Pub Date : 2022-05-16DOI: 10.23919/IST-Africa56635.2022.9845662
Folashikemi Maryam Asani Olaniyan, A. Owoseni
The study examined the data quality efficiency of the WHO Data Quality Review (DQR) toolkit and PyCaret anomaly detection algorithms. The tools were applied to the African HIV/AIDS data (2015-2021) extracted from a public data repository (data.pepfar.gov). The research outcome suggests that unsupervised anomaly detection algorithms could complement the efficiency of the WHO DQR toolkit and improve Data Quality Assessment (DQA). In particular, the study showed that anomaly detection algorithms through python programming provide a more straightforward and more reliable process for detecting data inconsistencies, incompleteness, and timeliness appears more accurate than the WHO tool. Consequently, the study contributed to ongoing debates on improving health data quality in low-income African countries.
{"title":"Toward Improved Data Quality in Public Health: Analysis of Anomaly Detection Tools applied to HIV/AIDS Data in Africa","authors":"Folashikemi Maryam Asani Olaniyan, A. Owoseni","doi":"10.23919/IST-Africa56635.2022.9845662","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845662","url":null,"abstract":"The study examined the data quality efficiency of the WHO Data Quality Review (DQR) toolkit and PyCaret anomaly detection algorithms. The tools were applied to the African HIV/AIDS data (2015-2021) extracted from a public data repository (data.pepfar.gov). The research outcome suggests that unsupervised anomaly detection algorithms could complement the efficiency of the WHO DQR toolkit and improve Data Quality Assessment (DQA). In particular, the study showed that anomaly detection algorithms through python programming provide a more straightforward and more reliable process for detecting data inconsistencies, incompleteness, and timeliness appears more accurate than the WHO tool. Consequently, the study contributed to ongoing debates on improving health data quality in low-income African countries.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"130 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":"123223134","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-Africa56635.2022.9845528
Jafer Hassan Abdikadir, Amen Tamene Gemeda, S. Mwongela
Since the dawn of COVID-19, everything has changed drastically. From education to business, all sectors of peoples’ lives have been affected. An arising issue from the current situation is the tracking and managing of COVID-19 related data. With the resumption of educational institutions in Kenya, adherence to protocols provided by the ministry of education is paramount. One of the guidelines provided for the resumption of schools is thermal monitoring/screening of people, which has been implemented differently across the country. Some universities have opted for checking students’ temperatures and not keeping a record of this information. Others require students to go through a check-up to give their details, and their temperature is recorded. The flaw with this system is inadequate record-keeping as the records are manual, which leads to a hectic analysis. The research aimed to find a solution to better manage and analyse COVID-19 data. The solution was implemented using IoT technology and AI, where a camera and a temperature sensor was used to record the temperature and identify the students. The research methods applied were experimental and a case study of Kenyan universities. A progressive web application is used to interact with the system. The solution was able to improve on data management and analysis, among other benefits.
{"title":"An IoT Based Web Application for Tracking and Managing Covid-19 Related Data. A Case of Kenyan Learning Institutions","authors":"Jafer Hassan Abdikadir, Amen Tamene Gemeda, S. Mwongela","doi":"10.23919/IST-Africa56635.2022.9845528","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845528","url":null,"abstract":"Since the dawn of COVID-19, everything has changed drastically. From education to business, all sectors of peoples’ lives have been affected. An arising issue from the current situation is the tracking and managing of COVID-19 related data. With the resumption of educational institutions in Kenya, adherence to protocols provided by the ministry of education is paramount. One of the guidelines provided for the resumption of schools is thermal monitoring/screening of people, which has been implemented differently across the country. Some universities have opted for checking students’ temperatures and not keeping a record of this information. Others require students to go through a check-up to give their details, and their temperature is recorded. The flaw with this system is inadequate record-keeping as the records are manual, which leads to a hectic analysis. The research aimed to find a solution to better manage and analyse COVID-19 data. The solution was implemented using IoT technology and AI, where a camera and a temperature sensor was used to record the temperature and identify the students. The research methods applied were experimental and a case study of Kenyan universities. A progressive web application is used to interact with the system. The solution was able to improve on data management and analysis, among other benefits.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"36 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":"131929399","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-Africa56635.2022.9845517
Nesisa Moyo, Sibonile Moyo, Belinda Mutunhu
The COVID-19 pandemic has been a challenge for the past two years, and continues to be so, with the virus showing more mutations with time. The use of face masks in public spaces has been proven to be a precautionary measure to minimize the spread of the Coronavirus, which is the causative agent of the disease. However, enforcing the proper wearing of masks, particularly in environments like schools is a daunting task. This study develops a live video camera application that detects proper wearing of face masks by students in schools using a machine learning algorithm. On detecting an improper mask-wearing face, or a face with no mask, the system displays a red message “No Mask”, while a face with a mask properly worn is flagged with a green message “Mask”. To enforce the proper wearing of masks, on detecting persons improperly wearing masks, the system automatically sends an alert WhatsApp message to the classroom manager (teacher) to take appropriate action. This application would help ease the workload of teachers who have the task of ensuring a quality teaching and learning environment, at the same time safeguarding the health of learners in this COVID-19 era.
{"title":"Mask-Up: A Face Mask Alert App Using Machine Learning","authors":"Nesisa Moyo, Sibonile Moyo, Belinda Mutunhu","doi":"10.23919/IST-Africa56635.2022.9845517","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845517","url":null,"abstract":"The COVID-19 pandemic has been a challenge for the past two years, and continues to be so, with the virus showing more mutations with time. The use of face masks in public spaces has been proven to be a precautionary measure to minimize the spread of the Coronavirus, which is the causative agent of the disease. However, enforcing the proper wearing of masks, particularly in environments like schools is a daunting task. This study develops a live video camera application that detects proper wearing of face masks by students in schools using a machine learning algorithm. On detecting an improper mask-wearing face, or a face with no mask, the system displays a red message “No Mask”, while a face with a mask properly worn is flagged with a green message “Mask”. To enforce the proper wearing of masks, on detecting persons improperly wearing masks, the system automatically sends an alert WhatsApp message to the classroom manager (teacher) to take appropriate action. This application would help ease the workload of teachers who have the task of ensuring a quality teaching and learning environment, at the same time safeguarding the health of learners in this COVID-19 era.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"112 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120933106","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-Africa56635.2022.9845534
Misheck Banda, E. Ngassam, Ernest Mnkandla
Artificial intelligence and its related machine learning technologies constantly change how organisations manage their business data in a dynamic environment of ubiquitous data sources and formats. Most organisations face the challenge of selecting the appropriate machine learning models to extract insights from their existing business data, of which datasets may be unstructured, of different forms, types, and sizes. Logistic regression, random forest, and decision tree were the three machine learning models selected for this paper’s preliminary experiments to predict the likelihood of passengers surviving the Titanic disaster. Our investigation revealed that specific models are required to handle specific dataset types, in this case, categorical datasets. It was noted from the findings that a logistic regression model could be highly recommended for use on a categorical dataset based on the speed and high prediction performance obtained in the classification error metrics and confusion matrix. The selected models form part of a set of models currently being explored in the construction of hybrid machine learning models beyond the scope of this paper.
{"title":"Preliminary Experiments on the Performance of Machine Learning Models","authors":"Misheck Banda, E. Ngassam, Ernest Mnkandla","doi":"10.23919/IST-Africa56635.2022.9845534","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845534","url":null,"abstract":"Artificial intelligence and its related machine learning technologies constantly change how organisations manage their business data in a dynamic environment of ubiquitous data sources and formats. Most organisations face the challenge of selecting the appropriate machine learning models to extract insights from their existing business data, of which datasets may be unstructured, of different forms, types, and sizes. Logistic regression, random forest, and decision tree were the three machine learning models selected for this paper’s preliminary experiments to predict the likelihood of passengers surviving the Titanic disaster. Our investigation revealed that specific models are required to handle specific dataset types, in this case, categorical datasets. It was noted from the findings that a logistic regression model could be highly recommended for use on a categorical dataset based on the speed and high prediction performance obtained in the classification error metrics and confusion matrix. The selected models form part of a set of models currently being explored in the construction of hybrid machine learning models beyond the scope of this paper.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"52 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":"130921072","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-Africa56635.2022.9845590
A. Omambia, B. Maake, Anthony Wambua Wambua
Safe water access is fundamental form of human survival and it is presented as a fundamental human right. As consumers use water, primarily sourced from pipes and springs located around towns, contamination, leakages, and pilferage happen. IoT and Machine Learning offer a promising solution to address these challenges. Premised on these technologies, the authors propose a system that monitors water quality and pilferage and wastage that uses machine learning algorithms for decision making.
{"title":"Water Quality Monitoring Using IoT & Machine Learning","authors":"A. Omambia, B. Maake, Anthony Wambua Wambua","doi":"10.23919/IST-Africa56635.2022.9845590","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845590","url":null,"abstract":"Safe water access is fundamental form of human survival and it is presented as a fundamental human right. As consumers use water, primarily sourced from pipes and springs located around towns, contamination, leakages, and pilferage happen. IoT and Machine Learning offer a promising solution to address these challenges. Premised on these technologies, the authors propose a system that monitors water quality and pilferage and wastage that uses machine learning algorithms for decision making.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"8 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":"132321240","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-Africa56635.2022.9845599
A. Periola, A. Alonge, K. Ogudo
Crop production is an important task for ensuring food security. Hence, it is important to ensure a high global food production. However, flooding impairs crop production to achieve food security. The occurrence of large scale flooding causes the loss of a significant number of crops. This challenge arises due to the reliance of agriculture on terrestrial land resources. A solution that reduces the reliance of agriculture on terrestrial resources is proposed and presented. The proposed solution incorporates the multi-location plant paradigm alongside logical plant units (LPUs). LPUs can change their locations and return to the initial terrestrial position after the receding of a flood event. This enables crop production of food in areas with high flooding susceptibility. Previously, crop production in such areas was deemed infeasible. An LPU can be hosted in aerial, ocean-surface or terrestrial environment. The proposed solution reduces the number of lost crops by an average of (9.6-33) % in a two-farm scenario. The results of analysis shows that the use of LPUs incorporating dynamic location plants can limit crop loss due to flooding.
{"title":"Intelligent and Flood Resilient Agriculture","authors":"A. Periola, A. Alonge, K. Ogudo","doi":"10.23919/IST-Africa56635.2022.9845599","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845599","url":null,"abstract":"Crop production is an important task for ensuring food security. Hence, it is important to ensure a high global food production. However, flooding impairs crop production to achieve food security. The occurrence of large scale flooding causes the loss of a significant number of crops. This challenge arises due to the reliance of agriculture on terrestrial land resources. A solution that reduces the reliance of agriculture on terrestrial resources is proposed and presented. The proposed solution incorporates the multi-location plant paradigm alongside logical plant units (LPUs). LPUs can change their locations and return to the initial terrestrial position after the receding of a flood event. This enables crop production of food in areas with high flooding susceptibility. Previously, crop production in such areas was deemed infeasible. An LPU can be hosted in aerial, ocean-surface or terrestrial environment. The proposed solution reduces the number of lost crops by an average of (9.6-33) % in a two-farm scenario. The results of analysis shows that the use of LPUs incorporating dynamic location plants can limit crop loss due to flooding.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"26 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":"126073141","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-Africa56635.2022.9845670
J. Osakwe, Iyaloo N. Waiganjo, Terhemen Tarzoor, G. Iyawa, M. Ujakpa
Resource-based view is the theory that has been applied to analyse the impact of Information Systems resources on business performance. Its main argument is that competitive advantages are determined by the unique valuable resources controlled by an organisation. It also analyses Information Systems (IS) as a valuable asset, which are firm-specific resources that will have positive effect on firm performance. This paper x-rays the tangible and intangible Information Systems resources with a view to pointing out the key Information Systems resources that are determinants of organisational competitive advantage.
{"title":"Determinants of Information Systems Resources for Business Organisations’ Competitive Advantage: A Resource-Based View Approach","authors":"J. Osakwe, Iyaloo N. Waiganjo, Terhemen Tarzoor, G. Iyawa, M. Ujakpa","doi":"10.23919/IST-Africa56635.2022.9845670","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845670","url":null,"abstract":"Resource-based view is the theory that has been applied to analyse the impact of Information Systems resources on business performance. Its main argument is that competitive advantages are determined by the unique valuable resources controlled by an organisation. It also analyses Information Systems (IS) as a valuable asset, which are firm-specific resources that will have positive effect on firm performance. This paper x-rays the tangible and intangible Information Systems resources with a view to pointing out the key Information Systems resources that are determinants of organisational competitive advantage.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"2014 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":"127463935","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-Africa56635.2022.9845654
Alex Mongi
Video streaming applications have grown tremendously in recent years due to the technological advancement of wireless networks and smart devices. Unlike voice content, videos possess strict network performance demands to deliver a quality view. The Quality of Experience (QoE) refers to the level of users’ satisfaction with the delivered service and is one of the important aspects of managing wireless networks. Normally, wireless networks inherently exhibit various impairments such as packet loss, delay, and jitter. Therefore, understanding QoE on services delivered through the wireless networks is a basic requirement for the quality management process. Hence, this study adopts the Taguchi design of experiments to investigate the simultaneous impacts of network impairments on video streaming QoE. Experiments were conducted in a laboratory using a wireless network testbed. Different network conditions were emulated and real people assessed their impacts on videos streamed using smart devices. This study found that delay and jitter significantly affected video streaming QoE at $mathrm{p}lt 0.05$. Moreover, the effects of packet loss were not significant but exhibited outstanding interaction effects with jitter on video streaming QoE, which must be considered for effective network management practices.
近年来，由于无线网络和智能设备的技术进步，视频流应用得到了极大的发展。与语音内容不同，视频对网络性能有严格的要求，以提供高质量的观看效果。体验质量(Quality of Experience, QoE)是指用户对所提供服务的满意程度，是无线网络管理的一个重要方面。通常，无线网络固有地表现出各种损害，如数据包丢失、延迟和抖动。因此，了解通过无线网络交付的服务的QoE是质量管理过程的基本要求。因此，本研究采用田口实验设计来研究网络损伤对视频流QoE的同时影响。实验在实验室使用无线网络试验台进行。模拟不同的网络条件，真人评估它们对使用智能设备的视频流的影响。本研究发现延迟和抖动显著影响视频流QoE在$ mathm {p}lt 0.05$。此外，丢包对视频流QoE的影响并不显著，但与抖动的交互作用突出，这是有效的网络管理实践必须考虑的问题。
{"title":"Perceptual Impacts of Wireless Network Impairments on Video Streaming QoE using Taguchi Approach","authors":"Alex Mongi","doi":"10.23919/IST-Africa56635.2022.9845654","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845654","url":null,"abstract":"Video streaming applications have grown tremendously in recent years due to the technological advancement of wireless networks and smart devices. Unlike voice content, videos possess strict network performance demands to deliver a quality view. The Quality of Experience (QoE) refers to the level of users’ satisfaction with the delivered service and is one of the important aspects of managing wireless networks. Normally, wireless networks inherently exhibit various impairments such as packet loss, delay, and jitter. Therefore, understanding QoE on services delivered through the wireless networks is a basic requirement for the quality management process. Hence, this study adopts the Taguchi design of experiments to investigate the simultaneous impacts of network impairments on video streaming QoE. Experiments were conducted in a laboratory using a wireless network testbed. Different network conditions were emulated and real people assessed their impacts on videos streamed using smart devices. This study found that delay and jitter significantly affected video streaming QoE at $mathrm{p}lt 0.05$. Moreover, the effects of packet loss were not significant but exhibited outstanding interaction effects with jitter on video streaming QoE, which must be considered for effective network management practices.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"34 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":"126329658","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-Africa56635.2022.9845511
M. Thiga, Pamela C. Kimeto, Mvurya Mgala, E. Kweyu, Steve Wanyee, Tooroti Mwirigi
Pre-enclampsia, a condition evidenced by persistent high blood pressure during pregnancy, can lead to the loss of both the mother and child, and often times persists beyond the delivery of the baby. Its early detection through regular blood pressure measurements can inform timely and life saving interventions for both the mother and baby. This study developed a system for remote blood pressure data collection and monitoring incorporating (i) a smartwatch with Photolethysmography (PPG) and Electrocardiogram (ECG) sensors, (ii) a mobile application for receiving the readings through bluetooth and (iii) a mobile application for use by caregivers, namely; ante natal clinic nurses, community health extension workers, community health workers and next of kin, to monitor the blood pressure readings for mothers assigned to them. The system demonstrates significant potential in the early detection of pre-eclampsia, which will in turn inform timely interventions to prevent fatal complications for both mother and baby.
{"title":"A Remote Blood Pressure Data Collection and Monitoring System for Expectant Mothers","authors":"M. Thiga, Pamela C. Kimeto, Mvurya Mgala, E. Kweyu, Steve Wanyee, Tooroti Mwirigi","doi":"10.23919/IST-Africa56635.2022.9845511","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845511","url":null,"abstract":"Pre-enclampsia, a condition evidenced by persistent high blood pressure during pregnancy, can lead to the loss of both the mother and child, and often times persists beyond the delivery of the baby. Its early detection through regular blood pressure measurements can inform timely and life saving interventions for both the mother and baby. This study developed a system for remote blood pressure data collection and monitoring incorporating (i) a smartwatch with Photolethysmography (PPG) and Electrocardiogram (ECG) sensors, (ii) a mobile application for receiving the readings through bluetooth and (iii) a mobile application for use by caregivers, namely; ante natal clinic nurses, community health extension workers, community health workers and next of kin, to monitor the blood pressure readings for mothers assigned to them. The system demonstrates significant potential in the early detection of pre-eclampsia, which will in turn inform timely interventions to prevent fatal complications for both mother and baby.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"556 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120932938","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-Africa56635.2022.9845540
F. Uzoka, Mugisha Gift, K. Attai, B. Akinnuwesi, S. Mlay, P. Zeh, Arnold Kiirya, C. Muhumuza, J. Bukenya, S. Fashoto, Daniel Asuquo, C. Akwaowo, O. K. Akputu, Mercy E. Edoho, Ifiok J. Udo, Lucy Amaniyo, A. Metfula, Gorretti Kyeyune
In middle- and low-income countries where higher nosocomial infection rates have been reported, approximately 5% to 10% of hospitalized patients have some infection acquired after admission. Recent studies suggest that contaminated environmental surfaces may play a major role in the transmission of nosocomial infections. Therefore, this study presents an e-Medical Assistant Tool (Vitex), which is a mobile device that disinfects wards of 100 square feet in a single cycle which can be increased since the device is mobile by using powerful U.V rays of 222nm that can be used in occupied rooms without adverse effects on human health. It also employs artificial intelligence, big data, and machine learning to improve patient care and practitioner assistance. Unlike existing similar devices, our innovation disinfects the ward, and facilitates healthcare provision via remote patient consultation and diagnosis; thus, bringing care nearer to the patient.
{"title":"Tackling Occupational and Nosocomial Infection using Vitex-Medical Assistant Tool","authors":"F. Uzoka, Mugisha Gift, K. Attai, B. Akinnuwesi, S. Mlay, P. Zeh, Arnold Kiirya, C. Muhumuza, J. Bukenya, S. Fashoto, Daniel Asuquo, C. Akwaowo, O. K. Akputu, Mercy E. Edoho, Ifiok J. Udo, Lucy Amaniyo, A. Metfula, Gorretti Kyeyune","doi":"10.23919/IST-Africa56635.2022.9845540","DOIUrl":"https://doi.org/10.23919/IST-Africa56635.2022.9845540","url":null,"abstract":"In middle- and low-income countries where higher nosocomial infection rates have been reported, approximately 5% to 10% of hospitalized patients have some infection acquired after admission. Recent studies suggest that contaminated environmental surfaces may play a major role in the transmission of nosocomial infections. Therefore, this study presents an e-Medical Assistant Tool (Vitex), which is a mobile device that disinfects wards of 100 square feet in a single cycle which can be increased since the device is mobile by using powerful U.V rays of 222nm that can be used in occupied rooms without adverse effects on human health. It also employs artificial intelligence, big data, and machine learning to improve patient care and practitioner assistance. Unlike existing similar devices, our innovation disinfects the ward, and facilitates healthcare provision via remote patient consultation and diagnosis; thus, bringing care nearer to the patient.","PeriodicalId":142887,"journal":{"name":"2022 IST-Africa Conference (IST-Africa)","volume":"417 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":"117318367","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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