Pub Date : 2023-01-26DOI: 10.1109/LT58159.2023.10092345
Sammar Z Allam
This research explores machine learnt use-patter of human activities in outdoor and indoor spaces. It proposes scenarios to be used through Generative Adversarial Network for AI-Based use-pattern generative spaces. The study investigates futuristic AI-based life styles and its impact on the architectural spaces and clusters agglomeration. Clusters algorithmic design includes cellular automata and fractals in regards of stable null space as green nodes. Machine learnt use-pattern from daily activities incorporates a dynamic-responsive pixelation of spaces. The research manifest machine learnt algorithmic design and demonstrates IOT generative responsive spaces. A hybrid space of extended spatial reality that complies as well architectural boundaries has resulted using cellular responsive units/cells to include an extended reality (XR) part that supply the space with extended multiple activities. This hybrid space acts as a virtual and a real space that accommodates various functionalities with flexibilities relying on IOT, AI-based and XR technologies.
{"title":"AI-Based Use-Pattern Generative Hybrid Spaces for Indoor and Outdoor Activities","authors":"Sammar Z Allam","doi":"10.1109/LT58159.2023.10092345","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092345","url":null,"abstract":"This research explores machine learnt use-patter of human activities in outdoor and indoor spaces. It proposes scenarios to be used through Generative Adversarial Network for AI-Based use-pattern generative spaces. The study investigates futuristic AI-based life styles and its impact on the architectural spaces and clusters agglomeration. Clusters algorithmic design includes cellular automata and fractals in regards of stable null space as green nodes. Machine learnt use-pattern from daily activities incorporates a dynamic-responsive pixelation of spaces. The research manifest machine learnt algorithmic design and demonstrates IOT generative responsive spaces. A hybrid space of extended spatial reality that complies as well architectural boundaries has resulted using cellular responsive units/cells to include an extended reality (XR) part that supply the space with extended multiple activities. This hybrid space acts as a virtual and a real space that accommodates various functionalities with flexibilities relying on IOT, AI-based and XR technologies.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115911412","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092357
Mirna Ali, Nouf Alsaedi, S. Qaisar
People with disabilities struggle to perform specific tasks throughout their daily life. However, BCI systems are developed to assist people struggling with motor impairment by transforming their thoughts into action. Non-invasive BCI systems use electroencephalogram (EEG) to record brain activities. In this study, we segment the EEG signals and then break the segment down into a few intrinsic mode functions using oscillation mode decomposition. Then the intrinsic mode functions are mined for feature extraction. The features mined are processed by different machine learning algorithms for categorization. Among the different algorithms, K-NN yielded the best results with an overall average accuracy score of 95.48%. This approach can be used in future to develop the brain driven metaverse interactive solutions.
{"title":"Non-Invasive BCI by using EMD and Machine Learning: A Metaverse Interaction Perspective","authors":"Mirna Ali, Nouf Alsaedi, S. Qaisar","doi":"10.1109/LT58159.2023.10092357","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092357","url":null,"abstract":"People with disabilities struggle to perform specific tasks throughout their daily life. However, BCI systems are developed to assist people struggling with motor impairment by transforming their thoughts into action. Non-invasive BCI systems use electroencephalogram (EEG) to record brain activities. In this study, we segment the EEG signals and then break the segment down into a few intrinsic mode functions using oscillation mode decomposition. Then the intrinsic mode functions are mined for feature extraction. The features mined are processed by different machine learning algorithms for categorization. Among the different algorithms, K-NN yielded the best results with an overall average accuracy score of 95.48%. This approach can be used in future to develop the brain driven metaverse interactive solutions.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"770 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115753622","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092321
Lina Almatrafi, Salma Badaam, S. Qaisar
The conventional vehicles use fuels to provide excellent performance. However, conventional vehicles have some cons such as environmental pollution due to exhaust gas emissions that is the reason behind the interest in electric vehicles (EVs) is increasing. It is mainly to reduce the pollution and greenhouse gas (GHG) emissions. In this research, the EV model is implemented via SIMULINK platform with the use of Simscape and Simulink blocks. The implemented model consists of the driving cycles which are connected to the longitudinal driver block. The Driver block is attached to the power controller system. A DC motor is used to move the vehicle body subsystem. Also a battery pack is used to power the EV. The performance of this model is evaluated, based on the speed, state of charge (SoC) of the battery, and power consumption, using three known drive cycles which are Urban Dynamometer Driving Schedule (UDDS), New York City Cycle (NYCC), and the Worldwide Harmonized Light Vehicles Test Procedure (WLTP). A performance comparison for the three considered drive cycles is also made. The findings of this paper shown that the WLTP drive cycle causes the lowest power consumption of 11.113 kW and the SoC value of 87.62%.
{"title":"Electric Vehicle Performance Evaluation Using UDDS, NYCC and WLTP Drive Cycles","authors":"Lina Almatrafi, Salma Badaam, S. Qaisar","doi":"10.1109/LT58159.2023.10092321","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092321","url":null,"abstract":"The conventional vehicles use fuels to provide excellent performance. However, conventional vehicles have some cons such as environmental pollution due to exhaust gas emissions that is the reason behind the interest in electric vehicles (EVs) is increasing. It is mainly to reduce the pollution and greenhouse gas (GHG) emissions. In this research, the EV model is implemented via SIMULINK platform with the use of Simscape and Simulink blocks. The implemented model consists of the driving cycles which are connected to the longitudinal driver block. The Driver block is attached to the power controller system. A DC motor is used to move the vehicle body subsystem. Also a battery pack is used to power the EV. The performance of this model is evaluated, based on the speed, state of charge (SoC) of the battery, and power consumption, using three known drive cycles which are Urban Dynamometer Driving Schedule (UDDS), New York City Cycle (NYCC), and the Worldwide Harmonized Light Vehicles Test Procedure (WLTP). A performance comparison for the three considered drive cycles is also made. The findings of this paper shown that the WLTP drive cycle causes the lowest power consumption of 11.113 kW and the SoC value of 87.62%.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127395312","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092369
Ammar Alzaydi
This paper presents the utilization of polymer and reflective polyester and other flexible films to fabricate deformable rotational mirrors, where the rotation is utilized to help and filter a reflected image impacted by mirror surface impurities. A self-supporting membrane is fabricated using Mylar polyester film, with a diameter of 120mm and a thickness of 1mm. Electromagnetic actuation is used in combination with a magnetic electrode array beneath the mirror membrane to deform the reflective surface and change the location of the focal point. The mechanical properties of the Mylar polyester film are such that the deflection required for focal point position is minimal, thus increasing mirror flexibility and sensitivity when controlled electromagnetically, whilst the fabrication process is simple and potentially low cost. The developed mirror in this paper consists of two similar membranes lying on top of each other, both rotating at equal speeds around the center to ensure electro-magnetic forces used for deflection are spread evenly between each reflective film sector. The developed mirror prototype functionality was successfully demonstrated when used to filter an image using rotational motion and focus an unfocused picture taken by a regular camera. Therefore, the two main features of the developed mirror are: The rotational behaviour of the mirror and its divided surface that give it the ability to filter the impact of surface impurities on the reflected image and the flexibility to concave and change focal point location while in rotation. This design can be implemented on MEMS devices that look to reduce manufacturing costs by dealing with less than perfect reflective surfaces or other example applications that aim to digitize objects (take images) to be used in virtual reality related projects.
{"title":"Adaptive Optics Rotational Design and Electro-Magnetic Actuation","authors":"Ammar Alzaydi","doi":"10.1109/LT58159.2023.10092369","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092369","url":null,"abstract":"This paper presents the utilization of polymer and reflective polyester and other flexible films to fabricate deformable rotational mirrors, where the rotation is utilized to help and filter a reflected image impacted by mirror surface impurities. A self-supporting membrane is fabricated using Mylar polyester film, with a diameter of 120mm and a thickness of 1mm. Electromagnetic actuation is used in combination with a magnetic electrode array beneath the mirror membrane to deform the reflective surface and change the location of the focal point. The mechanical properties of the Mylar polyester film are such that the deflection required for focal point position is minimal, thus increasing mirror flexibility and sensitivity when controlled electromagnetically, whilst the fabrication process is simple and potentially low cost. The developed mirror in this paper consists of two similar membranes lying on top of each other, both rotating at equal speeds around the center to ensure electro-magnetic forces used for deflection are spread evenly between each reflective film sector. The developed mirror prototype functionality was successfully demonstrated when used to filter an image using rotational motion and focus an unfocused picture taken by a regular camera. Therefore, the two main features of the developed mirror are: The rotational behaviour of the mirror and its divided surface that give it the ability to filter the impact of surface impurities on the reflected image and the flexibility to concave and change focal point location while in rotation. This design can be implemented on MEMS devices that look to reduce manufacturing costs by dealing with less than perfect reflective surfaces or other example applications that aim to digitize objects (take images) to be used in virtual reality related projects.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"116 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125752843","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092295
Mai El Seknedy, S. Fawzi
The Speech Emotion Recognition (SER) system is an approach to identify individuals' emotions. This is important for human-machine interface applications and for the emerging Metaverse. This work presents a bilingual Arabic-English speech emotion recognition system based on EYASE and RAVDESS datasets. A novel feature set was composed by using spectral and prosodic parameters to obtain high performance at a low computational cost. Different classification models were applied. These machine learning classifiers are Random Forest, Support Vector Machine, Logistic Regression, Multi-Layer Perceptron, and Ensemble learning. The proposed feature set performance was compared to the "Interspeech 2009" challenge feature set, which is considered a benchmark in the field. Promising results were obtained using the proposed feature sets. SVM resulted in the best emotion recognition rate and execution performance. The best accuracies achieved were 85% on RADVESS, and 64% on EYASE. Ensemble learning detected the valence emotion with 90% on RADVESS, and 87.6% on EYASE.
{"title":"Arabic English Speech Emotion Recognition System","authors":"Mai El Seknedy, S. Fawzi","doi":"10.1109/LT58159.2023.10092295","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092295","url":null,"abstract":"The Speech Emotion Recognition (SER) system is an approach to identify individuals' emotions. This is important for human-machine interface applications and for the emerging Metaverse. This work presents a bilingual Arabic-English speech emotion recognition system based on EYASE and RAVDESS datasets. A novel feature set was composed by using spectral and prosodic parameters to obtain high performance at a low computational cost. Different classification models were applied. These machine learning classifiers are Random Forest, Support Vector Machine, Logistic Regression, Multi-Layer Perceptron, and Ensemble learning. The proposed feature set performance was compared to the \"Interspeech 2009\" challenge feature set, which is considered a benchmark in the field. Promising results were obtained using the proposed feature sets. SVM resulted in the best emotion recognition rate and execution performance. The best accuracies achieved were 85% on RADVESS, and 64% on EYASE. Ensemble learning detected the valence emotion with 90% on RADVESS, and 87.6% on EYASE.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134442648","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092368
Esraa Elgamal, Walaa Medhat, M. A. Elfatah, Nashwa Abdelbaki
In recent years, advances in technology in several industries have resulted in massive data collections on the web. It raises worries about large data security and protection. The advent of Blockchain technology has caused a revolution in the security field for different applications. The distributed ledger is stored on each Blockchain node, which enhances security and data transparency. On the Blockchain network, illegal users are not authorized to undertake any fault transactions. In this article, we will discuss how Blockchain may be employed to secure the big data. We explain the problems that the Blockchain faced with big data and its solutions. We summarize recent works of Blockchain with big data and the present issues and trends. We demonstrate that Blockchain technology is still in its initial phases of validation and there are no large-scale application scenarios available, particularly in the big data sector. Finally, we narrow our study to the Healthcare industry and offer the following research directions for its primary issues.
{"title":"Blockchain Application on Big Data Security","authors":"Esraa Elgamal, Walaa Medhat, M. A. Elfatah, Nashwa Abdelbaki","doi":"10.1109/LT58159.2023.10092368","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092368","url":null,"abstract":"In recent years, advances in technology in several industries have resulted in massive data collections on the web. It raises worries about large data security and protection. The advent of Blockchain technology has caused a revolution in the security field for different applications. The distributed ledger is stored on each Blockchain node, which enhances security and data transparency. On the Blockchain network, illegal users are not authorized to undertake any fault transactions. In this article, we will discuss how Blockchain may be employed to secure the big data. We explain the problems that the Blockchain faced with big data and its solutions. We summarize recent works of Blockchain with big data and the present issues and trends. We demonstrate that Blockchain technology is still in its initial phases of validation and there are no large-scale application scenarios available, particularly in the big data sector. Finally, we narrow our study to the Healthcare industry and offer the following research directions for its primary issues.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128576910","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092310
M. El-Amin, Budoor Alwated
The use of machine learning to forecast how nanoparticles would migrate through porous material is covered in this research. We employed the random forest, decision tree, artificial neural network, and gradient boosting regression machine learning techniques. Since there are not many experimental datasets available, it is easier to create artificial datasets using verified numerical simulators. Additionally, covered in the paper are data preprocessing, correlations, the importance of features, and hyperparameter adjustment. Moreover, different error metrics and R2-correlation are used to gauge how well the predictive models perform. Finally, examples of the findings are presented. The decision tree model is determined to have the highest accuracy, the best performance, and the lowest root mean squared error.
{"title":"Machine Learning Prediction for Nanoparticles Behavior in Hydrocarbon Reservoirs","authors":"M. El-Amin, Budoor Alwated","doi":"10.1109/LT58159.2023.10092310","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092310","url":null,"abstract":"The use of machine learning to forecast how nanoparticles would migrate through porous material is covered in this research. We employed the random forest, decision tree, artificial neural network, and gradient boosting regression machine learning techniques. Since there are not many experimental datasets available, it is easier to create artificial datasets using verified numerical simulators. Additionally, covered in the paper are data preprocessing, correlations, the importance of features, and hyperparameter adjustment. Moreover, different error metrics and R2-correlation are used to gauge how well the predictive models perform. Finally, examples of the findings are presented. The decision tree model is determined to have the highest accuracy, the best performance, and the lowest root mean squared error.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127013885","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 : 2023-01-26DOI: 10.1109/lt58159.2023.10092342
Erika Mazurkiewicz, Sahar Al Seesi, Amal Abdel Raouf
The spread of COVID-19 has thrown the world into a panic. We are constantly learning more about the virus every day, from how it spreads to who is more susceptible to becoming infected by different variants. Those with underlying respiratory conditions and other immunocompromised individuals need to be extra cautious regarding the virus. Many researchers have created COVID-19 trackers to detect the spread of COVID-19 around the world and show hot spots where COVID-19 cases are more prevalent. Previous work lacks the consideration of comorbidity as a factor of death rate. This work aims to create an agent-based model to predict comorbidity death rate caused by a health condition in addition to COVID-19. The model is evaluated using the symmetric mean absolute percentage error metric and proved to be very efficient.
{"title":"Predicting COVID-19 Mortalities for Patients with Special Health Conditions Using an Agent-Based Model","authors":"Erika Mazurkiewicz, Sahar Al Seesi, Amal Abdel Raouf","doi":"10.1109/lt58159.2023.10092342","DOIUrl":"https://doi.org/10.1109/lt58159.2023.10092342","url":null,"abstract":"The spread of COVID-19 has thrown the world into a panic. We are constantly learning more about the virus every day, from how it spreads to who is more susceptible to becoming infected by different variants. Those with underlying respiratory conditions and other immunocompromised individuals need to be extra cautious regarding the virus. Many researchers have created COVID-19 trackers to detect the spread of COVID-19 around the world and show hot spots where COVID-19 cases are more prevalent. Previous work lacks the consideration of comorbidity as a factor of death rate. This work aims to create an agent-based model to predict comorbidity death rate caused by a health condition in addition to COVID-19. The model is evaluated using the symmetric mean absolute percentage error metric and proved to be very efficient.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115496238","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092283
A. Hussein, Ibrahim Salah, K. Rahouma, M. Mourad Mabrook
The rapidly increasing demand for mobile communication over satellite platforms and its applications necessitates a significant effort on the part of researchers to fulfill the prospective requirements of wireless network infrastructure. It is predicted that traffic will increase by multiples of hundreds soon. Therefore, the network's capacity has to multiply with high energy efficiency (EE), which can be achieved using massive multiple-input, multiple-output (M-MIMO). An adaptive scheme that maximizes energy efficiency is proposed in this paper at maximum spectral efficiency. Also, an efficient tradeoff between energy efficiency and throughput is mainly proposed. The analytical and simulation results prove that the proposed multi-cell minimum mean square error (M-MMSE) precoding scheme provides the maximum EE and efficient throughput of next-generation networks and satellite communication utilizing M- MIMO. Hence, it gives the optimum and most efficient tradeoff between EE and the throughput of the M-MIMO system.
{"title":"Efficient Tradeoff between Throughput and Energy Efficiency of Massive-MIMO Technique for Satellite Communication applications","authors":"A. Hussein, Ibrahim Salah, K. Rahouma, M. Mourad Mabrook","doi":"10.1109/LT58159.2023.10092283","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092283","url":null,"abstract":"The rapidly increasing demand for mobile communication over satellite platforms and its applications necessitates a significant effort on the part of researchers to fulfill the prospective requirements of wireless network infrastructure. It is predicted that traffic will increase by multiples of hundreds soon. Therefore, the network's capacity has to multiply with high energy efficiency (EE), which can be achieved using massive multiple-input, multiple-output (M-MIMO). An adaptive scheme that maximizes energy efficiency is proposed in this paper at maximum spectral efficiency. Also, an efficient tradeoff between energy efficiency and throughput is mainly proposed. The analytical and simulation results prove that the proposed multi-cell minimum mean square error (M-MMSE) precoding scheme provides the maximum EE and efficient throughput of next-generation networks and satellite communication utilizing M- MIMO. Hence, it gives the optimum and most efficient tradeoff between EE and the throughput of the M-MIMO system.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125922466","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 : 2023-01-26DOI: 10.1109/LT58159.2023.10092319
Dev Mashru, Ganesha Maruthi Mangipudi, H. Swamy, Shivakumar Halangali, Sushma E
Instant messaging applications enable users to communicate with each other in a simple and efficient manner. However, big corporations dominate and control the market today. This gives these corporations authority over their users and their data. Moreover, all popular instant messaging applications today rely on a set of centralised servers, introducing a single point of failure. The authors of this paper propose an instant messaging application that relies on a decentralised architecture, a first of its kind, hosted on the cloud, making the service fault-tolerant. Additionally, all messages being exchanged between users are End-to-End Encrypted, providing the users with privacy. The authors of this paper were able to demonstrate the proposed system working as envisioned.
{"title":"A Decentralised Instant Messaging Application with End-to-End Encryption","authors":"Dev Mashru, Ganesha Maruthi Mangipudi, H. Swamy, Shivakumar Halangali, Sushma E","doi":"10.1109/LT58159.2023.10092319","DOIUrl":"https://doi.org/10.1109/LT58159.2023.10092319","url":null,"abstract":"Instant messaging applications enable users to communicate with each other in a simple and efficient manner. However, big corporations dominate and control the market today. This gives these corporations authority over their users and their data. Moreover, all popular instant messaging applications today rely on a set of centralised servers, introducing a single point of failure. The authors of this paper propose an instant messaging application that relies on a decentralised architecture, a first of its kind, hosted on the cloud, making the service fault-tolerant. Additionally, all messages being exchanged between users are End-to-End Encrypted, providing the users with privacy. The authors of this paper were able to demonstrate the proposed system working as envisioned.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":"35 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126021483","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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