Masters Degrees (Electrical and Electronic Engineering)
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Browsing Masters Degrees (Electrical and Electronic Engineering) by browse.metadata.advisor "Booysen, M. J."
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- ItemAutomated mobile water leakage assessment system(2016-12) Erwee, Jurie Johannes; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Despite humanity’s absolute reliance on the increasingly scarce resource of potable water, 25.4% of South Africa’s water is lost due to leaks in the distribution network before it reaches the consumer. This figure is even worse in many developing countries. Because developing countries generally have a lack of technical skills, active leakage management techniques are not implemented, resulting in a large number of leaks being undetected. Current leak detection and assessment solutions are not well suited to the conditions of developing countries, due to the substantial cost thereof and the lacking practitioner skills. The work presented in this thesis describes the development of a mobile platform that automatically assesses a section of the Water Distribution System (WDS) to identify and characterise leaks, and transmits the data to an online platform for storage and further analysis. The approach taken is to measure the resulting flow rates at discrete pressure levels that the proposed system applies to the assessed section of the WDS. According to the Fixed And Variable Area Discharge (FAVAD) equation, this relationship can be used to give an indication of the size and type of apparent leaks, since round holes, longitudinal cracks, and circumferential cracks behave differently. The proposed mobile platform connects via a fire hydrant to a section of the WDS, which is isolated by shutting its mains and service valves, and executes the test at a push of a button, making it suitable for low-skilled operators. Once the test is completed, the results are transmitted to an online platform, where it can be analysed further and viewed by a water distributor or expert. The thesis presents the design and test procedures of control circuitry and software that are developed specifically with mobility and automation in mind. The consistency and accuracy of the system’s results are experimentally tested on three different leak types and three different pipe materials, namely polyvinyl chloride, high density polyethylene, and polypropylene, since these pipes are commonly used on municipal WDSs. The flow rate for the round holes were found to be more consistent than the flow rate of the longitudinal cracks. The results also showed that leakages are easily effected by small imperfections caused by leak manufacturing. The tests verified the system’s ability to detect and characterise the leaks in terms of the FAVAD equation with detected results corresponding to theoretically predicted values. The research objective of developing an automated mobile platform that assess leaks and transmit the results to an online analysis platform, was achieved. If the solution is deployed, it will enable water distributors to implement active leakage control and prioritise refurbishment projects.
- ItemDemanding change in a constrained environment: water usage in schools(Stellenbosch : Stellenbosch University, 2019-12) Ripunda, Cheroline; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Water shortages are currently a global challenge. The scarcity of water sources is particularly evident in developing countries because of over population and high rates of urbanisation. The challenge is further worsened by the constraints on financial resources in these countries. For example, schools in the Western Cape experienced increased financial losses due water shortages brought on by the drought that hit the province between 2016 to 2018. As such, this research study proposed water demand solutions that use realtime data to understand and manage school water demand. This was done by using historical water data to understand and classify school water use. The effects of socio-economic and political variables on school water demand were then analysed. Thereafter, in an effort to reduce school water demand, two methods were employed to measure the impact of interventions that evaluated school-time and night-time water usage. The first was the MNF method, used to measure water losses. The other, was a RCT, which was used to quantify the reductions in water usage after employing two behavioural interventions, a Information Only and a Social Norm. The results of this research study highlighted several important aspects. The first being the importance of maintenance in managing school water demand. Consequently, effective "quick-fixes" resulted in drastic water usage reductions for several of the participating schools. Secondly, the results revealed that the current governmental funding policies are outdated and hence these policies need to be constantly updated in order to ensure that they influence water demand positively. The RCT results demonstrated that behavioural interventions are valuable in encouraging reduced water usage. Further, the Information Only intervention showed that self-monitoring is important for improving the overall management and maintenance of school water systems. While, the Social Norm intervention helped schools adopt water conservation cultures and was more effective in reducing school water usage during school hours. Overall, this study shed light on a topic that is often neglected, particularly in developing countries.
- ItemDesign and assessment of an energy efficient office building utilising a building management system. A study of a use case in Cape Town.(Stellenbosch : Stellenbosch University, 2017-03) Muller, Regardt; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. Electrical and Electronic Engineering.ENGLISH ABSTRACT: According to the WWF, food, water and energy security form the basis of any selfsufficient economy. A crisis in any of the three systems will directly affect the other two. The WWF believes that effectively averting such a crisis requires enhanced information, coordinated planning and adapting to a resource-scarce future. As a result of a global movement toward “green” or sustainable living and possibly boosted by the recently experienced crises in two of these systems, businesses in South Africa have adapted by investing in “green” or resource efficient facilities. The Green Building Council of South Africa, through their rating system, provides a certification process to acknowledge market leaders in this movement. With the development of modern buildings, electronic building systems and controls become increasingly complex, necessitating the use of a building management system. The V&A Waterfront’s No. 5 Silo building in Cape Town is no different. It is one of a number of buildings in the Silo district that makes use of a seawater district cooling system as an alternative source, primarily for air conditioning purposes. It also utilises a central air conditioning system that incorporates a number of energy saving features. All of its air conditioning systems are also monitored and controlled by a building management system. This research focusses on the design and assessment of an energy efficient office building, concentrating specifically on the role that a building management system plays in achieving energy efficiency. Various methods of reducing resource consumption or improving system efficiencies are investigated and discussed based on implementation, achievable savings, costs and other complexities. Focus areas include the use of alternative, more sustainable sources, various optimisation methods as well as closely monitoring and reporting of consumption data. The impact of a building management system and the green building rating system on a building project and specifically on its resource efficiency is also evaluated. This information gathered from existing literature is used to assess savings methods that are applied to the No. 5 Silo building. The design, construction and operation of its air conditioning systems are described in depth, focussing on energy saving practices and ways of quantifying the potential savings. The No. 5 Silo building management system is practically tested for its functionality and is used to gather operational data from the building to investigate potential energy savings. The data is processed, presented graphically and interpreted in terms of its usefulness, visible savings and other trends or events that are identified. The results confirm that substantial savings are achieved through the use of the district cooling system. It also quantifies and proves the previously unknown amount of energy saved through the economy cycle feature of central air handling units. The combined effect of the results and preceding tests also proves the building management system to be an invaluable tool for the monitoring and controlling of building systems from a central point. Transferability to other scenarios (buildings, regions) will be evaluated, and key lessons learned will be captured for the benefit of future ventures.
- ItemDetecting potholes with monocular computer vision: A Performance evaluation of techniques(Stellenbosch : Stellenbosch University, 2016-03) Nienaber, Sonja; Booysen, M. J.; Kroon, R. S. (Steve); Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Potholes in road surfaces create problems for motorists and driverless vehicles. This is because the damage to the vehicle that can be caused by hitting a pothole with a vehicle can be costly and even dangerous. Previous works of other authors with respect to pothole detection did not investigate the limitations of the detection capabilities of their works such as the distance at which the potholes could be detected and often used footage where the camera was directly facing the road, thereby only having a viewing range of roughly 2-4 m. In order to complete this project, it was necessary to obtain suitable footage of potholes. The method for collecting the pothole footage can be seen as novel. The method included attaching a GoPro camera inside of a vehicle windscreen and photographing the road as the vehicle was driven around. This footage is, therefore, akin to a driver’s viewpoint of the road. This viewpoint is advantageous as it ensures that the maximum amount of the road can be photographed by the camera. By mounting the camera in this manner, it could potentially be possible to detect potholes before the vehicle reaches them as opposed to other works done where the camera was mounted to the rear of the vehicle. In the instance of a driverless vehicle, this would allow the vehicle to avoid hitting the pothole and would prevent damage to the vehicle. Due to the difficulty of detecting potholes, the footage was split into two different datasets namely, a simple scenario and a complex scenario. The simple scenario considered footage where the road lighting conditions were always open and clear. In this scenario, the road was extracted and only the extracted region was used in pothole detection algorithms. The complex scenario considered footage where the road lighting conditions were either open or contained mixed lighting conditions. Therefore, in this scenario, the input images were cropped to the suspected road region within the image. This region is rectangular and contains additional information along the sides of the image such as foliage etc. Image processing algorithms, as well as machine learning algorithms were deployed in this thesis to investigate the feasibility of pothole detection. The machine learning algorithms used, consisted of an LBP (Local Binary Pattern) cascade classifier and an SVM (Support Vector Machine) with HOG (Histogram of Oriented Gradients) features. The pothole locations were also analysed in terms of the relative distance that a pothole occurred from the camera. This process is known as depth estimation in monocular images, and this work allowed for determining the ranges at which pothole detection was more successful than others. The discrepancy in the results at the different depth ranges might indicate that different algorithms and classifiers need to be implemented for different ranges to increase the performance of the pothole detector. The final results of this project indicate that under certain conditions, it is possible to detect potholes with modest results.
- ItemDevelopment of a non-invasive water flow meter for a smart geyser(Stellenbosch : Stellenbosch University, 2018-03) Pirow, Nicol Oswald; Booysen, M. J.; Louw, Tobias M.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: South Africa has experienced electricity and water shortages in recent years. The use of smart geyser controller units has the potential to decrease the electricity and water consumption associated with the domestic sector. The installation of an in-line, invasive flow meter is the most expensive aspect of the costs associated with smart geyser controllers. The aim of the project is to develop a non-invasive, retrofit water flow meter which is intended to be used for smart geyser controllers in domestic applications. The successful design of such a non-invasive water flow meter would decrease the installation cost and installation inconvenience associated with smart geyser controllers. This means that more individuals can use smart geyser controllers which can result in a greater total decrease in resource consumption. Several non-invasive fluid measurement methods were investigated in the context of domestic hot water flow. Many were found to be too expensive or require complex installation which meant that they would not provide the intended convenience to users. Thermal methods and vibration methods were investigated to design a non-invasive flow meter which required less expensive components and did not require a complex installation. The use of thermal methods only to measure domestic flow was investigated. It was determined to be impractical due to the small temperature differences associated with domestic conditions and the diffcult installation required for accurate temperature measurements using inexpensive sensors. A non-invasive flow estimation algorithm was designed which used the fusion of thermal and vibration data provided using relatively inexpensive sensors which did not require complex installation. The algorithm was able to detect hot water usage events with over 90% accuracy using thermal and vibration data. Event detection was successful for flow events spaced at least 2 minute apart. Flow rate estimation was performed using vibration data. A quadratic relationship between higher industrial flow rates and vibration standard deviation was found in literature, but a linear relationship was found for domestic conditions. Suficiently accurate quantitative flow rate estimation was possible for flow rates above 5 L min -1. The consumption patterns which occurred within these algorithm limitations were found to constitute 60% of measured volumetric consumption for anonymous smart geyser controller units in a field dataset. The use of fixed flow rate approximations for low flow rates (which could be detected but not quantitatively estimated) increased the simulated performance of the system from the mentioned 60% to 90%. The volumetric flow estimation accuracy of the algorithm was sufficient and the same error margins of 10% were achieved which matches the in-line flow meter currently used in installations. The results of this study show a proof of concept that non-invasive flow measurement can be performed for domestic conditions using the combination of thermal and vibration methods. The required consumption data can be gathered with a system that does not require expensive components or a complex installation procedure.
- ItemThe development of a novel method to identify and describe driving events using only MEMS-sensors in an unmounted smartphone.(Stellenbosch : Stellenbosch University, 2017-03) Bruwer, Frikkie; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The field of vehicle telematics has been revolutionised by mobile- and sensor technology. Mobile phones have become pervasive and the increase in processing capacity, connectivity and richness of sensors have lead to dedicated vehicle telematics hardware being replaced by the widely obtainable and affordable smartphone. The main inconveniences of using mobile phones for telematics sensing are batteryhungry systems (such as GPS) and app-related constraints on device position during operation (as required by systems using Microelectromechanical Systems (MEMS) sensors). Since users are in control of smartphones' permissions and application life cycles, these can be revoked and deactivated at will. Thus, to be a viable solution, the inconvenience caused to the user has to be minimised. This thesis analyses and compares the efficacy and challenges of using the Global Positioning System (GPS) vs. Microelectromechanical Systems (MEMS) sensors. The main metric considered, apart from user convenience, is the ability to detect driving events. It is hypothesised that a generalised sensing platform can be developed to identify a complete and representative set of driving events by exclusively using MEMS sensors in an unmounted smartphone. A system is developed for collecting, annotating and visualising driving data. More than 5000 user-identified driving events' data were collected and labelled using a developed, automated, Fuzzy Logic-based annotation algorithm. MEMS sensor errors and errors induced by sampling from a smartphone-based platform were characterised and a thorough spectral analysis identified high frequency information in MEMS sensor data with specific relevance to driving event detection. A unique multirate processing pipeline was developed using the acquired knowledge. By mitigating the identified errors, exploiting high frequency characteristics in the data and implementing a novel reorientation algorithm, the processing pipeline allows data from an unmounted smartphone to be transformed causally and efficiently into data apt for machine learning. Hidden Markov Models and Random Forests are trained, tested and compared using the processed data. The results of the, better performing, Random Forests show a Balanced accuracy of 70.3% for classifying a complete set of 9 driving events at 2Hz and balanced accuracies of 93%, 88% and 78% for most prevalent events, turning, stationarity and coasting respectively. Though the developed processing and classification systems have not been optimised, or implemented in the form of a smartphone application, the road has been paved for doing so. Given an application that can classify all significant types of driving events in a non-invasive and convenient way, information of specific relevance to an event of interest (i.e. yaw rate for a turn) could be parametrised and uploaded to the cloud. This could have a disruptive effect on the fields of vehicle telematics, intelligent transportation systems and participatory data aggregation.
- ItemA domestic electric water heater application for Smart Grid.(Stellenbosch : Stellenbosch University, 2017-03) Cloete, Andrew Hector; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Domestic electric water heaters (EWHs) are some of the largest consumers of electricity in the residential sector. EWHs are also responsible for high demand peaks, which add additional strain to the electrical grid. Currently, redistributors manage EWHs countrywide by using ripple control to remotely switch EWHs. However, ripple control is a unidirectional system that switches EWHs in bulk and subsequently cannot take individual customers into consideration. Peak demand management of electricity supply often disregards the comfort level of EWH users. This study presents advancements on two separate, but complementary, components that are necessary in a system in order to address both aspects, i.e. demand-side management as well as comfort levels. The components include a bidirectional communication system and computationally efficient EWH model. The former has the ability to connect a large number of EWH for monitoring and control. The latter is an accurate prediction tool to assess the EWH state in order to assist in its switch control. For the purpose of this research, two communication systems were developed for existing EWH monitoring that are equipped with cellular modems. The first system complies with the recent specifications released for machine-to-machine (M2M) communication known as SmartM2M. The second system uses popular web technologies and employs the lightweight MQTT application layer protocol. Both systems functioned as designed. It was found that the SmartM2M standards, although effective, lacks adoption at this point in time which made application development cumbersome. MQTT was employed by using community developed software for both client and server side, and proved highly effective. The cellular modem interface (known as the extended AT command set) proved challenging, as it is an obscure, vendor dependent interface with little community support. A communication software stack was developed that systematically interfaces with the modem. The communication software stack proved highly effective, enabling the MQTT protocol, the dialling of network service codes and remote firmware updates. A rigorous laboratory experiment was developed to validate the accuracy of computationally effcient EWH models proposed in a previous study. The experiment entailed performing automatic, consistent and precise water draw-off and heating, while periodically measuring several metrics. Eight datasets of 9- day experimental data was generated and used to compare with corresponding simulated results using the EWH nodal models. Overall, the models showed good accuracy in predicting input energy, energy efficiency and water draw-off temperature. Under scheduled heating control (as opposed to "always on"), increased model accuracy was observed in all three aforementioned categories. The experimental data was also used to show that the energy savings possible by implementing a heating schedule is approximately 6%, given the same effective output energy as when an "always on" heating schedule is applied.
- ItemThe evaluation and testing of mobile ITS interventions on speed compliance in the minibus taxi industry of South Africa(Stellenbosch : Stellenbosch University, 2015-12) Akoku Ebot Eno Akpa, Nelson; Booysen, M. J.; Sinclair, M.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Informal public transport in South Africa, dominated by minibus taxis is noted for poor compliance, and has been shown to disregard posted speed limits on long-distance trips. They go as far as driving over the di erentiated speed limit of the lighter passenger vehicles used for private transport. This work compares and evaluates improvements in their speed compliance using two renowned interventions: automated Average Speed Enforcement (ASE), and auditory Intelligent Speed Adaptation (ISA). The feasibility of fuel economy existing as a self-regulatory incentive for speed compliant driving is investigated, together with the impact of each intervention on fuel consumption rates. The main ndings were that with minibus taxis, ASE is not well understood and needs ISA as a complementary intervention, and safe driving can increase driver remuneration from fuel costs. Average Speed Enforcement is an emergent alternative to instantaneous speed enforcement to improve road safety. This study involves a mixed methods approach in understanding driver response to the system on the R61 Between Beaufort West and Aberdeen in South Africa. A spatio-temporal quantitative study of speed compliance is conducted. Various speed metrics are measured prior to, and during enforcement, and ASE impact on crash risk and injury severity is also examined. These measurements are taken on the enforcement route and on control routes having similar characteristics. Two main modes of transport in the region are considered, namely minibus taxis and passenger vehicles. A qualitative study is also conducted to evaluate the relationship between speed compliance and understanding of the system. Results show that for passenger vehicles, the ASE system led to a reduction in mean speed on the enforcement and adjacent control routes. However, ASE appears to have no in uence on minibus taxis, which could be linked to limited understanding on ASE operation. This study also tests and evaluates the impact of an auditory ISA intervention, applied at various levels, on the speeding behaviour of the seemingly intransigent minibus taxi industry. The experiment evaluates the same ASE section on the R61, to which the minibus taxi drivers were seemingly impervious. Various speed metrics, as well as their statistical relevance and the e ect sizes are evaluated. Results show that the auditory ISA intervention has a clear impact on speeding behaviour, both when applied at an audible level that can be drowned out by a radio, and even more so at a loud level. The impact on speeding is signi cant, with speeding frequency (both time and distance) reducing by over 20 percentage points. Also, although the drivers showed little or no behavioural change when driving on the ASE route, introduction of the ISA system resulted in signi cant changes bringing violation frequencies down to 47.4% from 81.2% on the enforcement route. These changes brought about lower fuel consumption rates especially with the ISA system, and drivers can increase their remuneration by a minimum of about 120% and by up to 214% from the fuel budget if they drive safely.
- ItemEvaluation of next-generation low-power communication technologies to replace GSM in IoT-applications(Stellenbosch : Stellenbosch University, 2018-12) Durand, Thomas Gerhardus; Booysen, M. J.; Visagie, L.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: In today's world smart metering and control has become a critical component of our modern lifestyle. Smart Internet of Things (IoT) devices are used in a variety of applications in all sectors. Due to the rapid expansion of IoT applications, various IoT-focused communication networks are being developed and deployed. Although many technologies are available and being pursued, they do not all perform equally for all key metrics of the various applications. Choosing the right technology for the right application is di cult with the plethora of technologies and their claims. This thesis provides an impartial and fair overview of the performance of alternative communication technologies available to the current cellular standard. Specifically, Sigfox, LoRaWAN and NB-IoT are compared to determine the best application for each technology. Through investigating current literature, a suitable set of test metrics are identified, motivated, and used to compare the different communication technologies. The comparative metrics consists of two categories. Firstly, performance is compared through practically testing the power-consumption, maximum coupling loss (MCL), throughput and simulating the scalability. Secondly, different application metrics that affect performance, specifically the antenna, polarization, near-field interference, transmission power, path loss and coverage are evaluated. To compare the technologies, four identical test devices were built and the firmware for each developed, each with their own communication module and test points in order to test power consumption. A LoRaWAN TTN base station was built to provide coverage in the testing area. To measure the power consumption of the communications modules accurately, a current measurement solution is designed, developed, built and tested. A complete back-end system is developed to store data transmitted by devices, used in the different testing procedures. The research objective to develop, test and compare the hardware and firmware of the different communication technologies is achieved. The results indicate that there is no one solution to all IoT applications, however certain technologies are better suited, based on their performance metrics. The test verified the ultra-low power consumption of LoRaWAN and Sigfox, while it indicated that NB-IoT's network process currently limits the power consumption savings of NB-IoT. NB-IoT and Sigfox performed the best in MCL tests, while GPRS performed the worst. Due to LoRaWAN and Sigfox's radio band duty cycle limitations, throughput is relatively limited compared to NB-IoT and GPRS.
- ItemFirmware and functional test platform developed for a smart controller(Stellenbosch : Stellenbosch University, 2017-12) Naude, Nicolaas Hendrik; Booysen, M. J.; Barnard, Arno; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Natural resources are important for human existence. Initiatives to manage resources effectively are exercised daily. The consumption of water and electricity increases daily in South Africa, and worldwide, thus the need for exploring new resource savings techniques. The primary electricity supplier of South Africa, Eskom, can not meet the current demand at all times. Not only is South Africa facing a shortage of electricity supply, but, at the time of writing, also a drought that could harm the economy. The Western Cape and the Eastern Cape provinces are especially under pressure by the drought. The Western Cape government implemented water usage limits and it is currently escalated to 87 L per person per day. The Nelson Mandela Bay municipality, in the Eastern Cape, was on the verge of being declared a drought disaster area in March of 2017. The necessity of saving initiatives are thus evident for South Africa. The Internet of Things is well suited to contribute to these savings initiatives. This thesis forms part of a smart controller (SC) for electric water heaters (EWHs), which allows the user to monitor water usage and set a control schedule to automatically switch the EWH on and off. The SC gathers data from EWHs, allowing research to predict optimal heating schedules. This research can also be used to implement a scheduling technique to switch an EWH on and off, depending on the national electricity grid load during peak consumption times, whilst still providing the EWH user with hot water on demand. The first development in this thesis is focused on designing and implementing firmware for a new SC hardware design. The SC communicates to a central database, with the use of an equipped cellular modem. The firmware consists of two parts, modem firmware and peripheral firmware. The peripheral firmware is responsible for correct actuator function and measuring the sensors accurately. The measurements are aggregated and concatenated into a single report string, which is sent to a cloud based database every minute. The SC forms part of a smart electric water heater controller project, which received funding from the Water Research Council to develop and install SCs in eMkhondo municipality district in Mpumalanga, South Africa. The SC used for research purposes is upgraded with new hardware, containing a new processor, which lead to the requirement of new rmware. The new hardware was tested in-house by a labourer, which required technical skills. This test required physical signal injection and result evaluation by the tester. The need to improve this test procedure lead to the second development of this thesis. An automatic test procedure is designed, which consists of test hardware and test software. The implementation of the complete test system is evaluated and the system efficacy is determined. The research objective to develop and implement firmware for the new SC hardware is achieved and is implemented on a total of 245 SCs. The data collected, by these SCs, was of such a standard that research could be done on optimisation of heating schedules and provide a means to create awareness of a household's EWH consumption patterns. The second objective to develop and implement a test system was achieved, where the accuracy of the hardware is determined and the test system efficacy showed, during the validation tests, six of the ten tests were successful. The test system would be a benefit to small scale production sectors, where uncertified test equipment suface and cost effective test solutions are required.
- ItemIdentification of driving manoeuvres using smartphone-based GPS and inertial forces measurement(Stellenbosch : Stellenbosch University, 2015-03) Engelbrecht, Jarrett; Booysen, M. J.; Van Rooyen, G-J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Road accidents are a growing concern for governments and is rising to become one of the leading causes of death in developing countries. Aggressive driving is one of the major causes of road accidents, and it is therefore important to investigate ways to improve people's driving habits. The ubiquitous presence of smartphones provides a new platform on which to implement sensor networks in vehicles, and therefore this thesis focuses on the use of smartphones to monitor a person's driving behaviour. The framework for a smartphone-based system that can detect and classify various driving manoeuvres is researched. As a proof of concept, a system is developed that specifically detects lateral driving manoeuvres and that classifies them as aggressive or not, using a supervised learning classification algorithm. Existing solutions found in research literature are investigated and presented. The best existing solution, a dynamic time warping classification approach, is also implemented and tested. We use an aggressive driving model that is based on the angle of a turn, the lateral force exerted on the vehicle and its speed through the turn. The tests and results of the implemented manoeuvre detection and classifcation algorithms are presented, and thoroughly discussed. The performance of each classifer is tested using the same data set, and a quantitative comparison are made between them. Ultimately, a lateral driving manoeuvre detection and recognition system was successfully developed, and its potential to be implemented on a smartphone was substantiated. The suitability of supervised learning classi ers for classifying aggressive driving, in comparison to dynamic time warping classifcation, was successfully demonstrated and used to validate our aggressive driving model. Conceivably, this work can be employed in the future to develop an holistic smartphone-based driver behaviour monitoring system, which can be easily deployed on a large scale to help make the public drive better. This would make our roads safer, reducing the occurrence of road accidents and fatalities.
- ItemImpacts of electric vehicle charging in South Africa and photovoltaic carports as a mitigation technique(Stellenbosch : Stellenbosch University, 2021-03) Buresh, Kevin; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The rise of greenhouse gas emissions having detrimental impacts on the environment have raised concerns. Efforts to combat these emissions have been agreed upon by countries across the globe, including South Africa. Reducing emissions, such as carbon, is commonly proposed as moving from coal-based generation sources to renewable sources for electricity,along with shifting from internal combustion engine (ICE) vehicles to electric vehicles(EVs). EVs have gained popularity internationally and are becoming widely adopted as a greener alternative. Research has uncovered that this may not always be the case, provided the different electricity generation sources utilized. South Africa, having a coal-dependent grid, might not see a reduction of emissions with the adoption of EVs. Mass charging of EVs can also jeopardize grid stability by creating new peak demands, which could be detrimental for South Africa’s currently fragile grid. Fortunately, through the use of renewable sources to offset electricity from the grid when charging EVs and implementing smart charging strategies, EVs could meet their acclaimed potential benefits.A simulation model was developed to examine the effects of varying EV fleet sizes in South Africa, and the potential of mitigation strategies such as large employers providing solar photovoltaic (PV) carport charging stations and smart charging methods. A varying fleet size aids in investigating the impacts of EV charging from the perspective of a vehicle owner, a large employer and the national grid. The model incorporates a solar PV model with measured weather data, along with an EV model consisting of a mobility model and battery model. A smart charging method was developed to limit the number of vehicles charging simultaneously based on a maximum load peak demand. This demand-side management (DSM) strategy determines the charging urgency of EVs to formulate a prioritized charging schedule. During this project, it was found that the current grid capacity would not be sufficient for more than four million EVs charging without any intervention. When supplementing charging with PV carports, the grid capacity could handle at least an additional 10% increase in fleet size. An employer providing PV carport charging would see an increase in revenue from electricity sales when customers only charge at work. A vehicle owner was found to have a cleaner carbon footprint travelling with a petrol ICE vehicle than an EV,except for scenarios where EVs utilize PV carports and would have the lowest operational costs when driving an EV that does not charge at home.Supplementary PV energy does prove to be a useful mitigation strategy, but when EVs are allowed to charge freely at work, they do not take advantage of the full potential. Employers, when coupling smart charging strategies with PV carports, gain further control of load demands, reductions in operational costs and grid energy consumption. An employer implementing charging imposed load limit restrictions, while still providing user comfort to vehicle owners, was seen to reduce the imposed peak demand by more than half and led to a doubling of the yearly revenue. Various levels of restrictions, when evaluated, were seen to have a significant impact on user comfort, with little impact on financial benefits.Overall, this project has demonstrated not only the need for EV charging mitigation strategies, but also the potential benefits of solar PV carports coupled with smart charging strategies.
- ItemLoad management of electric water heaters in a smart grid through forecasting and intelligent centralised control(Stellenbosch : Stellenbosch University, 2018-03) Roux, Marcel; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Globally utilities are facing increasing demand and numerous challenges arise with the supply and management thereof. The South African electricity utility Eskom is at present still facing difficulty with meeting the country's growing demand. One of the largest consumers of energy in the residential sector has been identified as the domestic electric water heater (EWH). To manage significant peak loads, electricity utilities employ demand side management (DSM) strategies to throttle demand in order to maintain stability in the electrical grid. Ripple control is such a strategy which is a blunt, unidirectional control scheme which toggles electrical supply to zones of EWHs at times with no consideration for the comfort of individual consumers. Smart grid (SG) technology is on the rise and emerging Internet of things (IoT) technology augments the adoption of SG to address the problem of DSM. The data collected from a SG is of high value for knowledge discovery and many advantages can be obtained from effective analysis of this data. This study utilises data obtained through the Geasy project which presents a smart EWH controller to enable the monitoring and control of EWHs with resolution of 1 minute. This study presents a three-part look at different aspects of the data aimed towards the development of a cogent, data-driven bidirectional DSM application. Of fundamental importance to data analysis is to assess the current quality of the data, due to the "garbage in, garbage out" principle. High quality data is required for analysis. After investigating potential data quality impacting factors, the Geasy data was used to develop a numerical data cleaning framework with scalability in mind. The implemented routines were tailored to the specific needs of the data fields considered, such as removing erroneous spikes and filling in missing data according to the most suitable processes. The cleaned data had vastly superior data quality and indicates that the developed data cleaning framework may provide a baseline for more advanced data cleaning steps to be employed before data warehousing. Next, the aspect of predictive scheduling was investigated. The temporal structure of one of the largest drivers of EWH usage, the hot water usage, was investigated using statistical methods including time series decomposition, autocorrelation and partial autocorrelation plots. The decomposition of the usage data indicated a strong seasonal component that indicated potential for forecasting. Linear seasonal autoregressive integrated moving average models were used to create models of the temporal structure of the usage data. Box-Jenkins parameter identification proved highly effective in estimating good, general-purpose seasonal forecasting models. The obtained forecasting results were shown to predict a daily water volume of 225 L, compared to the observed 272 L, which indicates an error of 17.3 %. However, correcting the forecast volume with the normalised observed training volume reduced the volume error to 0 %. Continuing the exploration of the value of the SG data, a DSM application was developed to balance the utility and consumer need in real time. During the development of the algorithms, a computationally efficient EWH thermal model was revised to provide improved scalability through vectorisation which also enabled the algorithms to consider multiple, micro-simulated EWHs during the macro evaluation of a microgrid. The approach uses actual individual hot water consumption patterns, measured real-time water heater temperatures and individual EWH properties as the main determinants in a cost function for a centralised scheduler. The application was evaluated against various demand and temperature limits, with actual consumption measured in a field trial of 34 EWHs for a period of measurements spanning 28 days at 1 minute resolution. For a temperature limit of 60° C, the application reduces the peak load from a measured 47 kW to 20 kW (vs. 106 kW for full ripple control). The number of undesired cold events decreases by 83.3 %, improving consumer experience, while the total grid energy consumption only increases by 12 %.
- ItemModule-level health monitoring of solar PV plants using LoRa wireless sensor networks(Stellenbosch : Stellenbosch University, 2019-04) Shuda, Eduan Joseph; Rix, Arnold J.; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The monitoring of PV plants is a crucial aspect in ensuring smooth operation and optimum e ciency. Early detection of faults or ine ciencies can greatly reduce downtime and increase overall plant e ciency. Faults include temporary and permanent soiling, shadowing, anomalous ageing and critical electrical or mechanical faults. Many solar installations are located at remote locations; faults often go unnoticed and unattended to for long periods. A remote module-level monitoring system can detect ine ciencies and faults when and where they occur. A wireless module-level monitoring system that measures electrical and environmental quantities related to PV module performance is proposed in this work. Although various wireless module-level sensor approaches exist, the sheer size of a typical solar PV plant presents challenges for the wireless technologies presented in these approaches. Di erent wireless technologies such as Bluetooth, Zigbee, Wi-Fi, GSM, Sigfox and LoRa were evaluated for the proposed monitoring system. LoRa was chosen as the wireless technology due to its long range and low power consumption. A number of sensor nodes and a gateway was designed, built and tested. Each sensor node is capable of measuring voltage, current, irradiance, ambient temperature, module temperature, orientation and tampering detection. Initial eld tests that were carried out indicate that the sensor nodes measure with adequate accuracy to evaluate PV module performance in detail. The developed monitoring system consisting of fteen sensor nodes, a gateway and a remote GUI application was tested on a operational PV plant. Shading and soiling eld scenarios, as well as a shading experiment proved that the module-level monitoring system is capable of detecting faults and ine ciencies within a PV plant. Results that were obtained indicate the following: sensor nodes are modular, self-powered and low maintenance. The wireless technology used to transmit measurement data from the sensor nodes to a central gateway is capable of operating on a small, medium or large PV plant. The monitoring system is also capable of remote detection and reporting via the GUI application.
- ItemNB-IoT (LTE Cat-NB1 / narrow-band IoT) performance evaluation of variability in multiple LTE vendors, UE devices and MNOs(Stellenbosch : Stellenbosch University, 2020-04) Robinson, Daniel; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Cellular 2G/GPRS is a sun-setting technology worldwide leaving behind a void for wireless low-power widearea-networks (LPWANs) such as LoRaWAN, SigFox and NB-IoT to fill. With NB-IoT on the roadmap towards 5G New Radio (NR), it is a promising contender due to its bidirectionality, power-saving mechanisms and ease of integration with existing equipment, yet there still exists a general uncertainty with regard to adoption. Research shows that most literature on NB-IoT is based on precise mathematical models, analysis or simulations, except for a few empirical performance evaluations which find variability in devices connected to a single network. The study theorizes that networks are responsible for the variation found in metrics and estimations, due to the high underlying complexity of Long-Term Evolution (LTE) architecture on which NB-IoT is based. Thus, the study proposes an empirical investigation using mobile-network operators (MNOs) in South Africa by comparing multiple top LTE vendors including Ericsson and ZTE on MTN’s network, and on Vodacom’s network Huawei and Nokia. Furthermore, similar user equipment (UE) devices such as Ublox and Quectel are used as a control to observe network changes via RF attenuation. A set of telemetry tests are developed to capture various metrics and estimations into datasets for comparison, which include differently sized UDP packet datagrams, cellular operator selection (COPS), extended discontinuous reception (eDRX) and periodic tracking-area-updates (PTAU). Data is measured using an external energy capture device or reported by the UE device for post-processing and analysis in plots, mean distribution tables and boxplots. Metrics such as latency, power efficiency, signal strength, enhanced coverage level (ECL) classes, throughput and data overhead are included, as well as estimates for telemetry interval periodicity and battery longevity. K-means clustering is applied to the datasets to reduce the skewness induced by the increased number of low-latency values during captures to normalize the number of unique features for comparison. Most clearly visible in the tests is how MTN leads Vodacom in NB-IoT performance due to Nokia’s subpar results. Power efficiency and latency metrics show that when connected to Vodacom-Nokia, results can factor up 20 and 10 times worse, respectively. Otherwise, ZTE, Ericsson and Huawei show satisfactory latency under the 10 second 3GPP standard. Although LTE vendors meet the 164 dBm MCL requirement, Vodacom-Nokia has 10 dB less receive sensitivity, with the rest at -130 dBm. Transmit power increases at 10 dBm per RSRP decade until its maximum at 23 dBm, except for Nokia which remains at full power. ECL classes overlap with respect to RSRP, yet partially correlate, which suggests an unknown network factor or hysteresis of a few seconds in the test captures. Nevertheless, Nokia is mostly in ECL class 1, while others are a mix of ECL class 0 and 1. This has an impact on the number of dynamic repetitions of messages between UE devices and cell-tower eNodeBs. Throughput is under 10 kbps, which is half or less than UE device claims by manufacturers. A quarter of datagrams in the telemetry test set show protocol overhead extending over 512 bytes in uplink and 200 bytes in downlink, except for Nokia extending up to 10,000 bytes. Telemetry interval and battery longevity estimates on a 9.36 Wh AA battery suggest that ZTE, Ericsson and Huawei can transmit 16-512 bytes between every 5 to 30 minutes to last at least a year, or hourly to last up to 10 years, however, a device that transmits hourly on the Vodacom-Nokia network will only last 2 months. The study provides recommendations based on these results. Finally, South Africa is ready for mobile network operators to deploy national NB-IoT coverage using ZTE, Ericsson and Huawei, but not using Nokia. With a satisfactory inter-cell tower distance, UE devices avoid having to use dynamic repetitions in higher ECL classes, thus keeping the variability that affects many of the metrics and estimates in the study to a minimum.
- ItemOn the use of WiMAX and Wi-Fi in a VANET to provide in-vehicle connectivity and media distribution(Stellenbosch : Stellenbosch University, 2011-12) Mojela, Lerotholi Solomon; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The recent emergence of ubiquitous wireless connectivity and the increasing computational capacity of modern vehicles have triggered immense interest in the possibilities of vehicular connectivity. A plethora of potential applications for vehicular networks have been proposed in the areas of safety, traffic infrastructure management, information, and entertainment. The broad range of applications requires creative utilisation of the available wireless medium, using a combination of existing and novel wireless technologies. In this research the evaluation of one such configuration is performed. Dedicated short range communication for safety applications is assumed, and the use of Wi- Fi and WiMAX for non-safety applications is evaluated. Little is known about the media streaming performance of these wireless technologies in realistic vehicular ad-hoc network (VANET) scenarios. Due to the extreme mobility and unpredictable environmental aspects in a real road environment, an empirical evaluation is performed and presented. Evaluation of a multi-vehicle to infrastructure (V2V2I) VANET, using Wi-Fi for the vehicle-to-vehicle communication and WiMAX for the vehicle to infrastructure (V2I) communication is experimented. It is observed that Wi-Fi is unaffected by the vehicle speed; whenever nodes are within communication range, data gets transferred normally. A detailed characterisation of the network architecture is presented and the results show that a multitude of applications can be supported with this proposed network architecture.
- ItemProof of concept : home automation solution with potential for seamless integration and vast expansion(Stellenbosch : Stellenbosch University, 2014-12) Sawyer, Guy; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The ever-increasing existence of electronic systems and devices within the residential environment, along with the human desire to simplify life and daily routine, is generating increased interest in the field of home automation (HA) and intelligent environments. A large variety of home automation solutions have been conceptualised or developed. However, many of these solutions are designed by experts and require professionals to install and/or operate them. Furthermore they lack the potential for seamless integration into an already functioning home environment. To bridge the gap between consumer and expert as well as allowing for integration into any existing home environment without physical alteration to the building, a modular home automation solution with seamless integration potential is proposed. The implemented system uses open source software and hardware allowing for development to continue within the existing, large open source community. It can be installed and configured without professional skills or physical alteration of the environment itself and due to its modular design, the system also allows users to add and remove functional components to and from the system providing them with a seamlessly customisable home automation solution. Conceptual design and practical implementations are covered in this document, along with recommendations for both continued research and potential avenues for expansion.
- ItemReal time segmentation of heart sounds(Stellenbosch : Stellenbosch University, 2015-12) Fourie, David; Booysen, M. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The poor state of the healthcare system in South Africa has resulted in unacceptable high levels of infant mortality. Congenital heart disease is one of the main contributions to these high rates of mortality, with the cost of treatment and the availability of specialists being the driving factors. Computer aided auscultation is a technological solution to assist with the diagnosis of the disease. In its current form, computer aided auscultation is unsuitable for continuous patient monitoring. The aim of this thesis is to develop an algorithm that will allow the existing methods of computer aided auscultation to work in real time so they can be used in patient monitoring. Existing methods of identifying the first and second heart sound are limited to offline processing. The algorithm developed in this thesis uses the correlation of the time-frequency coefficients of individual heart sounds to generate a feature vector for each heart sound that can be used to separate the sounds into different groups. To test the performance of the algorithm, 230 heart sounds from normal patients were first manually segmented and then processed with the algorithm. The noise sensitivity of the algorithm was also tested using generated heart sounds. Finally, the real time capability of the algorithm was tested. The testing against sounds for normal patients resulted in a 84.2 % accuracy and an 84.4% hit rate. The synthetic testing showed the system starts to perform badly with a signal to noise ratio lower than -10db. The real time testing of the system showed that the algorithm is fast enough to be used in a real time environment. This thesis concludes that proposed algorithm is suitable for the detection of the first and second heart sounds in real time.
- ItemReducing energy costs within schools in South Africa using solar and intelligent hot water interventions(Stellenbosch : Stellenbosch University, 2019-12) Gerber, Stefan; Booysen, M. J.; Rix, A. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: The educational gap within socio-economic groups in South Africa is immense and learners within no-fee schools are at a disadvantage with most of the available funding being used for personnel salaries. As the energy costs in South Africa rise, the remaining non-personnel funding will decrease, limiting spending on teacher-support materials and school maintenance. This has led to lasting problems within these communities and constrains the ability of the education system to provide learners of these schools with a pathway out of poverty. Schools are currently billed on commercial and industrial tariffic structures, and by reducing their energy usage and maximum monthly demand, money can be saved to be better spent improving the quality of education delivered. To address this problem a comprehensive system capable of estimating the potential financial viability of solar and load-shifting interventions within a school environment was developed. A method capable of determining the energy usage within schools was developed. This process creates a generic energy consumption profile for a building from measured energy usage data of a subset of schools, and is expanded to scale the load profile using only usage data from utility bills as well as seasonal dates to produce a load forecast. The method was validated using five datasets each containing the hourly energy usage measurement data from schools over a period of three years, and was capable of forecasting the yearly energy consumption of the schools to within an averaged accuracy of 5% while estimating the maximum monthly demand to 6% of the measured usage. A PV optimisation technique was implemented using the forecast to estimate the potential profitability of various solar system sizes by determining the internal rate of return and the utilisation of the system's generating capacity. It was able to identify the optimal system size of the schools with the best return on investment, presenting itself as a valuable tool for reducing the financial burden many schools face. Three control schemes of intelligent water heater scheduling were researched. Firstly, a priority-based scheduler was configured to heat water using the school's water usage history while diverting any excess solar energy to the water heaters to exploit their energy storage capabilities, increasing the school's energy bill savings to 23.2% per month. Secondly, a bi-thermal control method was added to the priority-based scheduler, employing a temperature delta to increase the amount of solar energy to be stored within the water heater tank while minimising their grid reliance and improving the monthly savings to 24.8% per month. Finally, a demand-limiter control scheme was implemented in conjunction with bi-thermal control resulting in large demand-charge savings and an average energy bill reduction of 26.7% per month, producing the maximum savings while maintaining suitable levels of user comfort.
- ItemRethinking electrical water heaters(Stellenbosch : Stellenbosch University, 2015-12) Nel, Philip Johannes Cornelis; Booysen, M. J.; Van der Merwe, A. B.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: South Africa is, at the time of writing, in the midst of an energy crisis as the national utility is unable to meet the nation’s energy demands. Electrical water heaters (EWHs) remain one of the main contributors to residential energy consumption in South Africa and other countries where they are used. Although educational material has been published to create awareness of energy saving actions for EWHs, it is unclear if users understand the content and efficiently control their EWHs. Additionally, insufficient feedback of usage data makes it difficult for consumers to understand their consumption patterns and make informed decisions regarding their future water and electricity use. This work presents a mobile based eco-feedback system for the energy and water consumption data of residential EWHs. The system consists of several components: an EWH model; an event detection algorithm; and an Android mobile application. The physics based EWH model was developed in order to accurately simulate the energy input and output of an EWH for various control settings, usage profiles and orientations (i.e. vertical and horizontal). The accuracy of the model is validated against six datasets, four comprising 900 hours with multiple usage events and two with only standing losses. The results show that measured energy usage is modelled with an estimation error of less than 2% and 7% for schedule control and thermostat control respectively. As well as being accurate, the presented model has a low computational complexity, taking only 100 milliseconds to complete a 10 day simulation on a standard desktop machine, making it ideal for use in mobile devices. A novel and non-invasive hardware solution and matching algorithm were developed to support the identification and classification of warm water usage events without the use of invasive and expensive water metering technologies. The algorithm was tested using 49 days of data which included 127 usage events and was found to accurately detect usage events with an accuracy of 91%. Additionally, the algorithm was able to detect very small usage events (0.5 litres was detected successfully). However, the estimated duration of events is within 2 minutes accurate 79% of the time. Additionally, the outlet temperature and water meter data were used as inputs to the EWH model for estimating the energy consumption under various control settings. The outlet temperature data was used to estimate both the total volume of warm water consumed and the energy input for the EWH with an error of less than 10% for 3 of the 4 datasets considered. An Android mobile application was then created to allow consumers to remotely monitor and control their EWH from their mobile device. The EWH model was implemented as part of the functionality of the mobile application to provide a user with instantaneous feedback on the impact of changes in control settings and usage profiles. For example, this functionality in the mobile application allows users to determine how switching their EWH off intermittently will affect their energy consumption. Additionally, the event detection algorithm was utilised by the mobile application to establish usage profiles and provide recommended schedules for users, based on their consumption data. Finally, a usability study was conducted in order to evaluate the ease with which users are able to utilise the mobile application and to improve on any areas of difficulty that may exist. Several areas of difficulty were determined and these results were used to implement various changes to improve the application by making it more user friendly. The results of the study indicate that the system is user friendly and that participants had a positive overall experience with the mobile application.