Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009087
Harshavardhan Vibhandik, Sudhanshu Kale, Samiksha Shende, M. Goudar
Healthcare sectors such as hospitals, nursing homes, medical offices, and hospice homes encountered several obstacles due to the outbreak of Covid-19. Wearing a mask, social distancing and sanitization are some of the most effective methods that have been proven to be essential to minimize the virus spread. Lately, medical executives have been appointed to monitor the virus spread and encourage the individuals to follow cautious instructions that have been provided to them. To solve the aforementioned challenges, this research study proposes an autonomous medical assistance robot. The proposed autonomous robot is completely service-based, which helps to monitor whether or not people are wearing a mask while entering any health care facility and sanitizes the people after sending a warning to wear a mask by using the image processing and computer vision technique. The robot not only monitors but also promotes social distancing by giving precautionary warnings to the people in healthcare facilities. The robot can assist the health care officials carrying the necessities of the patent while following them for maintaining a touchless environment. With thorough simulative testing and experiments, results have been finally validated.
{"title":"Medical Assistance Robot with capabilities of Mask Detection with Automatic Sanitization and Social Distancing Detection/ Awareness","authors":"Harshavardhan Vibhandik, Sudhanshu Kale, Samiksha Shende, M. Goudar","doi":"10.1109/ICECA55336.2022.10009087","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009087","url":null,"abstract":"Healthcare sectors such as hospitals, nursing homes, medical offices, and hospice homes encountered several obstacles due to the outbreak of Covid-19. Wearing a mask, social distancing and sanitization are some of the most effective methods that have been proven to be essential to minimize the virus spread. Lately, medical executives have been appointed to monitor the virus spread and encourage the individuals to follow cautious instructions that have been provided to them. To solve the aforementioned challenges, this research study proposes an autonomous medical assistance robot. The proposed autonomous robot is completely service-based, which helps to monitor whether or not people are wearing a mask while entering any health care facility and sanitizes the people after sending a warning to wear a mask by using the image processing and computer vision technique. The robot not only monitors but also promotes social distancing by giving precautionary warnings to the people in healthcare facilities. The robot can assist the health care officials carrying the necessities of the patent while following them for maintaining a touchless environment. With thorough simulative testing and experiments, results have been finally validated.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124943639","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009050
M. G. Kumar, R. Maheswari, M. Bakrutheen, B. Vigneshwaran
In the present decade, biodegradability is the most preferable and viable alternative solution for all kind of applications, which is also true for high voltage applications. In recent upgrades, researchers can suggest using natural oils for environmental concerns. This paper deals with the idea of blending petroleum based mineral oil (PBMO) and comestible corn oil (CCO) for high voltage liquid insulation. Conventional insulating oil has a high breakdown voltage, low viscosity and pour point, and a high flash and fire point. The main goal of the work is to navigate the blend oil ratio concentration to enhance the performance and improve the dielectric properties of insulating oil. As per standards, in order to verify the suitability of the fundamental oil test, it is taken and analyzed in all proportions. When compared to conventional oil, a blend oil ratio has exhibits the desired performance. Furthermore, the result of the fuzzy logic approach (FLA) is determined to improve the compactness of the research.
{"title":"Fuzzy Logic Based Efficient Blending of Mineral and Vegetable Oil as Alternate Liquid Insulation","authors":"M. G. Kumar, R. Maheswari, M. Bakrutheen, B. Vigneshwaran","doi":"10.1109/ICECA55336.2022.10009050","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009050","url":null,"abstract":"In the present decade, biodegradability is the most preferable and viable alternative solution for all kind of applications, which is also true for high voltage applications. In recent upgrades, researchers can suggest using natural oils for environmental concerns. This paper deals with the idea of blending petroleum based mineral oil (PBMO) and comestible corn oil (CCO) for high voltage liquid insulation. Conventional insulating oil has a high breakdown voltage, low viscosity and pour point, and a high flash and fire point. The main goal of the work is to navigate the blend oil ratio concentration to enhance the performance and improve the dielectric properties of insulating oil. As per standards, in order to verify the suitability of the fundamental oil test, it is taken and analyzed in all proportions. When compared to conventional oil, a blend oil ratio has exhibits the desired performance. Furthermore, the result of the fuzzy logic approach (FLA) is determined to improve the compactness of the research.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122009833","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009062
Khammampati R Sreejyothi, Balakrishnakothapalli, KALAGOTLA CHENCHIREDDY, Shabbier Ahmed Sydu, V. Kumar, W. Sultana
This paper presents a bi-directional battery charger circuit. The implemented circuit is controlled by a PI controller. The DC to DC converters are plays a key role in solar power plants and battery charging stations. It is possible to charge and discharge batteries using this bi-directional DC to DC converter. The converter functions as a boost converter when it is discharging and as a buck converter when it is charging. The bi-directional converter is managed by the closed-loop PI controller. These paper simulation results are verified in MATLAB/Simulink software during battery charging and discharging mode. The simulation results during charging and discharging mode reached reference values.
{"title":"Bidirectional Battery Charger Circuit using Buck/Boost Converter","authors":"Khammampati R Sreejyothi, Balakrishnakothapalli, KALAGOTLA CHENCHIREDDY, Shabbier Ahmed Sydu, V. Kumar, W. Sultana","doi":"10.1109/ICECA55336.2022.10009062","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009062","url":null,"abstract":"This paper presents a bi-directional battery charger circuit. The implemented circuit is controlled by a PI controller. The DC to DC converters are plays a key role in solar power plants and battery charging stations. It is possible to charge and discharge batteries using this bi-directional DC to DC converter. The converter functions as a boost converter when it is discharging and as a buck converter when it is charging. The bi-directional converter is managed by the closed-loop PI controller. These paper simulation results are verified in MATLAB/Simulink software during battery charging and discharging mode. The simulation results during charging and discharging mode reached reference values.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122841584","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009188
Pallavi, Vishal Bharti
Digital forensics is the study of discovering evidence pertaining to digital crimes & attacks. To monitor and investigate cloud-based crimes, Cloud Forensics (CF) operates as a subfield of Digital Forensics. Cloud computing is a rapidly evolving, worldwide network of interconnected servers. Therefore, Cloud Forensics belongs to Network Forensics, which is a subset of Digital Forensics. There is yet to be an overt forensic revolution in the cloud service, which includes cloud businesses, cloud service providers, & cloud service customers. They cannot guarantee the security of their system or quality of their services that aid in criminal & cybercrime investigations without this crucial forensic capacity. This research study analyzes the forensics procedure, the difficulties of CF, and the tools available to help the investigation. In the context of Blockchain Technology (BT), the approaches to solutions and future possibilities of CF have been outlined. These investigations will pave the path for future scholars to have a deeper grasp of the difficulties and develop innovative solutions.
{"title":"A Comprehensive Review of Cloud Forensics and Blockchain Based Solutions","authors":"Pallavi, Vishal Bharti","doi":"10.1109/ICECA55336.2022.10009188","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009188","url":null,"abstract":"Digital forensics is the study of discovering evidence pertaining to digital crimes & attacks. To monitor and investigate cloud-based crimes, Cloud Forensics (CF) operates as a subfield of Digital Forensics. Cloud computing is a rapidly evolving, worldwide network of interconnected servers. Therefore, Cloud Forensics belongs to Network Forensics, which is a subset of Digital Forensics. There is yet to be an overt forensic revolution in the cloud service, which includes cloud businesses, cloud service providers, & cloud service customers. They cannot guarantee the security of their system or quality of their services that aid in criminal & cybercrime investigations without this crucial forensic capacity. This research study analyzes the forensics procedure, the difficulties of CF, and the tools available to help the investigation. In the context of Blockchain Technology (BT), the approaches to solutions and future possibilities of CF have been outlined. These investigations will pave the path for future scholars to have a deeper grasp of the difficulties and develop innovative solutions.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126067193","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009502
Mohd Javeed Mehdi, Suram Purna Sai Chandra, M. Sravya, Gooty Hamsitha, Veggilapu Sai Krishna
Accidents are more common in mountainous areas, and as a result, more people lose their lives. The roads in this are a are curved and steep, making it difficult for drivers to see vehicles on the other side. Most accidents occur in hill stations, according to the report (i.e., 13% of all accidents). Because of this, we came up with the concept of utilizing embedded systems technology to solve the problem at hand. A model for reducing the number of accidents in hill stations is proposed in this research. Hair bend pin curves, valley points, and vehicle skidding are the three most common accident sites in the mountains. Our proposed system is created utilizing an Arduino Uno board with IR sensors and Ultrasonic (UR) sensors, and we are proposing to fix it at these dangerous spots. On either side of the road's hairpin bend, IR sensors detect vehicle movement and relay that information to a traffic module on the other side. The valley point has a UR sensor, which detects vehicles approaching the valley point and sounds an alert with buzzers. The primary goal of the proposed model is to reduce the death rate in mountainous stations by preventing accidents.
{"title":"Pre-Crash Sensing and Warning System in Hill Station","authors":"Mohd Javeed Mehdi, Suram Purna Sai Chandra, M. Sravya, Gooty Hamsitha, Veggilapu Sai Krishna","doi":"10.1109/ICECA55336.2022.10009502","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009502","url":null,"abstract":"Accidents are more common in mountainous areas, and as a result, more people lose their lives. The roads in this are a are curved and steep, making it difficult for drivers to see vehicles on the other side. Most accidents occur in hill stations, according to the report (i.e., 13% of all accidents). Because of this, we came up with the concept of utilizing embedded systems technology to solve the problem at hand. A model for reducing the number of accidents in hill stations is proposed in this research. Hair bend pin curves, valley points, and vehicle skidding are the three most common accident sites in the mountains. Our proposed system is created utilizing an Arduino Uno board with IR sensors and Ultrasonic (UR) sensors, and we are proposing to fix it at these dangerous spots. On either side of the road's hairpin bend, IR sensors detect vehicle movement and relay that information to a traffic module on the other side. The valley point has a UR sensor, which detects vehicles approaching the valley point and sounds an alert with buzzers. The primary goal of the proposed model is to reduce the death rate in mountainous stations by preventing accidents.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129960683","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009360
A. Bhavana, K. Shalini Reddy, Madhu, D. Praveen Kumar
Deaf and dumb persons who are physically impaired use sign language to communicate. The main obstacles that have prevented much ASL study have been incorporated characteristics and local dialect variance in this work sets. To communicate with them, sign language should be learned. Peer groups are typically where learning happens. There aren't many study resources accessible for learning signs. The process of learning sign language is therefore a very challenging undertaking. Finger spelling is the first stage of sign learning, and it is also used when the signer is unfamiliar of the equivalent sign or when there isn't one. The majority of the currently available sign language learning systems rely on expensive external sensors. By gathering a dataset and using various feature extraction approaches to extract relevant data, this research discipline has been further advanced. The data is then entered into various supervised learning algorithms. The reason why the proposed results differ from existing research work is that in the developed fourfold cross validation, the validation set corresponds to the images of a person, which are different from the people present in the training set. Currently, the fourfold cross validated results are provided for various techniques.
{"title":"Deep Neural Network based Sign Language Detection","authors":"A. Bhavana, K. Shalini Reddy, Madhu, D. Praveen Kumar","doi":"10.1109/ICECA55336.2022.10009360","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009360","url":null,"abstract":"Deaf and dumb persons who are physically impaired use sign language to communicate. The main obstacles that have prevented much ASL study have been incorporated characteristics and local dialect variance in this work sets. To communicate with them, sign language should be learned. Peer groups are typically where learning happens. There aren't many study resources accessible for learning signs. The process of learning sign language is therefore a very challenging undertaking. Finger spelling is the first stage of sign learning, and it is also used when the signer is unfamiliar of the equivalent sign or when there isn't one. The majority of the currently available sign language learning systems rely on expensive external sensors. By gathering a dataset and using various feature extraction approaches to extract relevant data, this research discipline has been further advanced. The data is then entered into various supervised learning algorithms. The reason why the proposed results differ from existing research work is that in the developed fourfold cross validation, the validation set corresponds to the images of a person, which are different from the people present in the training set. Currently, the fourfold cross validated results are provided for various techniques.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129276576","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009575
Anuj Kumar Goel
Due to the growing demand and wide application of microdevices, there is an increase in the demand of microgrippers that can perfectly carry and place the microparts in MEMS Devices. In this paper, grippers are designed in micro dimensions for micro and nano devices. The piezoelectric actuation is used for analyses of designed precise microgrippers. Different piezoelectric materials such as PZT5A, PZT7, Barium Titanate, Barium Sodium Niobate, and Lithium Niobate are modelled and analysed in terms of displacement of arms with stress observation at the actuator ends. PZT5A proves the best material for microgripping effect. COMSOL Multiphysics is the FEA tool used for the design and analysis of microdevices.
{"title":"Comparative Analysis of Different Piezoelectric materials in Design of Microgrippers","authors":"Anuj Kumar Goel","doi":"10.1109/ICECA55336.2022.10009575","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009575","url":null,"abstract":"Due to the growing demand and wide application of microdevices, there is an increase in the demand of microgrippers that can perfectly carry and place the microparts in MEMS Devices. In this paper, grippers are designed in micro dimensions for micro and nano devices. The piezoelectric actuation is used for analyses of designed precise microgrippers. Different piezoelectric materials such as PZT5A, PZT7, Barium Titanate, Barium Sodium Niobate, and Lithium Niobate are modelled and analysed in terms of displacement of arms with stress observation at the actuator ends. PZT5A proves the best material for microgripping effect. COMSOL Multiphysics is the FEA tool used for the design and analysis of microdevices.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130080880","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009181
Rajeshree Parsingbhai Vasava, Hetal A. Joshiara
“lung diseases are now considered as one of the fatal diseases across the globe. However, early detection of lung disease may help in providing earlier treatment since most cases of lung diseases are only detected after they have progressed to advanced stage. Today's healthcare system relies on the recent technological advancements. Lung sound analysis plays a crucial role in the diagnosis of lung disease. Further, the successful navigation of medical system requires the ability to acquire new information and utilize it in new contexts. To perform classification, this research work presents several transfer learning strategies, including ALEXNET, VGGNET, and RES NET for analyzing the lung sounds. To complement the techniques, a Transfer learning model that incorporates a Modified RESNET with a Mel spectrogram of lung sound signals are used to perform classification. These transfer learning models perform efficiently in classifying the lung sounds, which can be later used to diagnose respiratory diseases. This research study analyzes several transfer learning methods and discuss their benefits and drawbacks in identifying four distinct types of lung sounds. Finally, the further research directions on the identification of lung sounds are discussed.”
{"title":"Lung Sounds Identification based On Transfer Learning Approaches : A Review","authors":"Rajeshree Parsingbhai Vasava, Hetal A. Joshiara","doi":"10.1109/ICECA55336.2022.10009181","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009181","url":null,"abstract":"“lung diseases are now considered as one of the fatal diseases across the globe. However, early detection of lung disease may help in providing earlier treatment since most cases of lung diseases are only detected after they have progressed to advanced stage. Today's healthcare system relies on the recent technological advancements. Lung sound analysis plays a crucial role in the diagnosis of lung disease. Further, the successful navigation of medical system requires the ability to acquire new information and utilize it in new contexts. To perform classification, this research work presents several transfer learning strategies, including ALEXNET, VGGNET, and RES NET for analyzing the lung sounds. To complement the techniques, a Transfer learning model that incorporates a Modified RESNET with a Mel spectrogram of lung sound signals are used to perform classification. These transfer learning models perform efficiently in classifying the lung sounds, which can be later used to diagnose respiratory diseases. This research study analyzes several transfer learning methods and discuss their benefits and drawbacks in identifying four distinct types of lung sounds. Finally, the further research directions on the identification of lung sounds are discussed.”","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909535","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009346
R. Shah, Vrunda Shah, Anuja R. Nair, Tarjni Vyas, Shivani Desai, S. Degadwala
Accurate software work estimates is essential to the planning, management, and execution of a successful project on schedule and within budget. The necessity for accurate software work estimates is something that will never go away since both overestimation and underestimate provide substantial barriers to the development of additional software (SEE). Research and practise are aimed at finding the machine learning estimating technique that is most successful for a given set of criteria and data. This is the goal of the research and practise. Most academics working in a particular subject are not aware of the findings of previous studies that investigated different approaches to effort estimate in machine learning. The primary purpose of this investigation is to aid researchers working in the field of software development by assisting them in determining which method of machine learning produces the most promising effort estimate accuracy prediction.
{"title":"Software Effort Estimation using Machine Learning Algorithms","authors":"R. Shah, Vrunda Shah, Anuja R. Nair, Tarjni Vyas, Shivani Desai, S. Degadwala","doi":"10.1109/ICECA55336.2022.10009346","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009346","url":null,"abstract":"Accurate software work estimates is essential to the planning, management, and execution of a successful project on schedule and within budget. The necessity for accurate software work estimates is something that will never go away since both overestimation and underestimate provide substantial barriers to the development of additional software (SEE). Research and practise are aimed at finding the machine learning estimating technique that is most successful for a given set of criteria and data. This is the goal of the research and practise. Most academics working in a particular subject are not aware of the findings of previous studies that investigated different approaches to effort estimate in machine learning. The primary purpose of this investigation is to aid researchers working in the field of software development by assisting them in determining which method of machine learning produces the most promising effort estimate accuracy prediction.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125844205","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 : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009488
Parthiban Aravamudhan, T. Kanimozhi
Today, every IT business uses Cloud Computing since it's scalable and versatile. Its open and distributed nature makes security and privacy a big problem due to intruders. The Internet of Things (IoT) will impact many aspects of our lives due to its rapid development in household appliances, wearable technology, and intelligent sensors. IoT devices are connected, widespread, and low-powered. By 2020, there will be 50 billion Internet of Things (IoT) devices in use worldwide. There have been more IoT-based cyberattacks as a result of the growth of IoT devices, which now easily outweigh desktop PCs. To solve this challenge, new approaches must be developed for spotting assaults from hacked IoT devices. In this regard, machine learning and deep learning should be used as a detective control against IoT attacks. In addition to an introduction of intrusion detection methods, this paper analyses the technologies, protocols, and architecture of IoT networks and reviews the dangers of hacked IoT devices. This study examines methods for recognizing IoT cyberattacks using deep learning and machine learning. Various optimizer algorithms are discussed to improve the quality, efficiency and accuracy of the model.
{"title":"A Comprehensive Survey of Intrusion Detection Systems using Advanced Technologies","authors":"Parthiban Aravamudhan, T. Kanimozhi","doi":"10.1109/ICECA55336.2022.10009488","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009488","url":null,"abstract":"Today, every IT business uses Cloud Computing since it's scalable and versatile. Its open and distributed nature makes security and privacy a big problem due to intruders. The Internet of Things (IoT) will impact many aspects of our lives due to its rapid development in household appliances, wearable technology, and intelligent sensors. IoT devices are connected, widespread, and low-powered. By 2020, there will be 50 billion Internet of Things (IoT) devices in use worldwide. There have been more IoT-based cyberattacks as a result of the growth of IoT devices, which now easily outweigh desktop PCs. To solve this challenge, new approaches must be developed for spotting assaults from hacked IoT devices. In this regard, machine learning and deep learning should be used as a detective control against IoT attacks. In addition to an introduction of intrusion detection methods, this paper analyses the technologies, protocols, and architecture of IoT networks and reviews the dangers of hacked IoT devices. This study examines methods for recognizing IoT cyberattacks using deep learning and machine learning. Various optimizer algorithms are discussed to improve the quality, efficiency and accuracy of the model.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125999522","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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