A mobile based control system for smart homes
- Authors: Tshimanga, Danny Kazadi
- Date: 2022-03
- Subjects: Smart power grids , Home automation
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22632 , vital:52606
- Description: A Smart Home Control System can provide a secure home, convenience, comfort, and interactivity of life in a particular home. The system can enable the automatic controlling of a house via a Smart Phone. These systems are becoming vital and widely used in homes to improve conditions of life. Most commercial home automation systems are expensive and their maintenance would require experts who understand the underlying implementation of the systems. This study developed a mobile-based home automation system prototype. The system was developed using the waterfall model methodology. To evaluate the developed system, the study used a simulation method. Ten trials were conducted to determine the performance of the implemented system. The mean time to failure was used to evaluate the system’ reliability. The system’s performance analysis revealed that the developed system performed better than the two other approaches; the Bluetooth and ZigBee. The developed system showed a 0 percent error, while the Bluetooth had 8 percent error and ZigBee 6 percent error. The reliability results showed the average lifespan of assets in the system before they could fail. Knowing the lifespan of an asset before it fails can help in reducing downtime of the system by planning or scheduling maintenance and develop an improved maintenance strategy. , Thesis (MSc) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2022-03
- Authors: Tshimanga, Danny Kazadi
- Date: 2022-03
- Subjects: Smart power grids , Home automation
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22632 , vital:52606
- Description: A Smart Home Control System can provide a secure home, convenience, comfort, and interactivity of life in a particular home. The system can enable the automatic controlling of a house via a Smart Phone. These systems are becoming vital and widely used in homes to improve conditions of life. Most commercial home automation systems are expensive and their maintenance would require experts who understand the underlying implementation of the systems. This study developed a mobile-based home automation system prototype. The system was developed using the waterfall model methodology. To evaluate the developed system, the study used a simulation method. Ten trials were conducted to determine the performance of the implemented system. The mean time to failure was used to evaluate the system’ reliability. The system’s performance analysis revealed that the developed system performed better than the two other approaches; the Bluetooth and ZigBee. The developed system showed a 0 percent error, while the Bluetooth had 8 percent error and ZigBee 6 percent error. The reliability results showed the average lifespan of assets in the system before they could fail. Knowing the lifespan of an asset before it fails can help in reducing downtime of the system by planning or scheduling maintenance and develop an improved maintenance strategy. , Thesis (MSc) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2022-03
Modelling internet network intrusion detection in smart city ecosystems
- Authors: Mfenguza, Wandisa
- Date: 2021-05
- Subjects: Ecosystem management , Smart cities
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22501 , vital:52382
- Description: Smart city systems are intended to enhance the lives of citizens through the design of systems that promote resource efficiency and the real-time provisioning of resources in cities. The benefits offered by smart cities include the use of internet of things (IoT) sensors to gather useful data such as power demand to inhibit blackouts and the average speed of vehicles to alleviate traffic congestion. Nonetheless, earlier studies have indicated a substantial increase in cyber-security issues due to the increase in the deployment of smart city ecosystems. Consequently, IoT cyber-security is recognised as an area that requires crucial scrutiny. This study begins by investigating the current state of intrusion detection in smart city ecosystems. Current intrusion detection frameworks lack the capability to operate under extremely limiting settings such as conditions of low processing power and fast response times. Moreover, the study also identifies that, despite intrusion detection being a highly researched thematic area, a plethora of previous studies tend to propose intrusion detection frameworks that are more suitable for traditional computer networks rather than wireless sensor networks (WSNs) which consist of heterogeneous settings with diverse devices and communication protocols. Subsequently, this study developed two candidate deep learning models, namely a convolutional neural network (CNN) and a long short-term memory (LSTM) network and presents evidence on their robustness and predictive power. Results have indicated that, unlike the CNN model, the LSTM model can quickly converge and offer high predictive power without the vigorous application of regularisation techniques. The proposed LSTM classification model obtained a remarkable 100% in detection rates and further reported 0% in false alarm and false negative rates. This study gives a broad overview of the current state of intrusion detection mechanisms for smart city ecosystems to guide future studies. The study also demonstrates that existing intrusion detection systems (IDSs) can be enhanced through the development of more robust and lightweight models that offer high detection rates and minimal false alarm rates to prevent security risks in smart city ecosystems to ensure sustainable and safe smart cities. , Thesis (MSc) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2021-05
- Authors: Mfenguza, Wandisa
- Date: 2021-05
- Subjects: Ecosystem management , Smart cities
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/22501 , vital:52382
- Description: Smart city systems are intended to enhance the lives of citizens through the design of systems that promote resource efficiency and the real-time provisioning of resources in cities. The benefits offered by smart cities include the use of internet of things (IoT) sensors to gather useful data such as power demand to inhibit blackouts and the average speed of vehicles to alleviate traffic congestion. Nonetheless, earlier studies have indicated a substantial increase in cyber-security issues due to the increase in the deployment of smart city ecosystems. Consequently, IoT cyber-security is recognised as an area that requires crucial scrutiny. This study begins by investigating the current state of intrusion detection in smart city ecosystems. Current intrusion detection frameworks lack the capability to operate under extremely limiting settings such as conditions of low processing power and fast response times. Moreover, the study also identifies that, despite intrusion detection being a highly researched thematic area, a plethora of previous studies tend to propose intrusion detection frameworks that are more suitable for traditional computer networks rather than wireless sensor networks (WSNs) which consist of heterogeneous settings with diverse devices and communication protocols. Subsequently, this study developed two candidate deep learning models, namely a convolutional neural network (CNN) and a long short-term memory (LSTM) network and presents evidence on their robustness and predictive power. Results have indicated that, unlike the CNN model, the LSTM model can quickly converge and offer high predictive power without the vigorous application of regularisation techniques. The proposed LSTM classification model obtained a remarkable 100% in detection rates and further reported 0% in false alarm and false negative rates. This study gives a broad overview of the current state of intrusion detection mechanisms for smart city ecosystems to guide future studies. The study also demonstrates that existing intrusion detection systems (IDSs) can be enhanced through the development of more robust and lightweight models that offer high detection rates and minimal false alarm rates to prevent security risks in smart city ecosystems to ensure sustainable and safe smart cities. , Thesis (MSc) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2021-05
An analysis of technical efficiency and service effectiveness for freight railways in African and European countries
- Mfiyo, Azania https://orcid.org/0000-0002-0967-9756
- Authors: Mfiyo, Azania https://orcid.org/0000-0002-0967-9756
- Date: 2021-03
- Subjects: Freight and freightage , Railroads -- Freight
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/20186 , vital:45406
- Description: For the past decades, technical efficiency and service effectiveness have become topical as performance measures in various sectors. However, a comparison of technical efficiency and service effectiveness for freight rail transport has received less attention in African and European countries. To address this challenge the current study seeks to analyse technical efficiency and service effectiveness of rail freight in African and European countries. Due to data unavailability in other countries, this study selected four African countries (South Africa, Morocco, Democratic Republic of Congo and Algeria) and four European countries (Lithuania, Austria, France and Germany). The data has been collected from the World Bank, International Union of Railway Statistics and Knoema for the period 2017. Input oriented and output oriented data envelope analysis (DEA) were used to analyze technical efficiency and service effectiveness, respectively. The application of DEA requires the selection of appropriate inputs, production and output variables. This study selected a number of employees and length of rail lines as input variables, gross train tonne kilometres (km) as production variable, tonnes carried and tonne kilometres (km) as output variables. The result shows that five out of eight countries were technical efficient and their services effective with values equal to 1.00. The Pearson correlation coefficient was used to analyse the relationship between technical efficiency and service effectiveness. The results indicate that there is a statistically significant positive correlation between technical efficiency and service effectiveness. To determine the impact exogenous variables on technical efficiency and service effectiveness, a Tobit regression analysis was conducted. The results show that technical efficiency and service effectiveness are not significantly affected by exogenous variables. On the other hand, technical efficiency is significantly affected by the number of employees while service effectiveness is significantly affected by gross train tonne km. This study recommends the use of less labour intensive assets and monitoring of gross train tonne km should be viewed as important strategies to improve technical efficiency and service effectiveness, respectively. , Thesis (MCom) -- Faculty of Management and Commerce, 2021
- Full Text:
- Date Issued: 2021-03
- Authors: Mfiyo, Azania https://orcid.org/0000-0002-0967-9756
- Date: 2021-03
- Subjects: Freight and freightage , Railroads -- Freight
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/20186 , vital:45406
- Description: For the past decades, technical efficiency and service effectiveness have become topical as performance measures in various sectors. However, a comparison of technical efficiency and service effectiveness for freight rail transport has received less attention in African and European countries. To address this challenge the current study seeks to analyse technical efficiency and service effectiveness of rail freight in African and European countries. Due to data unavailability in other countries, this study selected four African countries (South Africa, Morocco, Democratic Republic of Congo and Algeria) and four European countries (Lithuania, Austria, France and Germany). The data has been collected from the World Bank, International Union of Railway Statistics and Knoema for the period 2017. Input oriented and output oriented data envelope analysis (DEA) were used to analyze technical efficiency and service effectiveness, respectively. The application of DEA requires the selection of appropriate inputs, production and output variables. This study selected a number of employees and length of rail lines as input variables, gross train tonne kilometres (km) as production variable, tonnes carried and tonne kilometres (km) as output variables. The result shows that five out of eight countries were technical efficient and their services effective with values equal to 1.00. The Pearson correlation coefficient was used to analyse the relationship between technical efficiency and service effectiveness. The results indicate that there is a statistically significant positive correlation between technical efficiency and service effectiveness. To determine the impact exogenous variables on technical efficiency and service effectiveness, a Tobit regression analysis was conducted. The results show that technical efficiency and service effectiveness are not significantly affected by exogenous variables. On the other hand, technical efficiency is significantly affected by the number of employees while service effectiveness is significantly affected by gross train tonne km. This study recommends the use of less labour intensive assets and monitoring of gross train tonne km should be viewed as important strategies to improve technical efficiency and service effectiveness, respectively. , Thesis (MCom) -- Faculty of Management and Commerce, 2021
- Full Text:
- Date Issued: 2021-03
The relationship between financial development and economic growth in Eswatini (formerly Swaziland)
- Fakudze, Siphe-okuhlehttps://orcid.org/0000-0001-7928-5552
- Authors: Fakudze, Siphe-okuhlehttps://orcid.org/0000-0001-7928-5552
- Date: 2019-12
- Subjects: Economic development -- Eswatini , Eswatini -- Economic conditions
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/19704 , vital:43170
- Description: The study empirically examined the relationship between financial development and economic growth in Eswatini using quarterly time series data covering the period 1996 to 2018. Auto Regressive Distributed Lag bounds test technique and Granger causality test were used. The ratio of credit to the private sector to economic growth, openness to trade, revealed a positive relationship with economic growth in the long-run and short-run dynamics. Money supply displayed a negative association with real output in the long-run and short-run. Government size as a ratio of GDP highlighted a negative linkage with economic growth in the long-run and temporary positive association in the short-run. The Granger Causality test results displayed unidirectional causality running from financial development to economic growth, supporting the demand following causality hypothesis in Eswatini. The study recommends developing policies aimed at enhancing credit to the private sector to stimulate investment; reprioritise Government expenditure to minimise fiscal gap and support supply side reforms focusing on infrastructure development; control domestic liquidity and develop market securities attractive to the private sector; strengthen trade intensity to bolster growth; and improve regulatory framework to develop the non-bank financial industry. , Thesis (MCom) -- Faculty of Management and Commerce, 2019
- Full Text:
- Date Issued: 2019-12
- Authors: Fakudze, Siphe-okuhlehttps://orcid.org/0000-0001-7928-5552
- Date: 2019-12
- Subjects: Economic development -- Eswatini , Eswatini -- Economic conditions
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/19704 , vital:43170
- Description: The study empirically examined the relationship between financial development and economic growth in Eswatini using quarterly time series data covering the period 1996 to 2018. Auto Regressive Distributed Lag bounds test technique and Granger causality test were used. The ratio of credit to the private sector to economic growth, openness to trade, revealed a positive relationship with economic growth in the long-run and short-run dynamics. Money supply displayed a negative association with real output in the long-run and short-run. Government size as a ratio of GDP highlighted a negative linkage with economic growth in the long-run and temporary positive association in the short-run. The Granger Causality test results displayed unidirectional causality running from financial development to economic growth, supporting the demand following causality hypothesis in Eswatini. The study recommends developing policies aimed at enhancing credit to the private sector to stimulate investment; reprioritise Government expenditure to minimise fiscal gap and support supply side reforms focusing on infrastructure development; control domestic liquidity and develop market securities attractive to the private sector; strengthen trade intensity to bolster growth; and improve regulatory framework to develop the non-bank financial industry. , Thesis (MCom) -- Faculty of Management and Commerce, 2019
- Full Text:
- Date Issued: 2019-12
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