"Yojan Chitkara","doi":"10.1109/I-SMAC55078.2022.9987403","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987403","url":null,"abstract":"The proliferation of portable applications has become a driving force for low power design making it crucial in the development of new processor architectures. Accompanying this is a scaling down of processor nodes which has caused many small channel effects to become more prominent eventually leading to a slow-down in CPU scaling. Smaller nodes in theory could provide better performance at higher frequencies but the apparent slow down has led to a saturation in performance and clock frequencies. This has led to the adoption of heterogeneous computing as a sustainable alternative in computing environments. Graphics Processor Units have gained popularity as a powerful “CPU Co-processor” by reducing the immense workloads on these Processing Units in the computing environments. However, such systems currently lack an effective methodology for power and performance modelling for design optimization. This research study presents a review on the basics of a Graphics Processing unit and the requirement of modelling for power and performance using statistical techniques that help optimize its design to obtain better perf-per-watt results. Methodologies used to obtain prioritized features that affect the power consumed and remove any correlations in data to prevent skewing are also discussed to build an effective Power Model.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126907624","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987291
T. S. Kumar, M. Narendra, U. Arul, S. Kavitha, P. Srinivas
To breathe, the human lungs employ the reverse pressure created by the diaphragm’s contraction motion to suck in air. A ventilator uses a contrary motion to inflate the lungs via a pumping action. A ventilator mechanism must be capable of delivering between 10 and 30 breaths per minute, with the option to regulate ascending increments in sets of two. In addition, the ventilator must be able to alter the amount of air forced into the lungs with each breath. The final but not least option is to change the time length for the inhale to exhalation ratio. Aside from that, the respirator must be able to concurrently regulate the patient’s blood oxygen concentration and exhaled pulmonary pressure to prevent over/under air pressure. The ventilator we design and construct using arduino meets all of these parameters in order to provide a dependable but economical ventilator to aid in pandemic situations. To push the ventilation bag, we employ a silicon ventilation bag linked to a servo motor and a one-side push mechanism.
{"title":"Design of a Smart Cloud Controlled based Artificial Ventilator Device Controller using Patients Vital Information in a Cloud Data Logs","authors":"T. S. Kumar, M. Narendra, U. Arul, S. Kavitha, P. Srinivas","doi":"10.1109/I-SMAC55078.2022.9987291","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987291","url":null,"abstract":"To breathe, the human lungs employ the reverse pressure created by the diaphragm’s contraction motion to suck in air. A ventilator uses a contrary motion to inflate the lungs via a pumping action. A ventilator mechanism must be capable of delivering between 10 and 30 breaths per minute, with the option to regulate ascending increments in sets of two. In addition, the ventilator must be able to alter the amount of air forced into the lungs with each breath. The final but not least option is to change the time length for the inhale to exhalation ratio. Aside from that, the respirator must be able to concurrently regulate the patient’s blood oxygen concentration and exhaled pulmonary pressure to prevent over/under air pressure. The ventilator we design and construct using arduino meets all of these parameters in order to provide a dependable but economical ventilator to aid in pandemic situations. To push the ventilation bag, we employ a silicon ventilation bag linked to a servo motor and a one-side push mechanism.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"233 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123193979","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987292
R. Pavaiyarkarasi, R. Ramu, G. Sahaana, L. Saravanan, R. Begam, R. Prabu
As innovation for transmitting data has advanced exponentially, new avenues for protecting sensitive information have emerged up. Over the last several decades, many different strategies, such as steganography and cryptography, have been developed to safeguard sensitive information. As the use of IoT devices in healthcare has grown exponentially, concerns about patient privacy and confidentiality have surfaced as important roadblocks for healthcare service systems. Security in device-to-device communication is a challenging subject. There are a plethora of existing cryptographic techniques for use, such as Data Encryption Standard (DES), Rivest-Shamir-Adleman (RSA), and Advanced Encryption Standard. In this research, we provide hybrid security architecture for safeguarding medical image files that include interpretive text. The proposed scheme uses 2D-DWT to encrypt and conceal sensitive information. Both color and black-and-white photos are used as text covers. The proposed system’s efficacy was evaluated using a battery of tests that included PSNR, SSIM, MSE, and Correlation. The suggested model disguised sensitive patient information in a way that was comparable to traditional methods in terms of throughput, invisibility, and damage to the received steno-image. To implement the suggested system, we turn to MATLAB, with throughput and execution time serving as key metrics for evaluation.
{"title":"A Hybrid Security Model for the Protection of Diagnostic Text Data in Medical Images over Internet of Things","authors":"R. Pavaiyarkarasi, R. Ramu, G. Sahaana, L. Saravanan, R. Begam, R. Prabu","doi":"10.1109/I-SMAC55078.2022.9987292","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987292","url":null,"abstract":"As innovation for transmitting data has advanced exponentially, new avenues for protecting sensitive information have emerged up. Over the last several decades, many different strategies, such as steganography and cryptography, have been developed to safeguard sensitive information. As the use of IoT devices in healthcare has grown exponentially, concerns about patient privacy and confidentiality have surfaced as important roadblocks for healthcare service systems. Security in device-to-device communication is a challenging subject. There are a plethora of existing cryptographic techniques for use, such as Data Encryption Standard (DES), Rivest-Shamir-Adleman (RSA), and Advanced Encryption Standard. In this research, we provide hybrid security architecture for safeguarding medical image files that include interpretive text. The proposed scheme uses 2D-DWT to encrypt and conceal sensitive information. Both color and black-and-white photos are used as text covers. The proposed system’s efficacy was evaluated using a battery of tests that included PSNR, SSIM, MSE, and Correlation. The suggested model disguised sensitive patient information in a way that was comparable to traditional methods in terms of throughput, invisibility, and damage to the received steno-image. To implement the suggested system, we turn to MATLAB, with throughput and execution time serving as key metrics for evaluation.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116571220","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987301
A. Goel, Aditi Rai, Anushree Narain, Ashish Richard, Kunal Kumar
Voting is the essential element for each nation to express one’s choice. Nowadays, Electronic Voting Machines (EVMs) are used to poll which may be tampered resulting in incorrect election results. Therefore, an online voting system has been introduced in this research. An Electronic Voting (E-Voting) machine is a balloting machine wherein the election opinions are notated, saved, stored, and processed digitally, which makes the balloting control project complicated than the conventional paper based method. The Election Commission forms elections and enlist party candidates along with the parties for contesting the election. This paper works with the following ideas by having the two different sets of modules: election commission and the voters. An election’s REST API is arranged on Ethereum’s Blockchain, which is the front end. The votes are then stored on the blockchain architecture, to which the Election Commission grants the number of votes. However, there are some limitations due to the fact that the blockchain architecture cannot run on the main net as it must be hosted, and a separate web3 provider must be used for interacting with it due to the lack of public API availability.
{"title":"Trusted Vote: Reorienting eVoting using Blockchain","authors":"A. Goel, Aditi Rai, Anushree Narain, Ashish Richard, Kunal Kumar","doi":"10.1109/I-SMAC55078.2022.9987301","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987301","url":null,"abstract":"Voting is the essential element for each nation to express one’s choice. Nowadays, Electronic Voting Machines (EVMs) are used to poll which may be tampered resulting in incorrect election results. Therefore, an online voting system has been introduced in this research. An Electronic Voting (E-Voting) machine is a balloting machine wherein the election opinions are notated, saved, stored, and processed digitally, which makes the balloting control project complicated than the conventional paper based method. The Election Commission forms elections and enlist party candidates along with the parties for contesting the election. This paper works with the following ideas by having the two different sets of modules: election commission and the voters. An election’s REST API is arranged on Ethereum’s Blockchain, which is the front end. The votes are then stored on the blockchain architecture, to which the Election Commission grants the number of votes. However, there are some limitations due to the fact that the blockchain architecture cannot run on the main net as it must be hosted, and a separate web3 provider must be used for interacting with it due to the lack of public API availability.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131471476","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987282
M. Bharathi, K. Geetha, P. Mani, G. N. Samuel Vijayakumar, K. Srinivasan, K. R. Kumar
In this technology world, technology is increasing by giving solutions to many problems. By using this technology, a solution for decreasing air pollution is implemented. The main cause of increasing air pollution is using various kinds of vehicles that run on combustion engines for transportation utilities. The implementation of Electric Vehicle (EVs) can resolve this air pollution problem and keeps the environment as pollution-free air and the world can survive in pure air. EVs are like machines that run on a charging battery. An EV’s condition is depending on the battery’s performance. The parameters for the battery’s condition the voltage, current, and temperature. By using these parameters State of Charge (SOC) is determined. These performances are monitored as Battery Management System (BMS). In this paper, the EV monitoring system is implemented using the combination of Artificial Intelligence (AI) and Internet of Things (IoT) interfacing by the sensors in the vehicle’s battery, and to the cloud. The performance of the battery is monitored using the mobile application of the cloud.
{"title":"AI and IoT-based Electric Vehicle Monitoring System","authors":"M. Bharathi, K. Geetha, P. Mani, G. N. Samuel Vijayakumar, K. Srinivasan, K. R. Kumar","doi":"10.1109/I-SMAC55078.2022.9987282","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987282","url":null,"abstract":"In this technology world, technology is increasing by giving solutions to many problems. By using this technology, a solution for decreasing air pollution is implemented. The main cause of increasing air pollution is using various kinds of vehicles that run on combustion engines for transportation utilities. The implementation of Electric Vehicle (EVs) can resolve this air pollution problem and keeps the environment as pollution-free air and the world can survive in pure air. EVs are like machines that run on a charging battery. An EV’s condition is depending on the battery’s performance. The parameters for the battery’s condition the voltage, current, and temperature. By using these parameters State of Charge (SOC) is determined. These performances are monitored as Battery Management System (BMS). In this paper, the EV monitoring system is implemented using the combination of Artificial Intelligence (AI) and Internet of Things (IoT) interfacing by the sensors in the vehicle’s battery, and to the cloud. The performance of the battery is monitored using the mobile application of the cloud.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"395 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134457572","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9986499
Araveeti V Sai Srujan, Medikonda Sandeep, K. S. V. Lakshmi, Gogineni Nithin Teja
Face Frontalization refers to generating the frontal view from a side faced view. There are a lot of crime scenes going on today in which a frontal face of the suscept is not perfectly visible. Even though many face recognition systems exist, it is still not possible to have a clear front view of the suspect. In order to find a clear face, the existing image should be rotated, this is where the face frontalization comes into action. This model will be able to rotate the available side face image in order to find a frontal face. To achieve this, the Generative Adversarial Networks (GAN) are used. The Generative Adversarial Network (GAN) consists of a discriminator and generator. The discriminator goes deep into the layers from the top layers to all the way leaving to the bottom most layers in order to get a deep understanding on the input image. The generator works in contrast to the discriminator and regain all the deep layers that are deconvoluted by the discriminator. Finally, both the generator and the discriminator will combinedly work to form a Generative Adversarial Network (GAN) and generate output based on the input image.
{"title":"Generative Adversarial Networks based Face Fractalization by using GAN","authors":"Araveeti V Sai Srujan, Medikonda Sandeep, K. S. V. Lakshmi, Gogineni Nithin Teja","doi":"10.1109/I-SMAC55078.2022.9986499","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9986499","url":null,"abstract":"Face Frontalization refers to generating the frontal view from a side faced view. There are a lot of crime scenes going on today in which a frontal face of the suscept is not perfectly visible. Even though many face recognition systems exist, it is still not possible to have a clear front view of the suspect. In order to find a clear face, the existing image should be rotated, this is where the face frontalization comes into action. This model will be able to rotate the available side face image in order to find a frontal face. To achieve this, the Generative Adversarial Networks (GAN) are used. The Generative Adversarial Network (GAN) consists of a discriminator and generator. The discriminator goes deep into the layers from the top layers to all the way leaving to the bottom most layers in order to get a deep understanding on the input image. The generator works in contrast to the discriminator and regain all the deep layers that are deconvoluted by the discriminator. Finally, both the generator and the discriminator will combinedly work to form a Generative Adversarial Network (GAN) and generate output based on the input image.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134495783","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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