Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623114
Zuhair Alqarni
Because of its numerous advantages, photovoltaic (PV) electricity is one of the most important renewable energy sources, and obtaining more power from these systems in varying conditions is much needed. Theoretically, simulated, and practically confirmed design of a Maximum Power Point Tracking (MPPT) controller using the Synchronous Reference Frame (SRF) theory is presented in this study. The indirect current control mechanism is used by the system. A solar PV system, a dc-dc boost converter, an MPPT controller, a Voltage Source Converter (VSC), a ripple filter, and a grid make up the whole system. For the simulation of the proposed control scheme, MATLAB / Simulink is used. The simulation results show that the suggested system maintains a high grid power factor under changing load situations, accomplishes voltage management by stabilising it at the Point of Common Coupling (PCC), and offers high grid power under changing load conditions. The suggested technique was also put to the test through an experimental implementation. The findings show that the system is extremely stable, with overall harmonic distortion of only 2.34 percent. In comparison to current techniques in the literature, the suggested approach is less complex and has a low computing cost. The suggested design for a new grid-connected solar panel system with improved power quality is thorough and comprehensive.
{"title":"Maximum Power Point Tracking for Solar Photovoltaic System using Synchronous Reference Frame Theory","authors":"Zuhair Alqarni","doi":"10.1109/iemcon53756.2021.9623114","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623114","url":null,"abstract":"Because of its numerous advantages, photovoltaic (PV) electricity is one of the most important renewable energy sources, and obtaining more power from these systems in varying conditions is much needed. Theoretically, simulated, and practically confirmed design of a Maximum Power Point Tracking (MPPT) controller using the Synchronous Reference Frame (SRF) theory is presented in this study. The indirect current control mechanism is used by the system. A solar PV system, a dc-dc boost converter, an MPPT controller, a Voltage Source Converter (VSC), a ripple filter, and a grid make up the whole system. For the simulation of the proposed control scheme, MATLAB / Simulink is used. The simulation results show that the suggested system maintains a high grid power factor under changing load situations, accomplishes voltage management by stabilising it at the Point of Common Coupling (PCC), and offers high grid power under changing load conditions. The suggested technique was also put to the test through an experimental implementation. The findings show that the system is extremely stable, with overall harmonic distortion of only 2.34 percent. In comparison to current techniques in the literature, the suggested approach is less complex and has a low computing cost. The suggested design for a new grid-connected solar panel system with improved power quality is thorough and comprehensive.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129070828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623165
Pinasthika Aulia Fadhila, M. I. Nashiruddin, M. Nugraha
4G LTE-Advanced is the current most advanced technology available, enabling speedier connectivity. Many individuals in Indonesia anticipate that this cutting-edge technology will facilitate internet-related activities. As a result, the number of users of this technology is growing, resulting in network congestion in a dense urban area in Indonesia. The answer to this issue is to raise the network's 4G LTE-Advanced frequency. The purpose of this study is to plan a 4G LTE-Advanced network in Central Jakarta utilizing quantitative techniques and two approaches, namely capacity planning, and coverage planning, and then simulate the results by using a network software simulator called Forsk Atoll. The performance study used four parameters: Reference Signal Received Power (RSRP), Signal to Interference Noise Ratio (SINR), radio bearer, and throughput. According to the findings of this study, adding a 700 MHz frequency to the 4G LTE-Advanced network in Central Jakarta will need at least 131 sites to provide adequate network coverage for all customers. The network performance in the Central Jakarta region is rather pretty good, with an RSRP of −38.88 dBm, a mean SINR value of 0.66 dB, 16QAM modulation with an efficiency of 1.4766, and an average throughput of 9.54 Mbps.
{"title":"Addressing Spectrum Scarcity in Indonesia Dense Urban Market by Using 700 MHz for 4G LTE-Advanced Network Deployment","authors":"Pinasthika Aulia Fadhila, M. I. Nashiruddin, M. Nugraha","doi":"10.1109/iemcon53756.2021.9623165","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623165","url":null,"abstract":"4G LTE-Advanced is the current most advanced technology available, enabling speedier connectivity. Many individuals in Indonesia anticipate that this cutting-edge technology will facilitate internet-related activities. As a result, the number of users of this technology is growing, resulting in network congestion in a dense urban area in Indonesia. The answer to this issue is to raise the network's 4G LTE-Advanced frequency. The purpose of this study is to plan a 4G LTE-Advanced network in Central Jakarta utilizing quantitative techniques and two approaches, namely capacity planning, and coverage planning, and then simulate the results by using a network software simulator called Forsk Atoll. The performance study used four parameters: Reference Signal Received Power (RSRP), Signal to Interference Noise Ratio (SINR), radio bearer, and throughput. According to the findings of this study, adding a 700 MHz frequency to the 4G LTE-Advanced network in Central Jakarta will need at least 131 sites to provide adequate network coverage for all customers. The network performance in the Central Jakarta region is rather pretty good, with an RSRP of −38.88 dBm, a mean SINR value of 0.66 dB, 16QAM modulation with an efficiency of 1.4766, and an average throughput of 9.54 Mbps.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125426679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623183
Zubaidah Al-Mashhadani, B. Chandrasekaran
Robotic systems can play a crucial role in the agricultural field as the increasing demands for crops lead to continuous pressure for more crop quality and quantity. Agricultural work is very tedious under poor weather circumstances. The agricultural robots represent a replacement for labor in carrying out the tiresome tasks and efficiently avoiding exposing humans to health risks. The proposed work implements a ground robot to navigate the farm and monitor the plants using the Robot Operating System. The monitoring includes the classification of nine types of tomato leaf diseases and three tomato ripeness levels using Convolutional Neural Networks and computer vision using a raspberry pi camera. The model is trained on Colab, and raspberry pi3 is used to run Keras pre-trained model on TurtleBot3. Three CNN architectures are used and compared for the disease and ripeness classification of tomatoes.
{"title":"ROS-based Robotic System for Tomato Disease and Ripeness Classification using Convolutional Neural Networks","authors":"Zubaidah Al-Mashhadani, B. Chandrasekaran","doi":"10.1109/iemcon53756.2021.9623183","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623183","url":null,"abstract":"Robotic systems can play a crucial role in the agricultural field as the increasing demands for crops lead to continuous pressure for more crop quality and quantity. Agricultural work is very tedious under poor weather circumstances. The agricultural robots represent a replacement for labor in carrying out the tiresome tasks and efficiently avoiding exposing humans to health risks. The proposed work implements a ground robot to navigate the farm and monitor the plants using the Robot Operating System. The monitoring includes the classification of nine types of tomato leaf diseases and three tomato ripeness levels using Convolutional Neural Networks and computer vision using a raspberry pi camera. The model is trained on Colab, and raspberry pi3 is used to run Keras pre-trained model on TurtleBot3. Three CNN architectures are used and compared for the disease and ripeness classification of tomatoes.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125447374","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}
With the technological advancements, every application from our day to day life is becoming Internet-oriented, leading to the concept of Internet of Things (IoT). Various IoT devices and applications can be combined together for making a Smart City where smart drainage system is essential. However, solid wastes from groundwater flowing through the drainage system can create significant obstruction to its unrestricted flow, thereby causing overflows and profound environmental pollution. Thus, it is essential to manage these solid wastes effectively so that they do not obstruct the way of the drainage system. There have been few isolated works focusing on underground drainage monitoring or drainage system management only. However, there has not been any work that focused on both the underground drainage mechanism and the ground surface waste management system. In this paper, we have aimed at solving the particular reason that causes overflow and to manage that cause efficiently. We have proposed a detailed IoT based drainage management system that also incorporates drainage waste management to make the system more effective. We have clearly specified the methods for preventing and managing the solid wastes that are responsible for creating blockage inside drainage pipelines and drain covers.
{"title":"An IoT-Based Complete Smart Drainage System for a Smart City","authors":"Tarannum Zaki, Ismat Tarik Jahan, Md. Shohrab Hossain, Husnu S. Narman","doi":"10.1109/iemcon53756.2021.9623149","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623149","url":null,"abstract":"With the technological advancements, every application from our day to day life is becoming Internet-oriented, leading to the concept of Internet of Things (IoT). Various IoT devices and applications can be combined together for making a Smart City where smart drainage system is essential. However, solid wastes from groundwater flowing through the drainage system can create significant obstruction to its unrestricted flow, thereby causing overflows and profound environmental pollution. Thus, it is essential to manage these solid wastes effectively so that they do not obstruct the way of the drainage system. There have been few isolated works focusing on underground drainage monitoring or drainage system management only. However, there has not been any work that focused on both the underground drainage mechanism and the ground surface waste management system. In this paper, we have aimed at solving the particular reason that causes overflow and to manage that cause efficiently. We have proposed a detailed IoT based drainage management system that also incorporates drainage waste management to make the system more effective. We have clearly specified the methods for preventing and managing the solid wastes that are responsible for creating blockage inside drainage pipelines and drain covers.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126670627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623167
Loubna Chaibi, Marouane Sebgui, Slimane Bah
This paper presents the role and limitations of Unmanned Aerial Vehicles in emergency situations especially during the Covid-19 outbreak. The world had faced lot of disasters through the years leading to a flurry of innovation. New business opportunities have merged especially in the automation revolution. UAVs are small aircraft, mainly known as drones, that are used as technology for public safety companies. A Flying Ad Hoc Network is a network composed by UAVs. They are used in different military and civilian applications especially in areas where there is no infrastructure or where it is difficult to access. In emergency situations, like Covid-19 pandemic that many countries fight nowadays, these technologies help the authorities to control and limit the propagation of the virus. Spraying of disinfectants, temperature scanning, broadcasting of warning messages or detection of suspicious movements, many situations where UAVs can be used. In some countries, UAVs are also used to transport medical supplies including vaccines or deliver food supplies to customers. Because Covid-19 is still so contagious, it is safer to minimize human-to-human contact and use more technologies. However, due to their specific nature, UAVs present some limitations. Solutions to address these limitations are also discussed in this article.
{"title":"Unmanned Aerial Vehicles Against Covid-19 Pandemic: Main Applications and Limitations","authors":"Loubna Chaibi, Marouane Sebgui, Slimane Bah","doi":"10.1109/iemcon53756.2021.9623167","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623167","url":null,"abstract":"This paper presents the role and limitations of Unmanned Aerial Vehicles in emergency situations especially during the Covid-19 outbreak. The world had faced lot of disasters through the years leading to a flurry of innovation. New business opportunities have merged especially in the automation revolution. UAVs are small aircraft, mainly known as drones, that are used as technology for public safety companies. A Flying Ad Hoc Network is a network composed by UAVs. They are used in different military and civilian applications especially in areas where there is no infrastructure or where it is difficult to access. In emergency situations, like Covid-19 pandemic that many countries fight nowadays, these technologies help the authorities to control and limit the propagation of the virus. Spraying of disinfectants, temperature scanning, broadcasting of warning messages or detection of suspicious movements, many situations where UAVs can be used. In some countries, UAVs are also used to transport medical supplies including vaccines or deliver food supplies to customers. Because Covid-19 is still so contagious, it is safer to minimize human-to-human contact and use more technologies. However, due to their specific nature, UAVs present some limitations. Solutions to address these limitations are also discussed in this article.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126483811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623199
Blake D. Bryant, Muhammad R. Abid
COVID-19 has claimed millions of lives and devastated economies worldwide. In efforts to control and limit the spread of COVID-19 many early detection methods are reviewed in this survey. Pneumonia has proven to be closely related to COVID-19 in how it appears on X-rays. This can affect the accuracy of diagnosis for both Pneumonia and COVID-19 when using X-ray imaging. Therefore, this survey will analyze current leading, highly accurate models for COVID-19 detection and its comparison to Pneumonia. These models adopted a variety of different approaches and performance metrics that this survey reviews. The current leading models at detecting COVID-19 are VGG-19, ResNet-50, and Histogram of Oriented Gradients in conjunction with the Support Vector Machines approach.
{"title":"A Medical Imaging Review for COVID-19 Detection and its Comparison to Pneumonia","authors":"Blake D. Bryant, Muhammad R. Abid","doi":"10.1109/iemcon53756.2021.9623199","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623199","url":null,"abstract":"COVID-19 has claimed millions of lives and devastated economies worldwide. In efforts to control and limit the spread of COVID-19 many early detection methods are reviewed in this survey. Pneumonia has proven to be closely related to COVID-19 in how it appears on X-rays. This can affect the accuracy of diagnosis for both Pneumonia and COVID-19 when using X-ray imaging. Therefore, this survey will analyze current leading, highly accurate models for COVID-19 detection and its comparison to Pneumonia. These models adopted a variety of different approaches and performance metrics that this survey reviews. The current leading models at detecting COVID-19 are VGG-19, ResNet-50, and Histogram of Oriented Gradients in conjunction with the Support Vector Machines approach.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125718599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623196
Tasnia Tabassum, Faria Soroni, Elias Ahammad Sojib, Md. Mahmudul Hasan Shihab, Mohammad Monirujjaman Khan
This article presents the notion of a project which was planned and carried out to identify toxic food components. This gadget detects not only the proportion of hazardous chemicals in foods, but also shows whether or not the item is safe to eat. The hazardous component in this research was formalin. Formaldehyde is a major concern in Bangladesh in terms of food preservation. Formalin consumption is a major risk to health. The Arduino module is utilized for this project as the system's main powerhouse. To detect formaldehyde gas, the HCHO grove module is utilized. Alongside the hardware, an Android app was developed. This appliance has been created for all Bangladeshi business people. This gadget is also used by people who can't afford a smart phone. This gadget may therefore be used with or without the application. For further information, the app has been developed.
{"title":"Development of a Toxic Food Ingredients Detector","authors":"Tasnia Tabassum, Faria Soroni, Elias Ahammad Sojib, Md. Mahmudul Hasan Shihab, Mohammad Monirujjaman Khan","doi":"10.1109/iemcon53756.2021.9623196","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623196","url":null,"abstract":"This article presents the notion of a project which was planned and carried out to identify toxic food components. This gadget detects not only the proportion of hazardous chemicals in foods, but also shows whether or not the item is safe to eat. The hazardous component in this research was formalin. Formaldehyde is a major concern in Bangladesh in terms of food preservation. Formalin consumption is a major risk to health. The Arduino module is utilized for this project as the system's main powerhouse. To detect formaldehyde gas, the HCHO grove module is utilized. Alongside the hardware, an Android app was developed. This appliance has been created for all Bangladeshi business people. This gadget is also used by people who can't afford a smart phone. This gadget may therefore be used with or without the application. For further information, the app has been developed.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"16 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133853720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623175
G.L.V. Mihiranga, W. Weerasooriya, T.L.P. Palliyaguruge, P. Gunasekera, M. Gamage, Shantha Selva Kumari
The railway service is a convenient and low-cost transport method in Sri Lanka, widely employed by both local and foreign passengers. Major railway lines in Sri Lanka cover unique and very different areas in the country. For example, the Northern province's weather and geography conditions significantly differ from Southern or Central provinces. Majority of the tourists lack understanding in identifying appropriate or attractive places that best suits them, close by to the Railway Stations. Therefore, a passenger needs to spend more time identifying their railway tour destinations. When passengers are booking tickets, even though they are able to reserve seats beforehand, they are unable to reserve a specific seat. Also, there is no process to identify the most suitable seat for them amidst many other travelers, especially if they are travelling alone. Considering the aforementioned, authors propose a more innovative and user-friendly system for the Railway Department of Sri Lanka. Depending on various passenger attributes the system is capable of suggesting a travel plan with railway lines which cover most suitable destination suggestions; identifying the best seats with a relaxing atmosphere; providing an interactive chatbot to satisfy user queries on specific location information; and facility for 24×7 user interaction. A travel plan can save passengers time and allows them to identify the desired railway line and relevant attractions without much hassle. And they are saved of an unpleasant experience through the suggestion of the best seating location. Machine Learning and Deep Learning technologies are used in developing the proposed system.
{"title":"User-friendly Enhanced Machine Learning-based Railway Management System for Sri Lanka","authors":"G.L.V. Mihiranga, W. Weerasooriya, T.L.P. Palliyaguruge, P. Gunasekera, M. Gamage, Shantha Selva Kumari","doi":"10.1109/iemcon53756.2021.9623175","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623175","url":null,"abstract":"The railway service is a convenient and low-cost transport method in Sri Lanka, widely employed by both local and foreign passengers. Major railway lines in Sri Lanka cover unique and very different areas in the country. For example, the Northern province's weather and geography conditions significantly differ from Southern or Central provinces. Majority of the tourists lack understanding in identifying appropriate or attractive places that best suits them, close by to the Railway Stations. Therefore, a passenger needs to spend more time identifying their railway tour destinations. When passengers are booking tickets, even though they are able to reserve seats beforehand, they are unable to reserve a specific seat. Also, there is no process to identify the most suitable seat for them amidst many other travelers, especially if they are travelling alone. Considering the aforementioned, authors propose a more innovative and user-friendly system for the Railway Department of Sri Lanka. Depending on various passenger attributes the system is capable of suggesting a travel plan with railway lines which cover most suitable destination suggestions; identifying the best seats with a relaxing atmosphere; providing an interactive chatbot to satisfy user queries on specific location information; and facility for 24×7 user interaction. A travel plan can save passengers time and allows them to identify the desired railway line and relevant attractions without much hassle. And they are saved of an unpleasant experience through the suggestion of the best seating location. Machine Learning and Deep Learning technologies are used in developing the proposed system.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133868871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623068
Ismail Hakki Yemenoglu, A. Shah, H. Ilhan
Deaf individuals rely heavily on sign languages. They make use of them to communicate with others. Although deaf individuals are familiar with sign language, but it is not widely understood by the general public. In this article, sign language recognition through convolutional neural network (CNN) system is developed for those who aren't familiar with sign language. American sign language letters are utilized in this work. We tried to create a translator for these letters for people who do not know sign language, and we used GoogleNet, a CNN, using the transfer learning method. Our dataset was used to train the network. The network model and network weights are recorded for the test data set once network training is finished. The accuracy of this sign language recognition system is 91.02%.
{"title":"Deep Convolutional Neural Networks-Based Sign Language Recognition System","authors":"Ismail Hakki Yemenoglu, A. Shah, H. Ilhan","doi":"10.1109/iemcon53756.2021.9623068","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623068","url":null,"abstract":"Deaf individuals rely heavily on sign languages. They make use of them to communicate with others. Although deaf individuals are familiar with sign language, but it is not widely understood by the general public. In this article, sign language recognition through convolutional neural network (CNN) system is developed for those who aren't familiar with sign language. American sign language letters are utilized in this work. We tried to create a translator for these letters for people who do not know sign language, and we used GoogleNet, a CNN, using the transfer learning method. Our dataset was used to train the network. The network model and network weights are recorded for the test data set once network training is finished. The accuracy of this sign language recognition system is 91.02%.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134107875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-27DOI: 10.1109/iemcon53756.2021.9623124
Samaneh Madanian, David Airehrour, Nabilah Ahmad Samsuri, M. Cherrington
We have yet to realise the full capability of social media as an innovative information platform during emergencies and crisis response and management. Sentiment analysis can systematically identify, extract, and scrutinise emotional states and subjective information in social media data. Exploring reactions and perceptions to response messaging is invaluable and proved especially useful for a pandemic response as it can demonstrate general population reaction to the pandemic and governments response actions. This can be further analysed to identify the gap between government response actions and communications and citizens' perceptions. In this paper, an analysis of Twitter data explores population reaction towards COVID-19 health messaging. A Natural Language Processing Python tool is known as TextBlob was used to discover general data sentiment. Data were divided into three sentiments and text extraction of health messages was conducted to explore subsequent tweets in predefined categories. Our findings show the outcome of Tweets analysis could help us to identify the general population concerns and their reactions to COVID-19 to give a better understanding of the situation to governments and support them in implementing appropriate policies.
{"title":"Twitter Sentiment Analysis in Covid-19 Pandemic","authors":"Samaneh Madanian, David Airehrour, Nabilah Ahmad Samsuri, M. Cherrington","doi":"10.1109/iemcon53756.2021.9623124","DOIUrl":"https://doi.org/10.1109/iemcon53756.2021.9623124","url":null,"abstract":"We have yet to realise the full capability of social media as an innovative information platform during emergencies and crisis response and management. Sentiment analysis can systematically identify, extract, and scrutinise emotional states and subjective information in social media data. Exploring reactions and perceptions to response messaging is invaluable and proved especially useful for a pandemic response as it can demonstrate general population reaction to the pandemic and governments response actions. This can be further analysed to identify the gap between government response actions and communications and citizens' perceptions. In this paper, an analysis of Twitter data explores population reaction towards COVID-19 health messaging. A Natural Language Processing Python tool is known as TextBlob was used to discover general data sentiment. Data were divided into three sentiments and text extraction of health messages was conducted to explore subsequent tweets in predefined categories. Our findings show the outcome of Tweets analysis could help us to identify the general population concerns and their reactions to COVID-19 to give a better understanding of the situation to governments and support them in implementing appropriate policies.","PeriodicalId":272590,"journal":{"name":"2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131643593","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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