Research Publications (Engineering and Built Environment)
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Item A taxonomy on smart healthcare technologies : security framework, case study, and future directions(Hindawi Limited, 2022-07-05) Chaudhary, Sachi; Kakkar, Riya; Jadav, Nilesh Kumar; Nair, Anuja; Gupta, Rajesh; Tanwar, Sudeep; Agrawal, Smita; Alshehri, Mohammad Dahman; Sharma, Ravi; Sharma, Gulshan; Davidson, Innocent E.There is a massive transformation in the traditional healthcare system from the specialist-centric approach to the patient-centric approach by adopting modern and intelligent healthcare solutions to build a smart healthcare system. It permits patients to directly share their medical data with the specialist for remote diagnosis without any human intervention. Furthermore, the remote monitoring of patients utilizing wearable sensors, Internet of Things (IoT) technologies, and artificial intelligence (AI) has made the treatment readily accessible and affordable. However, the advancement also brings several security and privacy concerns that poorly maneuvered the effective performance of the smart healthcare system. An attacker can exploit the IoT infrastructure, perform an adversarial attack on AI models, and proliferate resource starvation attacks in smart healthcare system. To overcome the aforementioned issues, in this survey, we extensively reviewed and created a comprehensive taxonomy of various smart healthcare technologies such as wearable devices, digital healthcare, and body area networks (BANs), along with their security aspects and solutions for the smart healthcare system. Moreover, we propose an AI-based architecture with the 6G network interface to secure the data exchange between patients and medical practitioners. We have examined our proposed architecture with the case study based on the COVID-19 pandemic by adopting unmanned aerial vehicles (UAVs) for data exchange. The performance of the proposed architecture is evaluated using various machine learning (ML) classification algorithms such as random forest (RF), naive Bayes (NB), logistic regression (LR), linear discriminant analysis (LDA), and perceptron. The RF classification algorithm outperforms the conventional algorithms in terms of accuracy, i.e., 98%. Finally, we present open issues and research challenges associated with smart healthcare technologiesItem Contactless palmprint recognition system : a survey(Institute of Electrical and Electronics Engineers (IEEE), 2022) Alausa, Dele W.S.; Adetiba, Emmanuel; Badejo, Joke A.; Davidson, Innocent E.; Obiyemi, Obiseye; Buraimoh, Elutunji; Abayomi, Abdultaofeek; Oshin, OluwadamilolaT Information systems in organizations traditionally require users to remember their secret pins (password), token, card number, or both to confirm their identities. However, the technological trend has been moving towards personal identification based on individual behavioural attributes (such as gaits, signature, and voice) or physiological (such as palmprint, fingerprint, face, iris, or ear). These attributes (biometrics) offer many advantages over knowledge and possession-based approaches. For example, palmprint images have rich, unique features for reliable human identification, and it has received significant attention due to their stability, reliability, uniqueness, and non-intrusiveness. This paper provides an overview and evaluation of contactless palmprint recognition system, the state-of-the-art performance of existing works, different types of "Region of Interest" (ROI) extraction algorithms, feature extraction, and matching algorithms. Finally, the findings obtained are presented and discussedItem Fusion in cryptocurrency price prediction: a decade survey on recent advancements, architecture, and potential future directions(Institute of Electrical and Electronics Engineers (IEEE), 2022) Patel, Nisarg P.; Parekh, Raj; Thakkar, Nihar; Gupta, Rajesh; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviCryptographic forms of money are distributed peer-to-peer (P2P) computerized exchange mediums, where the exchanges or records are secured through a protected hash set of secure hash algorithm-256 (SHA-256) and message digest 5 (MD5) calculations. Since their initiation, the prices seem highly volatile and came to their amazing cutoff points during the COVID-19 pandemic. This factor makes them a popular choice for investors with an aim to get higher returns over a short span of time. The colossal high points and low points in digital forms of money costs have drawn in analysts from the scholarly community as well as ventures to foresee their costs. A few machines and deep learning algorithms like gated recurrent unit (GRU), long short-term memory (LSTM), autoregressive integrated moving average with explanatory variable (ARIMAX), and a lot more have been utilized to exactly predict and investigate the elements influencing cryptocurrency prices. The current literature is totally centered around the forecast of digital money costs disregarding its reliance on other cryptographic forms of money. However, Dash coin is an individual cryptocurrency, but it is derived from Bitcoin and Litecoin. The change in Bitcoin and Litecoin prices affects the Dash coin price. Motivated from these, we present a cryptocurrency price prediction framework in this paper. It acknowledges different cryptographic forms of money (which are subject to one another) as information and yields higher accuracy. To illustrate this concept, we have considered a price prediction of Dash coin through the past days’ prices of Dash, Litecoin, and Bitcoin as they have hierarchical dependency among them at the protocol level. We can portray the outcomes that the proposed scheme predicts the prices with low misfortune and high precision. The model can be applied to different digital money cost expectations.Item Analysis of voltage rise phenomena in electrical power network with high concentration of renewable distributed generations(Springer Science and Business Media LLC, 2022-12) Akinyemi, Ayodeji Stephen; Musasa, Kabeya; Davidson, Innocent E.The increasing penetration levels of renewable distributed generation (RDG) into a power system have proven to bring both positive and negative impacts. The occurrence of under voltage at the far end of a conventional electrical distribution network (DN) may not raise concern anymore with RDGs integration into a power system. However, a penetration of RDGs into power system may cause problems such as voltage rise or over-voltage and reverse power flows at the Point of Common Coupling (PCC) between RDG and DN. This research paper presents the impact of voltage rise effect and reverse power flow constraint in power system with high concentration of RDG. The analysis is conducted on a sample DN, i.e., IEEE 13-bus test system, with RDG penetration by considering the most critical scenario such as low power demand in DN and a peak power injection by RDG. For studying the impact of voltage rise and reverse power flow, a mathematical model of a DN integrating RDG is developed. Furthermore, a controller incorporating an advance control-algorithm is proposed to be installed at PCC between DN and RDG to regulate the voltage rise effects and to mitigate the reverse power flow when operating at a worst critical scenario of minimum load and maximum generation from RDG. The proposed control strategy also mitigates the voltage–current harmonic distortions, improves the power factor, and maintain the voltage stability at PCC. The simulations are carried out using MATLAB/Simulink software. Finally, recommendations are provided for the power producers to counteract the effects of voltage rise at PCC. The study has demonstrated that, voltage at PCC can be sustained with a high concentration of RDG during a worst-case scenario without a reverse power flow and voltage rise beyond grid code limits.Item Modeling of double stage photovoltaic inverter system with fast delayed signal cancellation for fault ride-through control application in microgrids(MDPI AG, 2022-02) Buraimoh, Elutunji; Davidson, Innocent E.This research presents a secondary control for a grid-supporting microgrid with photovoltaics sources to guarantee grid code compliance and ancillary services. The secondary control accomplishes the fault ride-through, which implements a delayed signal cancellation (DSC) algorithm for negative sequence detection. Without mode switching, the proposed control strategy meets grid code requirements and ensures voltage regulation at the secondary level, which is active and more salient throughout the transient period of host grid disturbances. This control also ensures a constant supply of the microgrid’s sensitive local load while adhering to grid code requirements. Similarly, active power injection into the main grid is limited by progressively altering the MPPT operating point dependent on the depth of voltage sag to optimize reactive power injection to sustain grid voltage sag. The recommended secondary control is triggered by utilizing the DSC process’s detection algorithm to identify the occurrence of a fault in a tiny fraction of a half-cycle in a grid fault. Consequently, while satisfying microgrid load needs, the devised technique guaranteed that increases in DC-link voltage and AC grid current were controlled. MATLAB Simscape ElectricalTM and OPAL-RT Lab are used to do time-domain simulations of the model using the recommended secondary control systems.Item Solar irradiation forecasting for the city of Durban using time series analysis(IEEE, 2022-01-25) Ntlela, Simphiwe A.; Davidson, Innocent E.As a result of the country's rich solar resources, local and international investors have grown interested in the solar energy industry. The country has sufficient renewable energy resources that can be exploited to generate electricity. Solar power has exposed achievement in the area of electric power generation. The fuel that powers solar energy is Light from the sun and solar radiation. As a substitute for fossil fuel-based energy, renewable energy plays a vital role in developing countries such as those in Africa, Asia, and Latin America. Published publications related to this topic often use mathematical models to model the solar resources instead of measurements. The most preferable data is measured since the effects of weather and pollution are included. The commissioning of regional networks for monitoring solar stations in southern Africa has established a unique source for sun strength measurements in Southern Africa. This study presents sun strength measurements from the solar station in southern Africa Universities Radiometric Network (SAURAN) is compared with NASA data.Item Seasonal variation of soil resistivity and corrective factor for optimal substation earth grid design in Eastern Cape(IEEE, 2022-01-25) Madikizela, Andile; Kabeya, Musasa; Davidson, Innocent E.Optimal Substation Earth Grid Design is a vital aspect of the electrical power system protection. The Seasonal Variation of Soil Resistivity mostly influences Earth Grid Design. Due to seasonal changes, there is an annual variation in the Soil Resistivity with no known correction factors that can be utilized. This has led to a need to ascertain annual 'Seasonal Soil Resistivity Correction Factors' for utility application. The objective of this paper is to develop seasonal Soil Resistivity Correction Factors for Optimal Substation Earth Grid Design in a power distribution substation focusing on meeting the minimum safety requirements, which are the step and touch potentials. A case study site was used for this study in the Eastern Cape region based on a study carried out in the Gauteng province. Results obtained show that in winter, (June/July), the highest soil resistivity was reached and lowest value obtained in autumn season (March). The upper soil layer resistivity noticeably varies more than the lower layer. The corrective factors for the upper layer with probe spacing (0.5m-1m) is multiplied by 1.16; for the second upper layer probe spacing from (2m-5m) is multiplied by 1.02; while the lower layer with probe spacing (5m-50m) is multiplied by 1.01. The corrective factors are focused on July, which is the highest, for an Optimal Substation Earth Grid Design.Item Power planning for a smart integrated African super-grid(IEEE, 2022-01-25) Ndlela, Nomihla Wandile; Davidson, Innocent E.Africa's population has increased sharply from 364 million in 1970 to 1.3 billion in 2020 and is expected to reach 2.0 billion by 2050, representing the world's largest labor pool. Rapid growth in African population, generation capacity constraints, belated investment in new electricity infrastructure, load growth in unplanned areas, poor maintenance of existing power assets are some of Africa's critical challenges. These have resulted in demand outstripping available power generation capacity, leading to electricity shortages, load shedding, a huge backlog of unserved customers, and low economic growth. This paper presents the concept of a Smart Integrated African Super Grid, designed to energize Africa's emerging economy. In this paper, the five African Power pools are discussed, and the schemes for harnessing Africa's untapped renewable energy resources. A methodology is proposed to use highly complex power system controllers to integrate the African power pools, into a super-grid that absorbs large penetration of renewable powers using dispersed interconnected low voltage micro-grids, without compromising on power quality, stability, technical loss reduction, sustainability, and system reliability.Item Coalition games for performance evaluation in 5G and beyond networks : a survey(Institute of Electrical and Electronics Engineers (IEEE), 2022) Singh, Upendra; Ramaswamy, Aditya; Dua, Amit; Kumar, Neeraj; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviThe 5G network is an emerging field of the research community. 5G is a multi-disciplinary network that aims to support a wide range of services. 5G network has an objective to support a massive number of connected devices. Game theory has an extensive role in wireless network management. Game theory is an approach to analyzing and modeling the system where multiple actors have a role in decisionmaking with independent objectives and actions. The game theory is an exciting methodology to control the strategic behavior of players and generate an efficient outcome. Coalition game theory can play a crucial role in ensuring cooperation among a massive number of devices. This article provides insight into the current research trends in 5G using coalition games. The work presented in the survey is divided into three categories, namely resource management, interference management, and miscellaneous. This article also provides the foundation about 5G and coalition games highlight the scope of future research.