Pub Date : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845650
Dillys Larbi, K. Anthun, F. Asah, O. Debrah, Konstantinos Antypas
The use of electronic health systems is rapidly spreading in low-and middle-income countries (LLMICs). Empirical evidence shows that eHealth systems can improve access, quality, and equitable healthcare delivery, especially for the poor and vulnerable. Studies suggest that a lack of systems thinking leads to inadequate technical infrastructure, lack of interoperability, streamlining of patient-and health information sharing. This article assesses the BETTEReHEALTH strategic priority factors from four African countries: Ethiopia, Ghana, Malawi, and Tunisia. The primary data source was eHealth policies from the four countries. A document analysis was conducted, complemented by deductive, qualitative content analysis. The results show these countries have adopted and implemented eHealth policies. They have dedicated governing bodies that aim to strengthen the coordination of eHealth efforts. However, there is a need for more robust government support and regulation in creating a sustainable national eHealth environment.
{"title":"Assessing Strategic Priority Factors in eHealth Policies of Four African Countries","authors":"Dillys Larbi, K. Anthun, F. Asah, O. Debrah, Konstantinos Antypas","doi":"10.23919/IST-Africa56635.2022.9845650","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845650","url":null,"abstract":"The use of electronic health systems is rapidly spreading in low-and middle-income countries (LLMICs). Empirical evidence shows that eHealth systems can improve access, quality, and equitable healthcare delivery, especially for the poor and vulnerable. Studies suggest that a lack of systems thinking leads to inadequate technical infrastructure, lack of interoperability, streamlining of patient-and health information sharing. This article assesses the BETTEReHEALTH strategic priority factors from four African countries: Ethiopia, Ghana, Malawi, and Tunisia. The primary data source was eHealth policies from the four countries. A document analysis was conducted, complemented by deductive, qualitative content analysis. The results show these countries have adopted and implemented eHealth policies. They have dedicated governing bodies that aim to strengthen the coordination of eHealth efforts. However, there is a need for more robust government support and regulation in creating a sustainable national eHealth environment.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116893753","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845545
E. O. Aliyu, E. Kotzé
Next word prediction task is the application of a language model in natural language generation that deals with generating words by repeatedly sampling the next word conditioned on the previous choices. This paper proposes a stacked language model for optimized next word generation using three models. In stage I, the meaning of a word is captured through learn embedding and the structure of the text sequence is encoded using a stacked Long Short Term Memory (LSTM). In stage II, a Bidirectional Long Short Term Memory (Bi-LSTM) stacking on top of the unidirectional LSTM encodes the structure of the text sequences, while in stage III, a two-layer Gated Recurrent Unit (GRU) is used to capture text sequences of data. The proposed system was implemented using Python 3.7, Tensorflow 2.6.0 with Keras and a Nvidia Graphical Processing Unit (GPU). The proposed deep learning models were trained using the Pride and Prejudice corpus from the Project Gutenberg library of ebooks. The evaluation was performed by predicting the next 3 words after considering 10 sets of text sequences. From the experiment carried out, the accuracy of the two-layer LSTM model measured 83%, the accuracy of the Bi-LSTM stacking on unidirectional LSTM model measured 79%, and the accuracy of the two-layer GRU model measured 81%. Regarding predictions, the two-layer LSTM predicted the 10 sequences correctly, the Bi-LSTM stacking on unidirectional LSTM predicted 8 sequences correctly and the two-layer GRU predicted 7 sequences correctly.
{"title":"Stacked Language Models for an Optimized Next Word Generation","authors":"E. O. Aliyu, E. Kotzé","doi":"10.23919/IST-Africa56635.2022.9845545","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845545","url":null,"abstract":"Next word prediction task is the application of a language model in natural language generation that deals with generating words by repeatedly sampling the next word conditioned on the previous choices. This paper proposes a stacked language model for optimized next word generation using three models. In stage I, the meaning of a word is captured through learn embedding and the structure of the text sequence is encoded using a stacked Long Short Term Memory (LSTM). In stage II, a Bidirectional Long Short Term Memory (Bi-LSTM) stacking on top of the unidirectional LSTM encodes the structure of the text sequences, while in stage III, a two-layer Gated Recurrent Unit (GRU) is used to capture text sequences of data. The proposed system was implemented using Python 3.7, Tensorflow 2.6.0 with Keras and a Nvidia Graphical Processing Unit (GPU). The proposed deep learning models were trained using the Pride and Prejudice corpus from the Project Gutenberg library of ebooks. The evaluation was performed by predicting the next 3 words after considering 10 sets of text sequences. From the experiment carried out, the accuracy of the two-layer LSTM model measured 83%, the accuracy of the Bi-LSTM stacking on unidirectional LSTM model measured 79%, and the accuracy of the two-layer GRU model measured 81%. Regarding predictions, the two-layer LSTM predicted the 10 sequences correctly, the Bi-LSTM stacking on unidirectional LSTM predicted 8 sequences correctly and the two-layer GRU predicted 7 sequences correctly.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124183782","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845633
Thembakazi.M. Kangapi, E. Chindenga
Mobile banking has become the most preferred banking method globally due to the prevalence and popularity of mobile technology. The widespread adoption and usage of mobile devices for banking has attracted a lot of cybercrime. Despite the national government gazetting NCPF to standardise cybersecurity efforts in South Africa, it is not adequately regulated as cybercrime continues to rise. This paper surveyed the literature to develop a cybersecurity culture framework to mitigate cybersecurity challenges in the South African mobile banking sector. The socio-technical systems theory was adopted as the underlying research theory of this paper. A literature survey was conducted, and the outcomes were thematically interpreted. Findings revealed that critical components of a successful cybersecurity culture framework should incorporate support, cybersecurity collaboration, policy, and monitoring and evaluation. The proposed framework may help to secure mobile banking communities from ever-evolving cyberattacks.
{"title":"Towards a Cybersecurity Culture Framework for Mobile Banking in South Africa","authors":"Thembakazi.M. Kangapi, E. Chindenga","doi":"10.23919/IST-Africa56635.2022.9845633","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845633","url":null,"abstract":"Mobile banking has become the most preferred banking method globally due to the prevalence and popularity of mobile technology. The widespread adoption and usage of mobile devices for banking has attracted a lot of cybercrime. Despite the national government gazetting NCPF to standardise cybersecurity efforts in South Africa, it is not adequately regulated as cybercrime continues to rise. This paper surveyed the literature to develop a cybersecurity culture framework to mitigate cybersecurity challenges in the South African mobile banking sector. The socio-technical systems theory was adopted as the underlying research theory of this paper. A literature survey was conducted, and the outcomes were thematically interpreted. Findings revealed that critical components of a successful cybersecurity culture framework should incorporate support, cybersecurity collaboration, policy, and monitoring and evaluation. The proposed framework may help to secure mobile banking communities from ever-evolving cyberattacks.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115941256","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845559
Nabeelah Pooloo, Wafiik Aumeer, Rajeev Khoodeeram
The latest spinoffs in the field of Autonomous Vehicles have paved way for a revolution in mobility and transportation; particularly in the warehousing and distribution sector. AMRs, Autonomous Mobile Robots, are being deployed to assist in warehousing activities as they present multiple advantages. In this paper, an AMR coupled with image processing and deep learning is introduced as a novel approach to solve a two-fold problem: surveillance and disinfection. Deep learning will make use of real-time data collected by the AMR’s camera as a smart surveillance method for abnormal event detection. YOLOv4 is used to train a custom dataset for object detection on five different classes. The latter obtained a 74.40% accuracy. The vehicle will also be used to diffuse disinfecting agents as a mean to sanitize the stores and stocks against Covid-19. Moreover, autonomous navigation of the AMR will be based on image processing techniques for path track detection.
{"title":"Design of an AMR Using Image Processing and Deep Learning for Monitoring Safety Aspects in Warehouse","authors":"Nabeelah Pooloo, Wafiik Aumeer, Rajeev Khoodeeram","doi":"10.23919/IST-Africa56635.2022.9845559","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845559","url":null,"abstract":"The latest spinoffs in the field of Autonomous Vehicles have paved way for a revolution in mobility and transportation; particularly in the warehousing and distribution sector. AMRs, Autonomous Mobile Robots, are being deployed to assist in warehousing activities as they present multiple advantages. In this paper, an AMR coupled with image processing and deep learning is introduced as a novel approach to solve a two-fold problem: surveillance and disinfection. Deep learning will make use of real-time data collected by the AMR’s camera as a smart surveillance method for abnormal event detection. YOLOv4 is used to train a custom dataset for object detection on five different classes. The latter obtained a 74.40% accuracy. The vehicle will also be used to diffuse disinfecting agents as a mean to sanitize the stores and stocks against Covid-19. Moreover, autonomous navigation of the AMR will be based on image processing techniques for path track detection.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126108007","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845623
Fhulufhelo Mudau, Terence L van Zyl, A. Molotsi, Patrik Waldmann, K. Dzama, M. C. Marufu
Ticks and tick-borne diseases (TTBDs) are one of the biggest economic threats to livestock production systems in the world endangering approximately 80% of the global cattle population, especially in the sub- and tropical regions. It remains a challenge to effectively control ticks with acaricides due to the ability of ticks to develop resistance against acaricides. Algorithms for a cheap, rapid, and accurate method of quantifying tick burdens on cattle using infrared thermographic imaging technology could mitigate the danger of TTBDs in cattle. Tick counts were conducted once a month under natural challenge over a six-month period on 19 Bonsmara and 36 Nguni cattle located at ARC Roodeplaat and Loskop farms throughout both warmer climates and cooler climates. Thermographic images of both engorged & unfed females and males ticks were taken from cattle from February 2021 until July 2021. The deep learning models with architectures: “ConvNet” and “MobileNet” were trained on a dataset of 1124 “thermograms” to detect ticks on cattle. ConvNet model achieved a training and validation accuracy of $sim 90$ and 60%, respectively. Whereas MobileNet scored a training and validation accuracy of $sim 95$ and 75%, respectively. Finally, deep learning was successfully used to detect ticks on cattle using pretrained convolutional neural networks (CNNS).
{"title":"Application of Convolutional Neural Networks to the Quantification of Tick Burdens on Cattle Using Infrared Thermographic Imaging","authors":"Fhulufhelo Mudau, Terence L van Zyl, A. Molotsi, Patrik Waldmann, K. Dzama, M. C. Marufu","doi":"10.23919/IST-Africa56635.2022.9845623","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845623","url":null,"abstract":"Ticks and tick-borne diseases (TTBDs) are one of the biggest economic threats to livestock production systems in the world endangering approximately 80% of the global cattle population, especially in the sub- and tropical regions. It remains a challenge to effectively control ticks with acaricides due to the ability of ticks to develop resistance against acaricides. Algorithms for a cheap, rapid, and accurate method of quantifying tick burdens on cattle using infrared thermographic imaging technology could mitigate the danger of TTBDs in cattle. Tick counts were conducted once a month under natural challenge over a six-month period on 19 Bonsmara and 36 Nguni cattle located at ARC Roodeplaat and Loskop farms throughout both warmer climates and cooler climates. Thermographic images of both engorged & unfed females and males ticks were taken from cattle from February 2021 until July 2021. The deep learning models with architectures: “ConvNet” and “MobileNet” were trained on a dataset of 1124 “thermograms” to detect ticks on cattle. ConvNet model achieved a training and validation accuracy of $sim 90$ and 60%, respectively. Whereas MobileNet scored a training and validation accuracy of $sim 95$ and 75%, respectively. Finally, deep learning was successfully used to detect ticks on cattle using pretrained convolutional neural networks (CNNS).","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115408250","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845658
David Joshen Bastien, Vijay Prakash Chumroo, Johan Patrice Bastien
This case study focuses on laying down the foundations for the development of Kreol Morisien NLP (KreMoN) which is a series of Natural Language Processing tools to be used to process Mauritian Creole. While most of the works done so far focuses on detailing the Machine Learning algorithms, this work focuses on the first steps needed for any low resourced language which is the collection of data. We present a process currently being used to collect audio and textual data for a low resourced language like Mauritian Creole. This data will be used to develop a speech-to-text system as well as an Information Extractor for Mauritian Creole. As part of the case study, we detail some of the works made using existing textual data in Non standardized Mauritian Creole where an NLP pre-processing pipeline adapted for low resourced languages have been developed.
{"title":"Case Study on Data Collection of Kreol Morisien, a Low-Resourced Creole Language","authors":"David Joshen Bastien, Vijay Prakash Chumroo, Johan Patrice Bastien","doi":"10.23919/IST-Africa56635.2022.9845658","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845658","url":null,"abstract":"This case study focuses on laying down the foundations for the development of Kreol Morisien NLP (KreMoN) which is a series of Natural Language Processing tools to be used to process Mauritian Creole. While most of the works done so far focuses on detailing the Machine Learning algorithms, this work focuses on the first steps needed for any low resourced language which is the collection of data. We present a process currently being used to collect audio and textual data for a low resourced language like Mauritian Creole. This data will be used to develop a speech-to-text system as well as an Information Extractor for Mauritian Creole. As part of the case study, we detail some of the works made using existing textual data in Non standardized Mauritian Creole where an NLP pre-processing pipeline adapted for low resourced languages have been developed.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114496027","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845524
O. Čerba, Viktorie Sloupová, J. Macura, Sarah Velten
Despite the severe impacts of the COVID-19 pandemic on the tourism industry, tourism has become a key sector for economic development in the African continent. Nevertheless, the tourism sector in Africa is still in its early stages and much of its touristic potential remains untapped. To harness this potential, rational and wise tourism planning and management are key. These need to be based on an assessment of the tourism attractiveness of the different territories. In this paper we introduce a method of assessing tourism attractiveness in Africa on a regional level and ways to present the results of such assessments in an easily interpretable way. For these purposes, we calculate a regional tourism attractiveness index and to determine clusters of regions with similar tourism attractiveness profiles. We show how the results of these assessments can be visualized both in static maps and in a web mapping application.
{"title":"Assessment of Regional Attractiveness for Tourism","authors":"O. Čerba, Viktorie Sloupová, J. Macura, Sarah Velten","doi":"10.23919/IST-Africa56635.2022.9845524","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845524","url":null,"abstract":"Despite the severe impacts of the COVID-19 pandemic on the tourism industry, tourism has become a key sector for economic development in the African continent. Nevertheless, the tourism sector in Africa is still in its early stages and much of its touristic potential remains untapped. To harness this potential, rational and wise tourism planning and management are key. These need to be based on an assessment of the tourism attractiveness of the different territories. In this paper we introduce a method of assessing tourism attractiveness in Africa on a regional level and ways to present the results of such assessments in an easily interpretable way. For these purposes, we calculate a regional tourism attractiveness index and to determine clusters of regions with similar tourism attractiveness profiles. We show how the results of these assessments can be visualized both in static maps and in a web mapping application.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121002498","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845641
Keneilwe Maremi, Tumiso Thulare, M. Herselman
The objective of this paper is to provide insight into how the successful implementation of Digital Transformation (DT) can help address the challenges and hindrances in South Africa’s e-Government. It is essential to aid South Africa’s seamless transition to e-Government. A scoping review was conducted to identify how the benefits of digital transformation can be aligned with addressing the hindrances and challenges of e-Government services in South Africa. A study was also conducted at 12 prioritised South African government departments through expert interviews to identify hindrances in implementing e-Government services. The study found that the main hindrances to e-Government were the lack of governance between departments, the integration of legacy systems, insufficient funding for e-Government projects, and various systems and applications across government. The paper recommends that the government should consider factors hindering the implementation of e-Government from realising the benefits of DT.
{"title":"The Benefits of Digital Transformation addressing the Hindrances and Challenges of e-Government Services in South Africa: A Scoping Review","authors":"Keneilwe Maremi, Tumiso Thulare, M. Herselman","doi":"10.23919/IST-Africa56635.2022.9845641","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845641","url":null,"abstract":"The objective of this paper is to provide insight into how the successful implementation of Digital Transformation (DT) can help address the challenges and hindrances in South Africa’s e-Government. It is essential to aid South Africa’s seamless transition to e-Government. A scoping review was conducted to identify how the benefits of digital transformation can be aligned with addressing the hindrances and challenges of e-Government services in South Africa. A study was also conducted at 12 prioritised South African government departments through expert interviews to identify hindrances in implementing e-Government services. The study found that the main hindrances to e-Government were the lack of governance between departments, the integration of legacy systems, insufficient funding for e-Government projects, and various systems and applications across government. The paper recommends that the government should consider factors hindering the implementation of e-Government from realising the benefits of DT.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116001643","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845521
Nosipho Mthethwa, M. Masonta, Sifiso Dlamini, Lwando Ngcama
Broadband mapping is used in several countries to monitor and fast track broadband deployment to ensure internet connectivity for citizens. Literature review revealed that many European countries already have implemented broadband infrastructure mapping and broadband services mapping. Studies on broadband and infrastructure mapping shows that there are four different types of broadband mapping, namely: broadband infrastructure mapping, broadband service mapping, broadband demand mapping and broadband investment and funding mapping. In this paper, a framework for developing a broadband infrastructure mapping dashboard is proposed. More specifically, three broadband infrastructure mapping frameworks are being presented, which are: interoperability framework, readiness framework and usability framework. Based on these three frameworks, we go further to present an envisaged broadband infrastructure dashboard as a prototype. Broadband infrastructure mapping is critical in closing the internet access gap in the most cost-effective manner.
{"title":"Towards Developing a Broadband Infrastructure Dashboard Framework","authors":"Nosipho Mthethwa, M. Masonta, Sifiso Dlamini, Lwando Ngcama","doi":"10.23919/IST-Africa56635.2022.9845521","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845521","url":null,"abstract":"Broadband mapping is used in several countries to monitor and fast track broadband deployment to ensure internet connectivity for citizens. Literature review revealed that many European countries already have implemented broadband infrastructure mapping and broadband services mapping. Studies on broadband and infrastructure mapping shows that there are four different types of broadband mapping, namely: broadband infrastructure mapping, broadband service mapping, broadband demand mapping and broadband investment and funding mapping. In this paper, a framework for developing a broadband infrastructure mapping dashboard is proposed. More specifically, three broadband infrastructure mapping frameworks are being presented, which are: interoperability framework, readiness framework and usability framework. Based on these three frameworks, we go further to present an envisaged broadband infrastructure dashboard as a prototype. Broadband infrastructure mapping is critical in closing the internet access gap in the most cost-effective manner.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129351362","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 : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845532
Alice Nanyanzi, Chang Zhu, Justice Kintu Mugenyi, Ivo De Pauw, A. Mugenyi, Ilse Marien, L. Audenhove
Smartphone apps are promising tools for engagement between universities and external stakeholders like dairy farmers. However, there is limited evidence of dairy farmers’ intent to use apps. We use the Technology Acceptance Model to assess dairy farmers’ intent to use a co-created application. A survey of 100 farmers in the Kabarole district-Uganda was conducted, which focused on variables predicting farmers’ intention to use the app. Data were analysed using SPSS and Smart PLS 3 software. Findings show that hedonistic and utilitarian benefits drive farmers’ perceived ease of use and perceived usefulness of the app. Also, the intent to use the app is driven by both types of attitudes. Furthermore, self-belief affects the perceived usefulness but was insignificant on intent to use the app. The findings contribute to practical knowledge of the factors predicting the intent to use digital tools. Future research should focus on the actual usage of the app.
{"title":"Intent to Use a Smartphone App as a University-Engagement Tool by Kabarole Farmers in Uganda","authors":"Alice Nanyanzi, Chang Zhu, Justice Kintu Mugenyi, Ivo De Pauw, A. Mugenyi, Ilse Marien, L. Audenhove","doi":"10.23919/IST-Africa56635.2022.9845532","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845532","url":null,"abstract":"Smartphone apps are promising tools for engagement between universities and external stakeholders like dairy farmers. However, there is limited evidence of dairy farmers’ intent to use apps. We use the Technology Acceptance Model to assess dairy farmers’ intent to use a co-created application. A survey of 100 farmers in the Kabarole district-Uganda was conducted, which focused on variables predicting farmers’ intention to use the app. Data were analysed using SPSS and Smart PLS 3 software. Findings show that hedonistic and utilitarian benefits drive farmers’ perceived ease of use and perceived usefulness of the app. Also, the intent to use the app is driven by both types of attitudes. Furthermore, self-belief affects the perceived usefulness but was insignificant on intent to use the app. The findings contribute to practical knowledge of the factors predicting the intent to use digital tools. Future research should focus on the actual usage of the app.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130584313","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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