Pub Date : 2021-09-13DOI: 10.1109/africon51333.2021.9571005
Poovendren Govender, K. Ogudo, Chabalala S. Chabalala
The demand for high-speed connectivity has increased globally. The covid-19 pandemic, which forced global lockdown and directly led to most of the global workforce to telecommute, dramatically exacerbated the need for quality mobile connectivity and high data rates. The 5th generation of mobile communication technology (5G), with its ultra-low latency and high bandwidth capacity, becomes a natural fit to overhaul communication infrastructure to meet the connectivity demands. Key to 5G’s performance is network slicing, which allows for the 5G network to be segmented into virtual networks that can be used to serve specific industry verticals. To assure Quality of Service (QoS), our paper proposes a model that creates network slices with respect to QoS requirements for various industry verticals. The proposed model is designed and evaluated using a software simulation technique, and the results obtained show that QoS-enabled network slicing guarantees improved performance in terms of throughput and loss in highly varying network conditions.
{"title":"Quality of Service Enabled Network Slicing Model in 5G and the Next Generation Virtualized Networks","authors":"Poovendren Govender, K. Ogudo, Chabalala S. Chabalala","doi":"10.1109/africon51333.2021.9571005","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9571005","url":null,"abstract":"The demand for high-speed connectivity has increased globally. The covid-19 pandemic, which forced global lockdown and directly led to most of the global workforce to telecommute, dramatically exacerbated the need for quality mobile connectivity and high data rates. The 5th generation of mobile communication technology (5G), with its ultra-low latency and high bandwidth capacity, becomes a natural fit to overhaul communication infrastructure to meet the connectivity demands. Key to 5G’s performance is network slicing, which allows for the 5G network to be segmented into virtual networks that can be used to serve specific industry verticals. To assure Quality of Service (QoS), our paper proposes a model that creates network slices with respect to QoS requirements for various industry verticals. The proposed model is designed and evaluated using a software simulation technique, and the results obtained show that QoS-enabled network slicing guarantees improved performance in terms of throughput and loss in highly varying network conditions.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127478930","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570945
Ezra Misaki
The revolution of smartphone usage in agriculture by small-scale farmers has improved productivity by establishing a reliable agricultural knowledge information system. Despite the development achieved by the smartphone in agriculture, information on how the applications improve the farming value chain is still very scanty. Consequently, this study set out to assess the currently used application technologies by small-scale farmers at Miono to upgrade the user requirements for present and future applications. The study applied qualitative interview and observation approach in collecting data and thematic analysis to analyze the data. Results show that farmers at Miono used messaging applications, call applications, calculator apps and clock applications the most. On the other hand, the farmers rarely used WhatsApp, Facebook, email applications, and photo apps. Thus, for real present and future development, farmers need upgraded apps that disseminate information on local pests, pesticides, weather forecasts, and market information.
{"title":"Assessment of the Used Mobile Applications by Small-Scale Farmers at Miono and User Requirements in the Present and Future Mobile Apps","authors":"Ezra Misaki","doi":"10.1109/africon51333.2021.9570945","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570945","url":null,"abstract":"The revolution of smartphone usage in agriculture by small-scale farmers has improved productivity by establishing a reliable agricultural knowledge information system. Despite the development achieved by the smartphone in agriculture, information on how the applications improve the farming value chain is still very scanty. Consequently, this study set out to assess the currently used application technologies by small-scale farmers at Miono to upgrade the user requirements for present and future applications. The study applied qualitative interview and observation approach in collecting data and thematic analysis to analyze the data. Results show that farmers at Miono used messaging applications, call applications, calculator apps and clock applications the most. On the other hand, the farmers rarely used WhatsApp, Facebook, email applications, and photo apps. Thus, for real present and future development, farmers need upgraded apps that disseminate information on local pests, pesticides, weather forecasts, and market information.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121023924","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570983
Tawanda Matereke, Clement N. Nyirenda, Mehrdad Ghaziasgar
This paper presents a study on crime classification using two 3D deep learning algorithms, i.e., 3D Convolutional Neural Network and the 3D Residual Network. The Chicago crime dataset, which has 7.29 million records, collected from 2001 to 2020, is used for training the models. The models are evaluated by using F1 score, Area Under Receiver Operator Curve (AUROC), and Area Under Curve - Precision Recall (AUCPR). Furthermore, the effectiveness of spatial grid resolutions on the performance of the models is also evaluated. Results show that the 3D ResNet-18 achieved the best performance with an F1 score of 0.9985, whereas the 3D CNN achieved an F1 score of 0.9979, during training with a spatial resolution of 16 pixels. Furthermore, the 3D ResNet-18 achieved an accuracy of 0.92 and the 3D CNN achieved an accuracy of 0.87 during model testing. In terms of future work, we intend to test these algorithms on multi-label classification and regression crime problems, improve the performance of the 3D CNN by adding RNN layers, and evaluate the implementation of 3D ResNeXt for crime prediction and classification.
{"title":"A Performance Evaluation of 3D Deep Learning Algorithms for Crime Classification","authors":"Tawanda Matereke, Clement N. Nyirenda, Mehrdad Ghaziasgar","doi":"10.1109/africon51333.2021.9570983","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570983","url":null,"abstract":"This paper presents a study on crime classification using two 3D deep learning algorithms, i.e., 3D Convolutional Neural Network and the 3D Residual Network. The Chicago crime dataset, which has 7.29 million records, collected from 2001 to 2020, is used for training the models. The models are evaluated by using F1 score, Area Under Receiver Operator Curve (AUROC), and Area Under Curve - Precision Recall (AUCPR). Furthermore, the effectiveness of spatial grid resolutions on the performance of the models is also evaluated. Results show that the 3D ResNet-18 achieved the best performance with an F1 score of 0.9985, whereas the 3D CNN achieved an F1 score of 0.9979, during training with a spatial resolution of 16 pixels. Furthermore, the 3D ResNet-18 achieved an accuracy of 0.92 and the 3D CNN achieved an accuracy of 0.87 during model testing. In terms of future work, we intend to test these algorithms on multi-label classification and regression crime problems, improve the performance of the 3D CNN by adding RNN layers, and evaluate the implementation of 3D ResNeXt for crime prediction and classification.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"410 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116527073","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570882
Jacob J. Greeff, A. Nel, Reolyn Heymann, Johnson Carroll
Capstone projects are the projects students undertake during undergraduate studies where they serve as the final gatekeeping process in engineering degrees to ensure students have the ability to leverage all of the knowledge they have gained in the solving of an open ended problem. As part of a larger project to improve the experience of students in a capstone project module, a challenge-based system has been implemented with inspiration taken from the Superbetter approach. This paper introduces the wider project context, presents the three design cycles the challenge system went through and presents results. In this paper it is shown that the implementation of the artefact was ultimately not a success, and the reasons for this are explored and recommendations for the implementation of similar systems in the future in other contexts are presented.
{"title":"Academic challenges as part of capstone project resilience training","authors":"Jacob J. Greeff, A. Nel, Reolyn Heymann, Johnson Carroll","doi":"10.1109/africon51333.2021.9570882","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570882","url":null,"abstract":"Capstone projects are the projects students undertake during undergraduate studies where they serve as the final gatekeeping process in engineering degrees to ensure students have the ability to leverage all of the knowledge they have gained in the solving of an open ended problem. As part of a larger project to improve the experience of students in a capstone project module, a challenge-based system has been implemented with inspiration taken from the Superbetter approach. This paper introduces the wider project context, presents the three design cycles the challenge system went through and presents results. In this paper it is shown that the implementation of the artefact was ultimately not a success, and the reasons for this are explored and recommendations for the implementation of similar systems in the future in other contexts are presented.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132349733","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570989
L. Butgereit
Benford’s Law has been used to attempt to determine if a list of numbers has been artificially manipulated in any way. Benford’s Law is applicable to many types of lists of numbers and is often used in the accounting domain to flag possible fraud. This paper provides a history of Benford’s Law and presents a number of examples where Benford’s Law applies in the domain of geography, transportation, and economics. The goal of this research, however, is to focus Benford’s Law on the list of numbers representing daily Covid-19 cases and daily Covid-19 deaths. The lists of numbers were analysed with respect to Benford’s Law and graphs were produced comparing the Covid-19 numbers against what was predicted by Benford’s Law. The conclusion of this paper is that at a country level or at a specific date level, the datasets do not have the proper characteristics and Benford’s Law can not be used on those datasets. At a continent level, however, the datasets are much larger and wide ranging. Benford’s Law can be applied to continental datasets.
{"title":"Focusing Benford’s Law on the Daily Covid-19 Cases Numbers and Daily Covid-19 Deaths Numbers","authors":"L. Butgereit","doi":"10.1109/africon51333.2021.9570989","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570989","url":null,"abstract":"Benford’s Law has been used to attempt to determine if a list of numbers has been artificially manipulated in any way. Benford’s Law is applicable to many types of lists of numbers and is often used in the accounting domain to flag possible fraud. This paper provides a history of Benford’s Law and presents a number of examples where Benford’s Law applies in the domain of geography, transportation, and economics. The goal of this research, however, is to focus Benford’s Law on the list of numbers representing daily Covid-19 cases and daily Covid-19 deaths. The lists of numbers were analysed with respect to Benford’s Law and graphs were produced comparing the Covid-19 numbers against what was predicted by Benford’s Law. The conclusion of this paper is that at a country level or at a specific date level, the datasets do not have the proper characteristics and Benford’s Law can not be used on those datasets. At a continent level, however, the datasets are much larger and wide ranging. Benford’s Law can be applied to continental datasets.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124769836","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570950
Michael Njeru, C. Maina, K. Langat
Monitoring of wild animals has taken different approaches with an aim to provide vital information used in animal protection in their natural habitats. To recognize animal species without human trackers requires machine learning models that extract specie's features from an image. This project proposes a method of counting animals in an image and specifying the species of each animal using Unet and a variant of the SqueezeNet model. To train the Unet model, images and corresponding masks are used as the training data. Different optimizers are applied to each model. During inference, Unet outputs a binary mask with ones where an animal is detected and zeros elsewhere. SqueezeNet model is trained with images corresponding to six classes: bushbuck, impala, llama, warthog, waterbuck, and zebra. Three variants of the SqueezeNet model have been trained. The first contains the original backbone while the other two have the original backbone with an additional fire module. In one model the Fire module is similar to the Fire modules of the original backbone while in the other model, the extra fire module contains batch normalization layers. The trained models show that Unet trained with Nadam optimizer achieves the highest dice coefficient while the SqueezeNet with an extra Fire module containing batch norm layers and RMSprop optimizer achieves the highest training accuracy. The combined system containing the two models takes an image and outputs the image with bounding boxes around each animal and the corresponding animal species. The system achieves both counting and recognition of the species for each image placed at the input.
{"title":"Mammalian Species Detection Using a Cascade of Unet and SqueezeNet","authors":"Michael Njeru, C. Maina, K. Langat","doi":"10.1109/africon51333.2021.9570950","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570950","url":null,"abstract":"Monitoring of wild animals has taken different approaches with an aim to provide vital information used in animal protection in their natural habitats. To recognize animal species without human trackers requires machine learning models that extract specie's features from an image. This project proposes a method of counting animals in an image and specifying the species of each animal using Unet and a variant of the SqueezeNet model. To train the Unet model, images and corresponding masks are used as the training data. Different optimizers are applied to each model. During inference, Unet outputs a binary mask with ones where an animal is detected and zeros elsewhere. SqueezeNet model is trained with images corresponding to six classes: bushbuck, impala, llama, warthog, waterbuck, and zebra. Three variants of the SqueezeNet model have been trained. The first contains the original backbone while the other two have the original backbone with an additional fire module. In one model the Fire module is similar to the Fire modules of the original backbone while in the other model, the extra fire module contains batch normalization layers. The trained models show that Unet trained with Nadam optimizer achieves the highest dice coefficient while the SqueezeNet with an extra Fire module containing batch norm layers and RMSprop optimizer achieves the highest training accuracy. The combined system containing the two models takes an image and outputs the image with bounding boxes around each animal and the corresponding animal species. The system achieves both counting and recognition of the species for each image placed at the input.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134304194","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570895
Cameron S Sheehan, T. Green, N. Daina
Electric motorcycles are being introduced in some African countries to combat the negative environmental impacts from the rapid growth in the use of traditional internal combustion engine motorcycle taxis. However, the electricity systems in many of these countries are strained, with generation and/or distribution capacity at their limits, leading to regular power outages that could impact the charging of these e-motorcycles. These fragile grids may be put under further strain by additional e-motorcycle charging. Commercial motorcycle taxi drivers may not be willing to wait for extended periods to charge during their shift. The use of battery swapping stations could mitigate these issues. However, modelling of their system impacts is required to fully understand their potential. This paper presents a hybrid model to simulate the key operational processes of battery swapping stations and their energy systems, allowing various configurations and scenarios to be investigated for the specific context of e-motorcycles in Africa. The configuration parameters include the numbers of batteries and charging slots, the charging power, and the addition of solar PV and static battery energy storage capacity. Power outages can be modelled for various scenarios. A test case of a battery swap station in Nairobi, Kenya, was used to showcase and validate the model. The results demonstrated how the various sub-models performed and interacted with each other, and clearly showed what impact the chosen BSS configuration would have on the grid.
{"title":"A Simulation Approach to Analyse the Impacts of Battery Swap Stations for e-Motorcycles in Africa","authors":"Cameron S Sheehan, T. Green, N. Daina","doi":"10.1109/africon51333.2021.9570895","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570895","url":null,"abstract":"Electric motorcycles are being introduced in some African countries to combat the negative environmental impacts from the rapid growth in the use of traditional internal combustion engine motorcycle taxis. However, the electricity systems in many of these countries are strained, with generation and/or distribution capacity at their limits, leading to regular power outages that could impact the charging of these e-motorcycles. These fragile grids may be put under further strain by additional e-motorcycle charging. Commercial motorcycle taxi drivers may not be willing to wait for extended periods to charge during their shift. The use of battery swapping stations could mitigate these issues. However, modelling of their system impacts is required to fully understand their potential. This paper presents a hybrid model to simulate the key operational processes of battery swapping stations and their energy systems, allowing various configurations and scenarios to be investigated for the specific context of e-motorcycles in Africa. The configuration parameters include the numbers of batteries and charging slots, the charging power, and the addition of solar PV and static battery energy storage capacity. Power outages can be modelled for various scenarios. A test case of a battery swap station in Nairobi, Kenya, was used to showcase and validate the model. The results demonstrated how the various sub-models performed and interacted with each other, and clearly showed what impact the chosen BSS configuration would have on the grid.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133273015","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9571000
F. Mthethwa, C. Gomes, D. Dorrell
Individual remote agro-based micro-grid is prone to reliability and resilient instability issues due to large sudden load or generation fluctuations. Therefore, it is important to integrate several micro-grids to solve the issue of reliability. An interconnected micro-grid system takes advantage of various complementary energy sources and effectively coordinates the energy sharing among the neighbouring micro-grids to improve the stability, reliability, and energy efficiency of the system in case of loss or insufficient power supply from one micro-grid. Control of energy management and communication for inter-micro-grid becomes complex and challenging in these areas due to the excess demand of agro-based consumer loads. In this paper, a decision-making algorithm that provides smart solution in interconnecting several neighbouring micro-grids to optimally share the supply is developed. A case study is presented and HOMER Pro software is used to optimize three proposed micro-grids and ensure optimal energy sharing.
{"title":"Development of Optimal Algorithm to Interconnect Multiple Microgrids in an Agricultural-based Remote Community","authors":"F. Mthethwa, C. Gomes, D. Dorrell","doi":"10.1109/africon51333.2021.9571000","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9571000","url":null,"abstract":"Individual remote agro-based micro-grid is prone to reliability and resilient instability issues due to large sudden load or generation fluctuations. Therefore, it is important to integrate several micro-grids to solve the issue of reliability. An interconnected micro-grid system takes advantage of various complementary energy sources and effectively coordinates the energy sharing among the neighbouring micro-grids to improve the stability, reliability, and energy efficiency of the system in case of loss or insufficient power supply from one micro-grid. Control of energy management and communication for inter-micro-grid becomes complex and challenging in these areas due to the excess demand of agro-based consumer loads. In this paper, a decision-making algorithm that provides smart solution in interconnecting several neighbouring micro-grids to optimally share the supply is developed. A case study is presented and HOMER Pro software is used to optimize three proposed micro-grids and ensure optimal energy sharing.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132692201","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570845
Naveenbalaji Gowthaman, V. Srivastava
The performance of the transistors is a measure for the system to perform desired output. The research in the development of transistors is continuously growing and defines an efficient system and device modeling. This work shows a comparative analysis of the various materials in the double-gate (DG) MOSFET. Here, the DG MOSFETs have been constructed using high-ƙ dielectrics to reduce the short channel effects and improve the performance of the transistors, which is the unit cell of the industrial and consumer electronics devices. This MOSFET can further be optimized by enhancing the analog characteristics in the nanometer regime. This work focuses on the performance of the DG MOSFETs by considering channels like Indium Arsenide (InAs) and Indium Phosphide (InP) in the Aluminium Gallium Arsenide (AlxGa1-xAs) and Gallium Arsenide Antimonide (GaAs1-xSbx) substrates. From the simulation and tabulations, it is evident that the properties of the DG MOSFETs with these novel materials change drastically, thereby inferring the optimum materials in MOSFETs for the high speed and long haul RF applications. In this work, three different models have been proposed, namely AlxGa1-xAs/HfO2, AlxGa1-xAs/La2O3, and GaAs1-xSbx/La2O3; which shows improvement in threshold voltage with 1.16%, 1.20%, and 1.64% respectively when compared to the conventional Silicon-based DG MOSFETs.
{"title":"Arbitrary Alloy Semiconductor Material Based DG MOSFET for High-Frequency Industrial and Hybrid Consumer Applications","authors":"Naveenbalaji Gowthaman, V. Srivastava","doi":"10.1109/africon51333.2021.9570845","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570845","url":null,"abstract":"The performance of the transistors is a measure for the system to perform desired output. The research in the development of transistors is continuously growing and defines an efficient system and device modeling. This work shows a comparative analysis of the various materials in the double-gate (DG) MOSFET. Here, the DG MOSFETs have been constructed using high-ƙ dielectrics to reduce the short channel effects and improve the performance of the transistors, which is the unit cell of the industrial and consumer electronics devices. This MOSFET can further be optimized by enhancing the analog characteristics in the nanometer regime. This work focuses on the performance of the DG MOSFETs by considering channels like Indium Arsenide (InAs) and Indium Phosphide (InP) in the Aluminium Gallium Arsenide (AlxGa1-xAs) and Gallium Arsenide Antimonide (GaAs1-xSbx) substrates. From the simulation and tabulations, it is evident that the properties of the DG MOSFETs with these novel materials change drastically, thereby inferring the optimum materials in MOSFETs for the high speed and long haul RF applications. In this work, three different models have been proposed, namely AlxGa1-xAs/HfO2, AlxGa1-xAs/La2O3, and GaAs1-xSbx/La2O3; which shows improvement in threshold voltage with 1.16%, 1.20%, and 1.64% respectively when compared to the conventional Silicon-based DG MOSFETs.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115466898","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 : 2021-09-13DOI: 10.1109/africon51333.2021.9570971
D. Modungwa, F. Mekuria, Mzuziwezulu Kekana
The design of a biomimicry autonomous underwater robot for monitoring and harvesting invasive weeds in lakes is presented in this paper. The systematic design of the robot focuses on integrating 5G-AI-IoT as effective technological tools to autonomously monitor and harvest invasive weeds in order to replace traditional weed control approaches. The robustness and versatility of the robotic platform to structural topology and autonomous navigation that uses convolutional neural network methods and unsupervised learning techniques will be demonstrated. The robotic concept design will investigate real time sensing, mapping and visualization of the invasive weeds. The system based on real-time mapping information obtained from the swarm of drones will also manage the control of the underwater robots equipped with smart networked sensors using State of the Art IoT technologies. The mechanical dislodging machine will be guided to the mapped areas and accurately controlled and guided through smart sensors via the 5G Ultra-reliable Low-Latency Communication Control (URLLC) and tactile control system to dislodge the invasive weed with no impact on other organisms and the biodiversity of the lake.
{"title":"Conceptual Development of an Autonomous Underwater Robot Design for Monitoring and Harvesting Invasive Weeds","authors":"D. Modungwa, F. Mekuria, Mzuziwezulu Kekana","doi":"10.1109/africon51333.2021.9570971","DOIUrl":"https://doi.org/10.1109/africon51333.2021.9570971","url":null,"abstract":"The design of a biomimicry autonomous underwater robot for monitoring and harvesting invasive weeds in lakes is presented in this paper. The systematic design of the robot focuses on integrating 5G-AI-IoT as effective technological tools to autonomously monitor and harvest invasive weeds in order to replace traditional weed control approaches. The robustness and versatility of the robotic platform to structural topology and autonomous navigation that uses convolutional neural network methods and unsupervised learning techniques will be demonstrated. The robotic concept design will investigate real time sensing, mapping and visualization of the invasive weeds. The system based on real-time mapping information obtained from the swarm of drones will also manage the control of the underwater robots equipped with smart networked sensors using State of the Art IoT technologies. The mechanical dislodging machine will be guided to the mapped areas and accurately controlled and guided through smart sensors via the 5G Ultra-reliable Low-Latency Communication Control (URLLC) and tactile control system to dislodge the invasive weed with no impact on other organisms and the biodiversity of the lake.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116179515","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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