Pub Date : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043241
S. Saminu, Guizhi Xu, Shuai Zhang, A. E. K. Isselmou, R. S. Zakariyya, A. H. Jabire
Epilepsy is a type of neurological disorder which can happen without serious warning and affects people almost at any age. It is a brain disorder caused by sudden and unprovoked seizures as a result of excitation of a lot of brain cells simultaneously which may lead to physical symptoms abnormalities and deformation such as failure in concentration, memory, attention etc. therefore, proper and efficient method of continues monitoring and detection of these epileptic seizures is paramount. This work presents an effective and efficient technique suitable for smart, low cost, power and real time devices that can be easily integrated with recent 5G network IoT devices for mobile applications, home and health care centers for monitoring and alert the doctors and patients about its occurrence to prevent a sudden collapse and consciousness which may cause injury and death. We proposed a low computational cost features extraction method by utilizing the efficacy of time-frequency, statistical and non-linear features known as hybrid techniques. The efficiency and accuracy of these smart devices is highly depends on quality of feature extraction methods and classifier performance. Therefore, this work employed two machine learning classifiers, support vector machine (SVM) and feedforward neural network (FFNN) to detect and classify interictal (normal) and ictal (seizure) signals. Discrete wavelet transform (DWT) is employed to decomposes the signals into decomposition levels as sub-bands of the signals to capture the non-stationarity of the EEG signals. Mean, median, maximum, minimum etc. were calculated for each sub-band as statistical parameters, non-linear features such as sample entropy, approximate entropy and wavelet energy were also calculated. The combination of features is then fed to two classifiers for the classification. Based on the performance measures such as accuracy, sensitivity and specificity, our proposed approach reveals a promising result with highest accuracy of 99.6%.
{"title":"Epilepsy Detection and Classification for Smart IoT Devices Using hybrid Technique","authors":"S. Saminu, Guizhi Xu, Shuai Zhang, A. E. K. Isselmou, R. S. Zakariyya, A. H. Jabire","doi":"10.1109/ICECCO48375.2019.9043241","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043241","url":null,"abstract":"Epilepsy is a type of neurological disorder which can happen without serious warning and affects people almost at any age. It is a brain disorder caused by sudden and unprovoked seizures as a result of excitation of a lot of brain cells simultaneously which may lead to physical symptoms abnormalities and deformation such as failure in concentration, memory, attention etc. therefore, proper and efficient method of continues monitoring and detection of these epileptic seizures is paramount. This work presents an effective and efficient technique suitable for smart, low cost, power and real time devices that can be easily integrated with recent 5G network IoT devices for mobile applications, home and health care centers for monitoring and alert the doctors and patients about its occurrence to prevent a sudden collapse and consciousness which may cause injury and death. We proposed a low computational cost features extraction method by utilizing the efficacy of time-frequency, statistical and non-linear features known as hybrid techniques. The efficiency and accuracy of these smart devices is highly depends on quality of feature extraction methods and classifier performance. Therefore, this work employed two machine learning classifiers, support vector machine (SVM) and feedforward neural network (FFNN) to detect and classify interictal (normal) and ictal (seizure) signals. Discrete wavelet transform (DWT) is employed to decomposes the signals into decomposition levels as sub-bands of the signals to capture the non-stationarity of the EEG signals. Mean, median, maximum, minimum etc. were calculated for each sub-band as statistical parameters, non-linear features such as sample entropy, approximate entropy and wavelet energy were also calculated. The combination of features is then fed to two classifiers for the classification. Based on the performance measures such as accuracy, sensitivity and specificity, our proposed approach reveals a promising result with highest accuracy of 99.6%.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121262444","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043293
Obinna Uchenna Obeleagu, Yusuf Aleshinloye Abass, Steve A. Adeshina
The task of predicting students’ performance has become more challenging due to the obscurity, volume, and irregularities of data. These factors compounded with the human element of mood and altitudes of the student and the perception of the lecturers by the students have brought about “SUBJECTIVITY” in the learning environment. This design seeks to eliminate “SUBJECTIVITY” in Student Learning Experience by leveraging on machine Learning algorithms & Methodology. This paper builds on existing techniques and aims to improve upon them. Success was achieved in this regard by combining academic and social variables in the attribute set. These variables will go a long way in improving student performance and success rates as well an explaining extensively the components of a student learning metric and its features.
{"title":"Sentiment Analysis In Student Learning Experience","authors":"Obinna Uchenna Obeleagu, Yusuf Aleshinloye Abass, Steve A. Adeshina","doi":"10.1109/ICECCO48375.2019.9043293","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043293","url":null,"abstract":"The task of predicting students’ performance has become more challenging due to the obscurity, volume, and irregularities of data. These factors compounded with the human element of mood and altitudes of the student and the perception of the lecturers by the students have brought about “SUBJECTIVITY” in the learning environment. This design seeks to eliminate “SUBJECTIVITY” in Student Learning Experience by leveraging on machine Learning algorithms & Methodology. This paper builds on existing techniques and aims to improve upon them. Success was achieved in this regard by combining academic and social variables in the attribute set. These variables will go a long way in improving student performance and success rates as well an explaining extensively the components of a student learning metric and its features.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124989266","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043297
Victor Odumuyiwa, Ukachi Osisiogu
This paper gives a review of the literature on the application of Hidden Markov Models in the field of sentiment analysis. This is done in relation to a research project on semantic representation and the use of probabilistic graphical models for the determination of sentiment in textual data. Relevant articles have been analyzed that correspond mainly to the certain variations of the implementation of HMM and a variety of use cases for the purpose of sentiment classification. Finally, this review presents the grounds for future works that seek to develop techniques for semantic text representations implemented with probabilistic graphical models (Hidden Markov Models) or that through a combination scheme allow for superior classification performance.
{"title":"A Systematic Review on Hidden Markov Models for Sentiment Analysis","authors":"Victor Odumuyiwa, Ukachi Osisiogu","doi":"10.1109/ICECCO48375.2019.9043297","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043297","url":null,"abstract":"This paper gives a review of the literature on the application of Hidden Markov Models in the field of sentiment analysis. This is done in relation to a research project on semantic representation and the use of probabilistic graphical models for the determination of sentiment in textual data. Relevant articles have been analyzed that correspond mainly to the certain variations of the implementation of HMM and a variety of use cases for the purpose of sentiment classification. Finally, this review presents the grounds for future works that seek to develop techniques for semantic text representations implemented with probabilistic graphical models (Hidden Markov Models) or that through a combination scheme allow for superior classification performance.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"49 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115340550","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043267
Lateefah Abdul-azeez, A. Aibinu, Sodiq Olanrewaju Akanmu, T. A. Folorunso, M. Salami
One of the famous biometric in use is the facial recognition, which uses statistical measurement of an individual face features to discover or determine his/her identity. Human are prone to errors or mistakes, therefore, using only security personnel cannot give us a perfect security mechanism. This paper explains the importance of biometric and also present various methods which biometric application can applied in solving various problem. It focuses on face recognition and face detection techniques which include Principle Components Analysis (PCA), Hidden Markov Model (HMM), and the Discrete Wavelet Transform (DWT). It briefly explains how the use of symmetry of the face can be used for recognition, the combination of audio and video in face recognition and also show that a face can be detected in a video. It also shows the various strengths and weaknesses from each method used.
{"title":"Intelligence Security Check System Using Face Recognition Algorithm: A Review","authors":"Lateefah Abdul-azeez, A. Aibinu, Sodiq Olanrewaju Akanmu, T. A. Folorunso, M. Salami","doi":"10.1109/ICECCO48375.2019.9043267","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043267","url":null,"abstract":"One of the famous biometric in use is the facial recognition, which uses statistical measurement of an individual face features to discover or determine his/her identity. Human are prone to errors or mistakes, therefore, using only security personnel cannot give us a perfect security mechanism. This paper explains the importance of biometric and also present various methods which biometric application can applied in solving various problem. It focuses on face recognition and face detection techniques which include Principle Components Analysis (PCA), Hidden Markov Model (HMM), and the Discrete Wavelet Transform (DWT). It briefly explains how the use of symmetry of the face can be used for recognition, the combination of audio and video in face recognition and also show that a face can be detected in a video. It also shows the various strengths and weaknesses from each method used.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122411442","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043279
Oladele.A. Daniel, F. Shaibu, Isreal Olu. Megbowon
This paper evaluates the performance of the developed bioreactor model with the following tuning techniques: Artificial Neural Network method, Fuzzy Logic method and Ziegler Nichols method. A model of the bioreactor was developed and an input of the stirrer speed and oxygen consumption was used as the input to control the temperature of the bioreactor. The stability of the bioreactor’s temperature was compared and recommendations were made. The Ziegler Nichols and fuzzy logic models were the most stable with a fuzzy logic technique having the least settling time. This paper has effectively shown how important tuning techniques are when using a PID controller to stable a chaotic system (in this case, bioreactor process plant). It has also shown that for the set conditions used in this paper, the fuzzy logic and the Ziegler Nichols tuning technique are the most stable and suitable.
{"title":"Evaluation of Three Tuning Techniques of PID Control for a Bioreactor Process Plant","authors":"Oladele.A. Daniel, F. Shaibu, Isreal Olu. Megbowon","doi":"10.1109/ICECCO48375.2019.9043279","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043279","url":null,"abstract":"This paper evaluates the performance of the developed bioreactor model with the following tuning techniques: Artificial Neural Network method, Fuzzy Logic method and Ziegler Nichols method. A model of the bioreactor was developed and an input of the stirrer speed and oxygen consumption was used as the input to control the temperature of the bioreactor. The stability of the bioreactor’s temperature was compared and recommendations were made. The Ziegler Nichols and fuzzy logic models were the most stable with a fuzzy logic technique having the least settling time. This paper has effectively shown how important tuning techniques are when using a PID controller to stable a chaotic system (in this case, bioreactor process plant). It has also shown that for the set conditions used in this paper, the fuzzy logic and the Ziegler Nichols tuning technique are the most stable and suitable.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129802697","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043271
A. Miyim, Abubakar Wakili
The explosion of mobile data usage due to the increase of mobile subscribers and emergence of new applications such as mobile TV and online gaming, which requires high quality of service is the driving force for developing Long-Term Evolution (LTE) mobile networks by 3GPP. Service providers are migrating to this network due to its promising quality of service to assist them meet the growing end-user demand for more bandwidth, high security and faster connectivity. Service providers in Nigeria claimed to have rolled out 4G (LTE) nationwide, yet mobile subscribers are still unhappy with network operators over slow network connection and poor quality of service. Base on this motive, OMNeT++ simulator was used to evaluate performance of LTE networks by varying number of user equipment (UE) connected to evolved Node Base station (eNB), distance of UE from eNB and mobility speed of UE. Performance metrics used are throughput, end-to-end delay and packet loss. We observed that the LTE network is capable of providing good quality voice call. Though, its quality is affected with increasing distances between UE and eNodeB, number of connected users, and mobility speed of user.
{"title":"Performance Evaluation of LTE Networks","authors":"A. Miyim, Abubakar Wakili","doi":"10.1109/ICECCO48375.2019.9043271","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043271","url":null,"abstract":"The explosion of mobile data usage due to the increase of mobile subscribers and emergence of new applications such as mobile TV and online gaming, which requires high quality of service is the driving force for developing Long-Term Evolution (LTE) mobile networks by 3GPP. Service providers are migrating to this network due to its promising quality of service to assist them meet the growing end-user demand for more bandwidth, high security and faster connectivity. Service providers in Nigeria claimed to have rolled out 4G (LTE) nationwide, yet mobile subscribers are still unhappy with network operators over slow network connection and poor quality of service. Base on this motive, OMNeT++ simulator was used to evaluate performance of LTE networks by varying number of user equipment (UE) connected to evolved Node Base station (eNB), distance of UE from eNB and mobility speed of UE. Performance metrics used are throughput, end-to-end delay and packet loss. We observed that the LTE network is capable of providing good quality voice call. Though, its quality is affected with increasing distances between UE and eNodeB, number of connected users, and mobility speed of user.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129883160","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043207
Ukachi Osisiogu
The adequate implementation of Cyber-Physical Security Systems of Smart Buildings and Infrastructure is vital. Threats when exploited cause negative impacts on the beneficial effects of SB; however, mitigation and defense techniques have been devised but there is a need for further research to produce smarter, robust and efficient systems.
{"title":"A Review on Cyber -Physical Security of Smart Buildings and Infrastructure","authors":"Ukachi Osisiogu","doi":"10.1109/ICECCO48375.2019.9043207","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043207","url":null,"abstract":"The adequate implementation of Cyber-Physical Security Systems of Smart Buildings and Infrastructure is vital. Threats when exploited cause negative impacts on the beneficial effects of SB; however, mitigation and defense techniques have been devised but there is a need for further research to produce smarter, robust and efficient systems.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127827795","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043250
E. O. Edward, J. Ojeniyi
Admissibility of Evidence is the eligibility of particular pieces of evidence for inception as part of the evidence in a case. Admissibility means the character or quality to be accepted and allowed to be presented or introduced as evidence in court. To be admissible means capable of being legally admitted or allowable or permissible as evidence or worthy of gaining entry or being admitted. This study focus on carrying out a systematic literature review and meta-analysis on Digital Evidence Admissibility. The methodology employed in this study was the querying of four academic database resources systematically and fundamentally identifying kinds of literature related to digital evidence admissibility through identification, screening, eligibility and inclusion criteria. The advantage of this study is revealing the gap and trends in digital evidence admissibility as the article published between the period of 2015 through 2018 are relative with the following variation 64%, 21% 7%, for the following respectively, IEEE, Science Direct, ACM Digital library, as well as Research Gate. While at the period under review, 2019 is yet to record publication in the field of research in Digital Evidence Admissibility. The period under review witnessed a low academic publication in the field of Digital Evidence admissibility. This research will aid in projecting future research in the aforementioned research field.
{"title":"A Systematic Literature Review On Digital Evidence Admissibility: Methodologies, Challenges and Research Directions","authors":"E. O. Edward, J. Ojeniyi","doi":"10.1109/ICECCO48375.2019.9043250","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043250","url":null,"abstract":"Admissibility of Evidence is the eligibility of particular pieces of evidence for inception as part of the evidence in a case. Admissibility means the character or quality to be accepted and allowed to be presented or introduced as evidence in court. To be admissible means capable of being legally admitted or allowable or permissible as evidence or worthy of gaining entry or being admitted. This study focus on carrying out a systematic literature review and meta-analysis on Digital Evidence Admissibility. The methodology employed in this study was the querying of four academic database resources systematically and fundamentally identifying kinds of literature related to digital evidence admissibility through identification, screening, eligibility and inclusion criteria. The advantage of this study is revealing the gap and trends in digital evidence admissibility as the article published between the period of 2015 through 2018 are relative with the following variation 64%, 21% 7%, for the following respectively, IEEE, Science Direct, ACM Digital library, as well as Research Gate. While at the period under review, 2019 is yet to record publication in the field of research in Digital Evidence Admissibility. The period under review witnessed a low academic publication in the field of Digital Evidence admissibility. This research will aid in projecting future research in the aforementioned research field.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127860639","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043253
Nazerke Sultanova, K. Kozhakhmet, R. Jantayev, Azhar Botbayeva
This paper considers construction of Kazakh language words. Kazakh language is the type of Turkic languages or alternatively called – agglutinative language where words are formed by attaching the finite sequence of suffixes. Kazakh morphology investigation was the main work done in construction of rule-based stemming algorithm. Stemmer algorithm will be useful in development of sentiment analysis for Kazakh language, because of its rareness and competency. Stemming algorithm works with aim to cut ending combinations. The results checked by using Machine Learning algorithms using annotated dataset, which were retrieved from KazCorpus dataset [7].
{"title":"Stemming algorithm for Kazakh Language using rule-based approach","authors":"Nazerke Sultanova, K. Kozhakhmet, R. Jantayev, Azhar Botbayeva","doi":"10.1109/ICECCO48375.2019.9043253","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043253","url":null,"abstract":"This paper considers construction of Kazakh language words. Kazakh language is the type of Turkic languages or alternatively called – agglutinative language where words are formed by attaching the finite sequence of suffixes. Kazakh morphology investigation was the main work done in construction of rule-based stemming algorithm. Stemmer algorithm will be useful in development of sentiment analysis for Kazakh language, because of its rareness and competency. Stemming algorithm works with aim to cut ending combinations. The results checked by using Machine Learning algorithms using annotated dataset, which were retrieved from KazCorpus dataset [7].","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"49 25","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131874018","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 : 2019-12-01DOI: 10.1109/ICECCO48375.2019.9043221
M. T. Dare, S. Zubair, Bala Alhaji Salihu, M. David, M. Abazeed
Power consumption is a key consideration in every WLAN MAC protocol design for wireless devices and extending battery life requires more efficient power management scheme considering that Carrier sensing by WLAN modules consumes enormous amount of power. Researchers over the years have proposed and implemented various schemes using a low-power Wake-up Radio for carrier sense which has proven to be effective. In this paper, a comprehensive literature review of the research progress in WuR-based energy saving is presented. This paper compares the various protocols already proposed for mitigating latency and energy consumption in WLAN networks and provides synthesis of wake-up radio (WUR) based carrier sensing approaches with analysis and discussions of merits and limitations of each technique. The operation principles of duty-cycle and wake-up radio bases MAC protocols were looked into in relation to how they affect energy efficiency and latency reduction.
{"title":"Literature Review of Energy Efficient Transmission in Wireless LANs by Using Low-Power Wake-Up Radio","authors":"M. T. Dare, S. Zubair, Bala Alhaji Salihu, M. David, M. Abazeed","doi":"10.1109/ICECCO48375.2019.9043221","DOIUrl":"https://doi.org/10.1109/ICECCO48375.2019.9043221","url":null,"abstract":"Power consumption is a key consideration in every WLAN MAC protocol design for wireless devices and extending battery life requires more efficient power management scheme considering that Carrier sensing by WLAN modules consumes enormous amount of power. Researchers over the years have proposed and implemented various schemes using a low-power Wake-up Radio for carrier sense which has proven to be effective. In this paper, a comprehensive literature review of the research progress in WuR-based energy saving is presented. This paper compares the various protocols already proposed for mitigating latency and energy consumption in WLAN networks and provides synthesis of wake-up radio (WUR) based carrier sensing approaches with analysis and discussions of merits and limitations of each technique. The operation principles of duty-cycle and wake-up radio bases MAC protocols were looked into in relation to how they affect energy efficiency and latency reduction.","PeriodicalId":166322,"journal":{"name":"2019 15th International Conference on Electronics, Computer and Computation (ICECCO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127415647","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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