Research Articles

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https://dir.muni.ac.ug/handle/20.500.12260/17

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Predictive maintenance (Ai) in power generation for rotating machines based on vibration analysis
(2024) Kalyankolo, Zaina; Mwesigwa, Samuel; Ainomuhwezi, Martha; Kibande, Steven; Kalyankolo, Umar
Predictive maintenance, aided by Artificial Intelligence (AI), has emerged as a game-changing approach that will revolutionize how to manage and maintain machinery especially rotating machinery particularly in power generation equipment. Traditional preventive maintenance approaches have proven to be expensive and time-consuming, and frequently fail to detect possible issues before they occur. Case in point is the Callide Power Station’s Unit C4 incident. In 2021, an offshore platform experienced a catastrophic failure of gas turbine generator due to a sudden bearing failure. The incident took place on May 25, 2021, at the Callide Power Station's Unit C4. This breakdown resulted in substantial damage to the transmission network. The primary cause was discovered as high system vibrations and inadequate maintenance of the lubrication systems, which are critical for the smooth operation of the bearings. This paper presents predictive maintenance (Pd.M.) as a leveraging solution to abrupt failure in rotating machines. The paper focuses on vibration analysis as a major determinant of the equipment health.
Evaluation of corrosion performance of LDX 2101 and UNS S32205 in flexible pipeline applications: A comparative study
(Journal of Engineering Research and Reports, 2024-09-24) Gumoshabe, Michael; Opio, Innocent M.; Makanga, Jackson; Kule, Saimon; Ongom, Douglas
Lean duplex stainless steel (LDSS) has been used in various applications, including flexible pipelines in offshore and other industrial settings. In recent years, LDSS has become the preferred choice over standard duplex stainless steel (DSS) for flexible pipeline applications due to its lower costs, achieved by reducing nickel and molybdenum content, while still providing comparable corrosion resistance and mechanical strength properties to DSS. However, there is still limited reporting on the corrosion effects of reducing these alloys on the behaviour of lean duplex stainless steel in flexible pipelines. This comparative study investigates the corrosion resistance of lean duplex stainless steel, LDX 2101 and duplex stainless steel, UNS S32205 in flexible pipeline applications using linear polarization resistance (LPR). The research focuses on assessing material performance in environments containing CO2 and H2S, commonly found in oil and gas production, by conducting short-term and long-term tests to evaluate pitting and selective corrosion. The samples, LDX 2101 and UNS S32205 were immersed in a 3.5M NaCl solution, and corrosion measurements were performed using the Metrohm Autolab potentiostat. The results indicate that both materials exhibit good corrosion resistance, but there are differences in their performance under specific conditions. While lean duplex stainless steel, LDX 2101, can be used as a substitute for duplex stainless steel UNS S32205, its corrosion resistance and mechanical properties gradually decrease over time due to the reduced nickel and molybdenum content. As a result, it would not be as effective as duplex stainless steel UNS S32205 in withstanding corrosion in aggressive conditions over a prolonged period.
Modeling and implementation of a hybrid solar-wind renewable energy system for constant power supply
(Journal of Engineering, Technology & Applied Science, 2024-08-10) Conceptar, Mubeezi; Kalyankolo, Umaru; Eze, Val Hyginus Udoka; Migisha, Jim; Asikuru, Salama; Nassaga, Musa; Ochima, Noah; Okafor, Wisdom
In recent years, Uganda has significantly increased the use of renewable energy sources, particularly solar and wind power. These energy sources are especially crucial in rural and remote areas where connecting to the national grid is challenging. Renewable Energy Sources (RES) have proven to be cost-effective alternatives to traditional energy sources, which often require substantial investments in transmission and distribution networks. This study focuses on designing and implementing a hybrid renewable energy system that integrates both solar and wind power. The research successfully established a reliable and continuous power supply for the community through the combination of wind and solar energy. The hybrid power generation system operates by simultaneously monitoring solar and wind energy using an ACS712 current and voltage sensor. Controlled by a microcontroller, the system employs dual-channel relay switches to activate the power source with sufficient energy to charge the battery. The programming for this system was conducted using C++ and Arduino software. This study highlights the vast potential within the field of sustainable energy. With rapid and economical electricity production, this hybrid system paves the way toward a greener future, where our energy needs can be met in an environmentally friendly manner.
A survey on artificial intelligence in cybersecurity for smart agriculture: state-of-the-art, cyber threats, artificial intelligence applications, and ethical concerns.
(Mesopotamian Academic Press, Imam Ja'afar Al-Sadiq University, 2024-07-20) Ali, Guma; Mijwil, Maad M.; Buruga, Bosco Apparatus; Abotaleb, Mostafa; Adamopoulos, Ioannis
Wireless sensor networks and Internet of Things devices are revolutionizing the smart agriculture industry by increasing production, sustainability, and profitability as connectivity becomes increasingly ubiquitous. However, the industry has become a popular target for cyberattacks. This survey investigates the role of artificial intelligence (AI) in improving cybersecurity in smart agriculture (SA). The relevant literature for the study was gathered from Nature, Wiley Online Library, MDPI, ScienceDirect, Frontiers, IEEE Xplore Digital Library, IGI Global, Springer, Taylor & Francis, and Google Scholar. Of the 320 publications that fit the search criteria, 180 research papers were ultimately chosen for this investigation. The review described advancements from conventional agriculture to modern SA, including architecture and emerging technology. It digs into SA’s numerous uses, emphasizing its potential to transform farming efficiency, production, and sustainability. The growing reliance on SA introduces new cyber threats that endanger its integrity and dependability and provide a complete analysis of their possible consequences. Still, the research examined the essential role of AI in combating these threats, focusing on its applications in threat identification, risk management, and real-time response mechanisms. The survey also discusses ethical concerns such as data privacy, the requirement for high-quality information, and the complexities of AI implementation in SA. This study, therefore, intends to provide researchers and practitioners with insights into AI’s capabilities and future directions in the security of smart agricultural infrastructures. This study hopes to assist researchers, policymakers, and practitioners in harnessing AI for robust cybersecurity in SA, assuring a safe and sustainable agricultural future by comprehensively evaluating the existing environment and future trends.
Design and implementation of a DC to AC power electronics-based inverter that produces pure sine wave output for critical engineering applications
(International Journal of Recent Technology and Applied Science, 2024-02-17) Mubeezi, Conceptar; Kalyankolo, Umaru; Eze, Val Hyginus Udoka; Okafor, Wisdom O.
Power inverters play a crucial role in the field of engineering, particularly in applications where power stability is imperative. In devices such as Uninterruptible Power Supplies (UPS), the conversion of raw power to DC, subsequent filtering, and inversion to AC are executed through pure sine wave inverters. These inverters exhibit remarkable stability, making them ideal for powering sensitive equipment like data switches and Remote Terminal Units (RTUs). This study delves into the intricate process of converting DC power into a pristine sine wave signal. The heart of this power conversion lies in the utilization of the KA3525A integrated circuit (IC) in conjunction with MOSFETs of the PN55 series, supported by capacitors and resistors for effective power filtration. The KA3525A, a monolithic IC, encompasses all essential control circuits for a pulse width modulating regulator. Within this IC, a voltage reference, error amplifier, pulse width modulator, oscillator, under-voltage lockout, soft start circuit, and output driver collaborate seamlessly. The MOSFETs function as switches, synchronized with the oscillating signal from the KA3525A IC. This coordination, combined with the filter and other signal conditioning units, enables the conversion process. The design achieves the conversion of raw power into a stable pure sine wave signal of 170V AC at the H-bridge terminals, demonstrating the success of the designed approach.
Voltage optimization on low voltage distribution transformer zones using batteries in Uganda
(Journal of Engineering, Technology & Applied Science, 2024-03-07) Kelechi, Edema Simon Iddi; Kalyankolo, Umaru; Eze, Val Hyginus Udoka; Asikuru, Salama; Nassaga, Musa; Ochima, Noah
In the context of Uganda's rapidly growing energy demands and the need for sustainable solutions, this study explores the implementation of voltage optimization techniques in Low Voltage (LV) distribution transformer zones. The research focuses on the innovative integration of batteries to optimize voltage levels, thereby enhancing the efficiency and reliability of the electrical distribution system. By analyzing real-time data from various LV transformer zones in Uganda, this study investigates the impact of voltage fluctuations on the overall power distribution network. The research methodology involves the design and deployment of battery energy storage systems (BESS) strategically placed within LV distribution transformer zones. These BESS units are utilized to store excess energy during periods of low demand and release it during peak hours, ensuring consistent voltage levels and minimizing losses in the distribution network. The study evaluates the effectiveness of this approach through extensive simulations and on-site experiments, considering factors such as battery capacity, charging/discharging rates, and load variations. A comprehensive cost-benefit analysis is conducted to evaluate the potential financial savings and environmental impact associated with this sustainable energy solution. The findings of this research indicate significant improvements in voltage regulation, reduced system losses, and enhanced reliability in LV distribution transformer zones. Additionally, the study demonstrates the feasibility of integrating batteries into the existing infrastructure, thereby contributing to the optimization of the energy distribution system in Uganda. The outcomes of this research provide valuable insights for policymakers, utility companies, and researchers, emphasizing the importance of embracing innovative technologies to address the energy challenges faced by developing nations like Uganda.
Design and implementation of a fire detection, alarm and suppression system using programmable logic controller (PLC)
(International Journal of Academic Engineering Research (IJAER), 2023-12) Kalyankolo, Umaru; Drici, Joseph Felix Tartisious
Industrial and or domestic safety is as much important as the processes carried out in any industry/homes. This is because there is always a tendency for fires to occur due to the existence of fire hazards in industries, domestic and residential settings. Therefore, firefighting system is one of the most important systems in industries and in buildings with multiple occupancy as it protects the facilities, equipment and people against disastrous effects of fire breakouts. Fire detection, alarm and fighting system is a combination of number of devices working together to detect and warn the people through visual and audible appliances when smoke, heat and/or fire are present. It also triggers the suppression system. The alarm used in such system may be activated from flame or smoke detectors and heat detectors. In this project, smoke detectors have been used to detect fire and give an input signal to the programmable logic controller(PLC) which triggers the fire alarm and fire suppression system. Fire alarm system plays the main role in maintaining and monitoring the safety in all kinds of environments and situations. The main objective of this Fire Alarm Control System in Building Automation Using PLC is to make a fire control and suppression system with high reliability and low cost. The system has been designed to cover three zones of protection (three rooms) in which on detection of fire, zone 1 produces audible (buzzer) and visual light emitting diode(LED) alarm, while the LED, direct current (DC) water pump and a buzzer are triggered in zone 2 and a LED, buzzer and Solenoid valve are triggered for zone 3.
Mobile disinfectant spraying robot and its implementation components for virus outbreak: Case study of COVID-19
(International Journal of Artificial Intelligence, 2023-07-28) Udoka, Eze Val Hyginus; Edozie, Enerst; Musika, Davis; Twijuke, Dickens; Wantimba, Janat; Okafor, Wisdom O.; Kalyankolo, Umaru; Nafuna, Ritah; Nansukusa, Yudaya
The virus pandemic COVID-19 outbreak brought a huge pressure to the public healthcare system worldwide, especially in developing African countries like Uganda. The Educational system and institutions were put on a standstill due to no quick countermeasures to make the environment clean and safe for normal activities to continue. This paper successfully and comprehensively reviewed the Bluetooth and smart disinfectant spraying robot that successfully controlled the spread of the deadly virus. It also detailed different components that made up the complete spraying robot systems and from this it was observed that spraying robot systems are made up of almost the same components for implementations but differs on program that is embedded on the microcontroller due to different functions. This programing differs based on the functions that the designer/programmer wants the robot to do despite using almost the same components. This research review paper will act as guide for future researchers when designing and implementing a mobile spraying robot.
Cybersecurity for sustainable smart healthcare: State of the Art, taxonomy, mechanisms, and essential roles
(Mesopotamian Journal of CyberSecurity, 2024-05-23) Ali, Guma; Mijwil, Maad M.
Cutting-edge technologies have been widely employed in healthcare delivery, resulting in transformative advances and promising enhanced patient care, operational efficiency, and resource usage. However, the proliferation of networked devices and data-driven systems has created new cybersecurity threats that jeopardize the integrity, confidentiality, and availability of critical healthcare data. This review paper offers a comprehensive evaluation of the current state of cybersecurity in the context of smart healthcare, presenting a structured taxonomy of its existing cyber threats, mechanisms and essential roles. This study explored cybersecurity and smart healthcare systems (SHSs). It identified and discussed the most pressing cyber threats and attacks that SHSs face, including fake base stations, medjacking, and Sybil attacks. This study examined the security measures deployed to combat cyber threats and attacks in SHSs. These measures include cryptographic-based techniques, digital watermarking, digital steganography, and many others. Patient data protection, the prevention of data breaches, and the maintenance of SHS integrity and availability are some of the roles of cybersecurity in ensuring sustainable smart healthcare. The long-term viability of smart healthcare depends on the constant assessment of cyber risks that harm healthcare providers, patients, and professionals. This review aims to inform policymakers, healthcare practitioners, and technology stakeholders about the critical imperatives and best practices for fostering a secure and resilient smart healthcare ecosystem by synthesizing insights from multidisciplinary perspectives, such as cybersecurity, healthcare management, and sustainability research. Understanding the most recent cybersecurity measures is critical for controlling escalating cyber threats and attacks on SHSs and networks and encouraging intelligent healthcare delivery.
Innovative Livestock: A Survey of artificial intelligence techniques in livestock farming management
(Wasit Journal of Computer and Mathematics Science, 2023-12-30) Mijwil, Maad M.; Adelaja, Oluwaseun; Badr, Amr; Ali, Guma; Buruga, Bosco Apparatus; Pudasaini, Pramila
Modern technology has recently become a meaningful part of all life sectors, as software, sensors, smart machines, and expert systems are successfully integrated into the physical environment. This technology relies in its work on artificial intelligence techniques to make the right decisions at the right time. These technologies have a significant role in improving productivity, product quality, and industry outputs by significantly reducing human labour and errors that humans may cause. Artificial intelligence techniques are increasingly being integrated into animal husbandry and animal revolution management because they provide advantages and means that serve agriculturalists. These techniques monitor the emotional state of animals, milk production and herd management, feeding habits, the movement of animals, and their health status. AI-powered sensors can monitor the health of livestock and detect early signs of illness or stress to which they are exposed. Also, these techniques contribute to assisting agriculturalists in customising feeding programs, reducing waste, and improving product quality. This article will discuss the role of artificial intelligence techniques in animal control, farm management, disease surveillance, and sustainable resource optimisation practices.
Comparative analysis of PWM AC choppers with different loads with and without neural network application.
(Wasit Journal of Computer and Mathematics Science, 2023-09) Bounab, Mariem; Ali, Guma
In this paper, we focus on the "Artificial Neural Network (ANN) based PWM-AC chopper". This system is based on the PWM AC chopper-encouraged single-phase induction motor. The main purpose of this paper is to design and implement an ideal technique regarding speed control. Here analyzed PWM-based AC-AC converter with resistive load, R-L load and finally, the PWM AC chopper is fed to single phase induction for speed control. Using other soft computing and optimization techniques such as Artificial Neural Networks, Fuzzy Logic, Convolution algorithm, PSO, and Neuro Fuzzy can control the Speed. We used Artificial Neural Network to control the Speed of the PWM-AC Single phase induction motor drive. The Neural Network toolbox has been further used for getting desired responses. Neural system computer programs are executed in MATLAB. The performance of the proposed method of ANN system of PWM AC Chopper fed single phase induction motor drive is better than other traditional and base methods for controlling the Speed, based on the MOSFET.
A Comprehensive review on cybersecurity issues and their mitigation measures in FinTech
(Al-Iraqia Univeristy, 2024-06-10) Ali, Guma; Mijwil, Maad M.; Buruga, Bosco Apparatus; Abotaleb, Mostafa
The fourth industrial revolution has seen the evolution and wide adoption of game-changing and disruptive innovation, "financial technologies (FinTech), around the globe. However, the security of FinTech systems and networks remains critical. This research paper comprehensively reviews cybersecurity issues and their mitigation measures in FinTech. Four independent researchers reviewed relevant literature from IEEE Xplore, ScienceDirect, Taylor & Francis, Emerald Insight, Springer, SAGE, WILEY, Hindawi, MDPI, ACM, and Google Scholar. The key findings of the analysis identified privacy issues, data breaches, malware attacks, hacking, insider threats, identity theft, social engineering attacks, distributed denial-of-service attacks, cryptojacking, supply chain attacks, advanced persistent threats, zero-day attacks, salami attacks, man-in-the-middle attacks, SQL injection, and brute-force attacks as some of the significant cybersecurity issues experienced by the FinTech industry. The review paper also suggested authentication and access control mechanisms, cryptography, regulatory compliance, intrusion detection and prevention systems, regular data backup, basic security training, big data analytics, use of artificial intelligence and machine learning, FinTech regulatory sandboxes, cloud computing technologies, blockchain technologies, and fraud detection and prevention systems as mitigation measures for cybersecurity issues. However, tackling cybersecurity issues will be paramount if FinTech is to realize its full potential. Ultimately, this research will help develop robust security mechanisms for FinTech systems and networks to achieve sustainable financial inclusion.
Artificial intelligence in corneal topography: A short article in enhancing eye care
(Mesopotamian Journal of Artificial Intelligence in Healthcare, 2023-06-17) Ali, Guma; Eid, Marwa M.; Ahmed, Omar G.; Abotaleb, Mostafa; Alaabdin, Anas M. Zein; Buruga, Bosco Apparatus
The eye is a critical part of the human being, as it provides complete vision and the ability to receive and process visual details, and any deficiency in it may affect vision and loss of sight. Corneal topography is one of the essential diagnostic tools in the field of ophthalmology, as it can provide important information about the cornea and the problems that appear in it. Artificial intelligence strategies contribute to the development of the healthcare domain through a group of approaches that have a significant and vital impact on improving the field of ophthalmology. The primary purpose of this paper is to highlight the efficiency of artificial intelligence in extracting features from corneal topography and how these techniques contribute to helping ophthalmologists diagnose corneal topography. Furthermore, the focus is on the performance of AI algorithms, their diagnostic capabilities, and their importance in helping physicians and patients. The effects of this paper confirm the effectiveness and efficiency of artificial intelligence algorithms in the clinical diagnosis of various eye concerns.
Design a hybrid approach for the classification and recognition of traffic signs using machine learning
(Wasit Journal of Computer and Mathematics Science, 2023-07) Ali, Guma; Sadıkoğlu, Emre; Abdelhak, Hatim
Advanced Driver Assistance Systems (ADAS) are a fundamental part of various vehicles, and the automatic classification of traffic signs is a crucial component. A traffic image is classified based on its recognizable features. Traffic signs are designed with specific shapes and colours, along with text and symbols that are highly contrasted with their surroundings. This paper proposes a hybrid approach for classifying traffic signs by combining SIFT with SVM for training and classification. There are four phases to the proposed work: pre-processing, feature extraction, training, and classification. A real traffic sign image is used for classification in the proposed framework, and MATLAB is used to implement the framework
The evolving role of artificial intelligence in the future of distance learning: Exploring the next frontier
(Mesopotamian Journal of Computer Science, 2023-05-17) Mijwil, Maad M.; Ali, Guma; Sadıkoğlu, Emre
In recent years, education has become especially related to the applications provided by artificial intelligence technology through a digital environment that includes a set of tools that assist in processing and storing information. Artificial intelligence techniques contribute to the development of students' skills by providing them with advanced scientific content and building their mental capabilities faster. Moreover, these techniques support analysing student data and suggest suitable educational materials and activities for them. Artificial intelligence is a noteworthy tool for the growth of distance education, especially after the development of expert systems that have become a human advisor in many domains, as this leads to the development of education systems that adjust the level of difficulty of materials based on the student’s performance in the electronic classroom, which ensures that the student continues in education and is not frustrated. This article will review the influential role of artificial intelligence applications in growing distance learning, improving the quality of education, and making it an adaptable and practical environment for students.
Analysing the connection between ai and industry 4.0 from a cybersecurity perspective: defending the smart revolution
(Mesopotamian Journal of Big Data, 2023-05-05) Bala, Indu; Mijwil, Maad M.; Ali, Guma; Sadıkoğlu, Emre
In recent years, the significance and efficiency of business performance have become dependent heavily on digitization, as jobs in companies are seeking to be transformed into digital jobs based on smart systems and applications of the fourth industrial revolution. Cybersecurity systems must interact and continuously cooperate with authorized users through the Internet of Things and benefit from corporate services that allow users to interact in a secure environment free from electronic attacks. Artificial intelligence methods contribute to the design of the Fourth Industrial Revolution principles, including interoperability, information transparency, technical assistance, and decentralized decisions. Through this design, security gaps may be generated that attackers can exploit in order to be able to enter systems, control them, or manipulate them. In this paper, the role of automated systems for digital operations in the fourth industrial revolution era will be examined from the perspective of artificial intelligence and cybersecurity, as well as the most significant practices of artificial intelligence methods. This paper concluded that artificial intelligence methods play a significant role in defending and protecting cybersecurity and the Internet of Things, preventing electronic attacks, and protecting users' privacy.
Artificial intelligence solutions for health 4.0: overcoming challenges and surveying applications
(Mesopotamian Journal of Artificial Intelligence in Healthcare, 2023-03-10) Al-Mistarehi, Abdel-Hameed; Mijwil, Maad M.; Filali, Youssef; Bounabi, Mariem; Ali, Guma; Abotaleb, Mostafa
In recent years, the term Health 4.0 has appeared in health services and is related to the concept of Industry 4.0. The term Health 4.0 focuses on replacing traditional care in hospitals and medical clinics with home health services that are based on artificial intelligence techniques through the use of telemedicine applications that allow the monitoring of patients in a virtual environment. This term is utilized to represent digital change in the healthcare sector. Governments aim to develop the level of medical care in hospitals and clinics to ensure the provision of healthcare benefits at low costs and increase patient satisfaction. It has become vital for hospitals to grow their environment into digital environments in their services through the use of a set of computer programs based on artificial intelligence. Artificial intelligence techniques in Health 4.0 provide a set of procedures that benefit patients and healthcare workers, including early diagnosis, make inquiries into treatment, data analysis, reports on the patient's condition, and others. The primary purpose of this article is to determine the significance of Health 4.0 and AI techniques in healthcare by mentioning the most important benefits and weaknesses of using AI techniques in healthcare.
Overview of renewable energy power generation and conversion (2015-2023)
(Eurasian Experiment Journal Of Engineering, 2023) Eze, Val Hyginus Udoka; Edozie, Enerst; Kalyankolo, Umaru; Okafor, O. Wisdom; Ugwu, Chinyere N; Ogenyi, Fabian Chukwudi
This paper successfully reviewed the renewable energy trend from 2015 to 2023 based on investment, power conversion and future prospect. From the review it was observed that solar energy is progressively taking the lead as the cleanest energy generator followed by the wind turbine since 2019-2023. It also detailed the overview of solar photovoltaic technologies, photovoltaic conversion Efficiency Enhancement and the solar photovoltaic generations which showed that China is the most invested country in renewable energy followed by European union. From this paper it was clear that the renewable energy research trend has shifted to third generation solar photovoltaic (perovskites) and power conversion efficiency enhancement (Maximum Power Point Tracking). Perovskites as the third generational solar cell gives the best energy conversion due to its absorption coefficient, exceptional carrier mobility, high dielectric constant, tunable bandgap, materials abundance and as such recommended for solar installers and other PV designer.
The differences between single diode model and double diode models of a solar photovoltaic cells: systematic review
(Journal of Engineering, Technology & Applied Science, 2023-08-21) Eze, Val Hyginus Udoka; Kalyankolo, Umaru; Edozie, Enerst; Nafuna, Ritah; Nansukusa, Yudaya
This research paper systematically reviewed and investigated single diode model and double diode model of a solar photovoltaic systems in terms of accuracy, differences under major unknown PV parameters, different optimization and fabrication. This research paper reviewed the differences and the similarities between the single diode model and double diode model. From the review, it was clear that single diode model has less computation time and number of unknown parameters compared to double diode model. The double diode model on its own superiority is more accurate under solar shading condition effect than single diode model but single diode model performs better under high insolation levels. None of the two models is superior than the other but the solar photovoltaic modelers/installers should bear the solar irradiance of the environment before installation.
Reviewing the pertinence of Sentinel-1 SAR for urban land use land cover classification
(International Journal of Scientific & Engineering Research, 2020-05) Abudu, Dan; Parvin, Nigar Sultana; Andogah, Geoffrey
Conventional approaches for urban land use land cover classification and quantification of land use changes have often relied on the ground surveys and urban censuses of urban surface properties. Advent of Remote Sensing technology supporting metric to centimetric spatial resolutions with simultaneous wide coverage, significantly reduced huge operational costs previously encountered using ground surveys. Weather, sensor’s spatial resolution and the complex compositions of urban areas comprising concrete, metallic, water, bare- and vegetation-covers, limits Remote Sensing ability to accurately discriminate urban features. The launch of Sentinel-1 Synthetic Aperture Radar, which operates at metric resolution and microwave frequencies evades the weather limitations and has been reported to accurately quantify urban compositions. This paper assessed the feasibility of Sentinel-1 SAR data for urban land use land cover classification by reviewing research papers that utilised these data. The review found that since 2014, 11 studies have specifically utilised the datasets. The reviewed studies demonstrated that, features representing urban topography such as morphology and texture can easily and accurately be extracted from Sentinel-1 SAR and subjected to state-of-the-art classification algorithms such as Support Vector Machine and ensemble Decision Trees for accurate urban land use land cover classification. Development of robust algorithms to deal with the complexities of SAR imagery is still an active research area. Furthermore, augmentation of SAR with optical imagery is required especially for classification accuracy assessments.

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