Pub Date : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075598
O. M. Hussein, N. Yasin
The best P and PI controller parameters of the cascade control of the BLDC system are determined using a new artificial intelligence-based optimization method called the slap swarm algorithm (SSA) in this paper. The algorithm's simplicity allows for precise tuning of optimal P and PI controller values. The integral time absolute error (ITAE) was chosen as the fitness function to optimize the controller parameters. Compared with the classical control technique (PID), the SSA approach was found to have good tuning and obtained less rise time, also less (Approximately zero) overshoot, and is more efficient in increasing the step response of the BLDC system, according to the transient response study.
{"title":"Salp Swarm Algorithm-based Position Control of a BLDC Motor","authors":"O. M. Hussein, N. Yasin","doi":"10.1109/ICOASE56293.2022.10075598","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075598","url":null,"abstract":"The best P and PI controller parameters of the cascade control of the BLDC system are determined using a new artificial intelligence-based optimization method called the slap swarm algorithm (SSA) in this paper. The algorithm's simplicity allows for precise tuning of optimal P and PI controller values. The integral time absolute error (ITAE) was chosen as the fitness function to optimize the controller parameters. Compared with the classical control technique (PID), the SSA approach was found to have good tuning and obtained less rise time, also less (Approximately zero) overshoot, and is more efficient in increasing the step response of the BLDC system, according to the transient response study.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130347794","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075578
M. A. Omer, Shimal Sh. Taher, S. Ameen
Telemedicine and telehealth care system show the revolutionary and modern way to deal with the coronavirus 2019 pandemic. However, such systems are facing increased security risks. As a result, healthcare providers and academic institutions must be well-informed, safe, and prepared to respond to any cyber-attack. The aim of this paper is to conduct a review of healthcare information systems together with how security can be provided for such systems. The paper main focus is on the adoption of blockchain technology to support the security of the healthcare system. This adoption has been investigated and assessed to show its benefits compared with other conventional technologies. Finally, a recommendation was pointed out for the security of healthcare with the usage of blockchain technology.
{"title":"Investigation of Healthcare Security Using Blockchain Technology: A review","authors":"M. A. Omer, Shimal Sh. Taher, S. Ameen","doi":"10.1109/ICOASE56293.2022.10075578","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075578","url":null,"abstract":"Telemedicine and telehealth care system show the revolutionary and modern way to deal with the coronavirus 2019 pandemic. However, such systems are facing increased security risks. As a result, healthcare providers and academic institutions must be well-informed, safe, and prepared to respond to any cyber-attack. The aim of this paper is to conduct a review of healthcare information systems together with how security can be provided for such systems. The paper main focus is on the adoption of blockchain technology to support the security of the healthcare system. This adoption has been investigated and assessed to show its benefits compared with other conventional technologies. Finally, a recommendation was pointed out for the security of healthcare with the usage of blockchain technology.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134206270","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075581
Shakir M. Abas, Omer Mohammed Salih Hassan, Imad Manaf Ali, Safin Saber Nori, Hamza Sardar Hassan
Recently, the various diseases are infecting the humans due to their living environmental and the changes of the environmental. It is much important to identification and prediction of such diseases at earlier stages to prevent the outbreak these diseases. The identification of these diseases manually by the doctors is difficult. There are many of the chronic diseases that affect human. One of these diseases is the brain tumors that arise by the abnormal growth and division of brain cells which leads to brain cancer. The computer vision plays important role in human health field which gives accurate results that helps the human to tack the true decision. In addition, traditional technics are time consuming, expensive and addressed problem requires expert knowledge. This research aims to focus on the using simple deep learning architecture with accurate results. Moreover, the Convolution Neural Network (CNN) algorithm is used for reliable Classification of the brain tumor Image. The proposed models are showed very good results and reached almost 96.4% accuracy on Brain MRI Images for Brain Tumor Detection1 dataset.
{"title":"Diseases Diagnosis Using Machine Learning of Medical Images","authors":"Shakir M. Abas, Omer Mohammed Salih Hassan, Imad Manaf Ali, Safin Saber Nori, Hamza Sardar Hassan","doi":"10.1109/ICOASE56293.2022.10075581","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075581","url":null,"abstract":"Recently, the various diseases are infecting the humans due to their living environmental and the changes of the environmental. It is much important to identification and prediction of such diseases at earlier stages to prevent the outbreak these diseases. The identification of these diseases manually by the doctors is difficult. There are many of the chronic diseases that affect human. One of these diseases is the brain tumors that arise by the abnormal growth and division of brain cells which leads to brain cancer. The computer vision plays important role in human health field which gives accurate results that helps the human to tack the true decision. In addition, traditional technics are time consuming, expensive and addressed problem requires expert knowledge. This research aims to focus on the using simple deep learning architecture with accurate results. Moreover, the Convolution Neural Network (CNN) algorithm is used for reliable Classification of the brain tumor Image. The proposed models are showed very good results and reached almost 96.4% accuracy on Brain MRI Images for Brain Tumor Detection1 dataset.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133925234","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075586
D. A. Zebari, Dawlat Mustafa Sulaiman, Shereen S. Sadiq, Nechirvan Asaad Zebari, Merdin Shamal Salih
Earlier discovery of COVID-19 through precise diagnosis, particularly in instances with no evident symptoms, may reduce the mortality rate of patients. Chest X-ray images are the primary diagnostic tool for this condition. Patients exhibiting COVID-19 symptoms are causing hospitals to become overcrowded, which is becoming a big concern. The contribution that machine learning has made to big data medical research has been very helpful, opening up new ways to diagnose diseases. This study has developed a machine vision method to identify COVID-19 using X-ray images. The preprocessing stage has been applied to resize images and enhance the quality of X-ray images. The Gray-level co-occurrence matrix (GLCM) and Gray-Level Run Length Matrix (GLRLM) are then used to extract features from the X-ray images, and these features are combined to develop the performance classification via training by Support Vector Machine (SVM). The testing phase evaluated the model's performance using generalized data. This developed feature combination utilizing the GLCM and GLRLM algorithms assured a satisfactory evaluation performance based on COVID-19 detection compared to the immediate, single feature with a testing accuracy of 96.65%, a specificity of 99.54%, and a sensitivity of 97.98%.
{"title":"Automated Detection of Covid-19 from X-ray Using SVM","authors":"D. A. Zebari, Dawlat Mustafa Sulaiman, Shereen S. Sadiq, Nechirvan Asaad Zebari, Merdin Shamal Salih","doi":"10.1109/ICOASE56293.2022.10075586","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075586","url":null,"abstract":"Earlier discovery of COVID-19 through precise diagnosis, particularly in instances with no evident symptoms, may reduce the mortality rate of patients. Chest X-ray images are the primary diagnostic tool for this condition. Patients exhibiting COVID-19 symptoms are causing hospitals to become overcrowded, which is becoming a big concern. The contribution that machine learning has made to big data medical research has been very helpful, opening up new ways to diagnose diseases. This study has developed a machine vision method to identify COVID-19 using X-ray images. The preprocessing stage has been applied to resize images and enhance the quality of X-ray images. The Gray-level co-occurrence matrix (GLCM) and Gray-Level Run Length Matrix (GLRLM) are then used to extract features from the X-ray images, and these features are combined to develop the performance classification via training by Support Vector Machine (SVM). The testing phase evaluated the model's performance using generalized data. This developed feature combination utilizing the GLCM and GLRLM algorithms assured a satisfactory evaluation performance based on COVID-19 detection compared to the immediate, single feature with a testing accuracy of 96.65%, a specificity of 99.54%, and a sensitivity of 97.98%.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124539684","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075570
Shimal Sh. Taher, S. Ameen, J. A. Ahmed
Over the last decade, worldwide data traffic has risen at an unprecedented rate, prompting a surge in interest in big data. manufacturing, entertainment, and media. With this interest, Blockchain Technology, appeared as a promising technology that enables the transaction record to be continuously stored, protected with the digital signature, and validated by consensus. It operates under the concept of a digital ledger that is distributed. In this article, recent growth in blockchain interest as an alternative to traditional centralized systems has been presented and considered the emerging implementations thereof. In particular, the key approaches needed for the introduction of the blockchain and security issues. This includes the general issue behind the blockchain, description of the component, and the blockchain importance and connection with the big data. Thus, the paper focuses on reviewing the research in blockchain applications in securing big data. The paper compares big data security techniques and mechanisms provided by the blockchain approach considering security attacks that might shed light on Blockchain enthusiasts and researchers. Finally, the paper evaluates the various challenges of blockchain and put some recommendations for future research.
{"title":"Blockchain for Big Data Security, Issues, Challenges and Future Directions","authors":"Shimal Sh. Taher, S. Ameen, J. A. Ahmed","doi":"10.1109/ICOASE56293.2022.10075570","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075570","url":null,"abstract":"Over the last decade, worldwide data traffic has risen at an unprecedented rate, prompting a surge in interest in big data. manufacturing, entertainment, and media. With this interest, Blockchain Technology, appeared as a promising technology that enables the transaction record to be continuously stored, protected with the digital signature, and validated by consensus. It operates under the concept of a digital ledger that is distributed. In this article, recent growth in blockchain interest as an alternative to traditional centralized systems has been presented and considered the emerging implementations thereof. In particular, the key approaches needed for the introduction of the blockchain and security issues. This includes the general issue behind the blockchain, description of the component, and the blockchain importance and connection with the big data. Thus, the paper focuses on reviewing the research in blockchain applications in securing big data. The paper compares big data security techniques and mechanisms provided by the blockchain approach considering security attacks that might shed light on Blockchain enthusiasts and researchers. Finally, the paper evaluates the various challenges of blockchain and put some recommendations for future research.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127469751","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075587
Nagham Saeed, H. M. Ahmed
The spread of the Corona Virus pandemic on a global scale had a great impact on the trend towards e-learning. In the virtual exams the student can take his exams online without any papers, in addition to the correction and electronic monitoring of the exams. Tests are supervised and controlled by a camera and proven cheat-checking tools. This technology has opened the doors of academic institutions for distance learning to be wide spread without any problems at all. In this paper, a proposed model was built by linking a computer network using a server/client model because it is a system that distributes tasks between the two. The main computer that acts as a server (exam observer) is connected to a group of sub-computers (students) who are being tested and these devices are considered the set of clients. The proposed student face recognition system is run on each computer (client) in order to identify and verify the identity of the student. When another face is detected, the program sends a warning signal to the server. Thus, the concerned student is alerted. This mechanism helps examinees reduce cheating cases in early time. The results obtained from the face recognition showed high accuracy despite the large number of students' faces. The performance speed was in line with the test performance requirements, handling 1,081 real photos and adding 960 photos.
{"title":"Building a Real-Time System to Monitor Students Electronically Based on Digital Images of Face Movement","authors":"Nagham Saeed, H. M. Ahmed","doi":"10.1109/ICOASE56293.2022.10075587","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075587","url":null,"abstract":"The spread of the Corona Virus pandemic on a global scale had a great impact on the trend towards e-learning. In the virtual exams the student can take his exams online without any papers, in addition to the correction and electronic monitoring of the exams. Tests are supervised and controlled by a camera and proven cheat-checking tools. This technology has opened the doors of academic institutions for distance learning to be wide spread without any problems at all. In this paper, a proposed model was built by linking a computer network using a server/client model because it is a system that distributes tasks between the two. The main computer that acts as a server (exam observer) is connected to a group of sub-computers (students) who are being tested and these devices are considered the set of clients. The proposed student face recognition system is run on each computer (client) in order to identify and verify the identity of the student. When another face is detected, the program sends a warning signal to the server. Thus, the concerned student is alerted. This mechanism helps examinees reduce cheating cases in early time. The results obtained from the face recognition showed high accuracy despite the large number of students' faces. The performance speed was in line with the test performance requirements, handling 1,081 real photos and adding 960 photos.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128232223","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075595
Bana Shekh Faraj, A. Siddiq
This paper is interested in studying the Peak to Average Power Ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) system transmitter. PAPR is a common issue in multicarrier transmission techniques which is the result of adding independent multicarrier signals of different peak values on the same phases. The reduction schemes have been diversly examined for classical OFDM and the majority of them can be directly extended to OFDM-IM while some require slight changes to suit the OFDM-IM characteristics. Selective Mapping (SLM), Partial Transmit Sequence (PTS), Tone Reservation (TR), and Peak Insertion (PI) are some examples on the reduction schemes that will be investigated throughout this paper. As for PI, to the best knowledge of the authors is for the first time implemented in OFDM-IM. The system parameters effects, number of total subcarriers(N), number of subblocks (n), the active subcarriers (k), and the activation ratio (r) are studied to gain the lowest PAPR amount possible that reached (1.2 dB) at specified system parameters.
{"title":"Peak to Average Power Ratio Reduction for OFDM with IM System","authors":"Bana Shekh Faraj, A. Siddiq","doi":"10.1109/ICOASE56293.2022.10075595","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075595","url":null,"abstract":"This paper is interested in studying the Peak to Average Power Ratio (PAPR) reduction in Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) system transmitter. PAPR is a common issue in multicarrier transmission techniques which is the result of adding independent multicarrier signals of different peak values on the same phases. The reduction schemes have been diversly examined for classical OFDM and the majority of them can be directly extended to OFDM-IM while some require slight changes to suit the OFDM-IM characteristics. Selective Mapping (SLM), Partial Transmit Sequence (PTS), Tone Reservation (TR), and Peak Insertion (PI) are some examples on the reduction schemes that will be investigated throughout this paper. As for PI, to the best knowledge of the authors is for the first time implemented in OFDM-IM. The system parameters effects, number of total subcarriers(N), number of subblocks (n), the active subcarriers (k), and the activation ratio (r) are studied to gain the lowest PAPR amount possible that reached (1.2 dB) at specified system parameters.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116754366","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075573
Roua Muwafaq Younus, Mahmod Ahmed Al Zubaidy, Safwan Hafeedh Younus
Many factors, such as direct spotlights and multipath propagation, contribute to the deterioration of the optical wireless communication (OWC) system's performance in the interior environment. In this study, we look at angle diversity receiver (ADR) that can assist to mitigate these issues by rejecting direct pathways from the spotlights and allowing only reflected rays to reach the receiver. ADR also shortens the distance between the sender and the recipient, resulting in less path loss and delay spread. ADR consists of five photodetectors and each photodetector is directed in a precise direction to improve the system's performance by providing a specified field of view (FOV). Elevation angles are optimized to enhance the signal-to-noise ratio (SNR) by changing the angle in steps. Select the Best (SB) scheme is used to choose the detector with the greatest SNR. The computations are done with the help of the MATLAB program. The ADR's results are compared to the conventional diffuse system's (CDS) results, where the bit error rate (BER), and the delay spread are lowered greatly, and the 3-dB bandwidth of the channel is extended, according to the findings.
{"title":"Angle Diversity Receiver for Indoor Optical Wireless Communication Systems","authors":"Roua Muwafaq Younus, Mahmod Ahmed Al Zubaidy, Safwan Hafeedh Younus","doi":"10.1109/ICOASE56293.2022.10075573","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075573","url":null,"abstract":"Many factors, such as direct spotlights and multipath propagation, contribute to the deterioration of the optical wireless communication (OWC) system's performance in the interior environment. In this study, we look at angle diversity receiver (ADR) that can assist to mitigate these issues by rejecting direct pathways from the spotlights and allowing only reflected rays to reach the receiver. ADR also shortens the distance between the sender and the recipient, resulting in less path loss and delay spread. ADR consists of five photodetectors and each photodetector is directed in a precise direction to improve the system's performance by providing a specified field of view (FOV). Elevation angles are optimized to enhance the signal-to-noise ratio (SNR) by changing the angle in steps. Select the Best (SB) scheme is used to choose the detector with the greatest SNR. The computations are done with the help of the MATLAB program. The ADR's results are compared to the conventional diffuse system's (CDS) results, where the bit error rate (BER), and the delay spread are lowered greatly, and the 3-dB bandwidth of the channel is extended, according to the findings.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134006405","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075597
Chahrazed Benrebbouh, Sarra Cherbal, Houssem Mansouri, A. Pathan
One of the most popular new technologies today is the Internet of Energy (IoE), which utilizes the Internet for collecting, organizing, optimizing and managing network energy information from various edge devices. In this way, a distributed smart energy infrastructure is developed. As IoE is essentially linked with the Internet, the cyber security concerns for this environment are also significant. Like any other technology connected with the Internet, IoE also is vulnerable to various kinds of attacks and threats. In this paper, we investigate the security issues in Internet of Energy. We study various security techniques proposed or developed for this environment during the recent years and discuss what to expect in the future.
{"title":"Future Security Issues in Internet of Energy","authors":"Chahrazed Benrebbouh, Sarra Cherbal, Houssem Mansouri, A. Pathan","doi":"10.1109/ICOASE56293.2022.10075597","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075597","url":null,"abstract":"One of the most popular new technologies today is the Internet of Energy (IoE), which utilizes the Internet for collecting, organizing, optimizing and managing network energy information from various edge devices. In this way, a distributed smart energy infrastructure is developed. As IoE is essentially linked with the Internet, the cyber security concerns for this environment are also significant. Like any other technology connected with the Internet, IoE also is vulnerable to various kinds of attacks and threats. In this paper, we investigate the security issues in Internet of Energy. We study various security techniques proposed or developed for this environment during the recent years and discuss what to expect in the future.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"149 S292","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120850530","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 : 2022-09-21DOI: 10.1109/ICOASE56293.2022.10075584
Zainab Qassim Mohammed Ali, S. T. Hasson
Wireless Sensor Networks (WSNs) have many crucial applications. WSNs can be created from number of deployed sensor nodes in a certain area. These nodes can be deployed randomly. Sensors are mainly utilized to track or monitor any modifications in a surrounding area. They can be used to monitor, gather information then, process and transfer the sensed data to a certain sink node. One of the main objectives of any proposed WSNs is to safely transfer the sensed data with minimum energy consumption and with reduced packet losses. The data transmissions in WSNs are affected by the network topology. The network topology in this paper is mesh topology. Each sensor in such a topology can communicate directly with its neighbors if they are located in its transmission range. The data transmission is performed through the shortest path. The problem in this work is to analyze and evaluate the effects of mesh topology on the coverage area and evaluate the cases when many sensor nodes send messages at the same time. The simulation results showed an average of 33.8 messages are sent and received in scenario 1. Four selected nodes are tested and their sent messages are (359, 531, 197 and 145) respectively.
{"title":"Simulating the Wireless Sensor Networks Coverage Area in a Mesh Topology","authors":"Zainab Qassim Mohammed Ali, S. T. Hasson","doi":"10.1109/ICOASE56293.2022.10075584","DOIUrl":"https://doi.org/10.1109/ICOASE56293.2022.10075584","url":null,"abstract":"Wireless Sensor Networks (WSNs) have many crucial applications. WSNs can be created from number of deployed sensor nodes in a certain area. These nodes can be deployed randomly. Sensors are mainly utilized to track or monitor any modifications in a surrounding area. They can be used to monitor, gather information then, process and transfer the sensed data to a certain sink node. One of the main objectives of any proposed WSNs is to safely transfer the sensed data with minimum energy consumption and with reduced packet losses. The data transmissions in WSNs are affected by the network topology. The network topology in this paper is mesh topology. Each sensor in such a topology can communicate directly with its neighbors if they are located in its transmission range. The data transmission is performed through the shortest path. The problem in this work is to analyze and evaluate the effects of mesh topology on the coverage area and evaluate the cases when many sensor nodes send messages at the same time. The simulation results showed an average of 33.8 messages are sent and received in scenario 1. Four selected nodes are tested and their sent messages are (359, 531, 197 and 145) respectively.","PeriodicalId":297211,"journal":{"name":"2022 4th International Conference on Advanced Science and Engineering (ICOASE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120960251","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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