Computer Engineering

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Computer Engineering

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A Hybrid Web Caching Design Model for Internet-Content Delivery
(Covenant Journal, 2016) Alfa, A. A., Ogwueleka, F. N., Dogo, E. M., & Sanjay, M.
The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture for Internet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network) inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamaisystem as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, and enhanced network security.
A Sensor-Based Data Acquisition System for Soil Parameters to Determine Suitable Crops
(2023) Abisoye, B. O.; Dogo, E. M.; Umar, B. U.; Mamman, I. Z.
Soil parameters monitoring is significant in sustainable crop and food production. The standard strategy of soil parameters monitoring in developing and underdeveloped nations uses manual labor, resulting in wrong decisions in soil management. Inaccurate measurements due to sensor miscalibration or low sensor quality can lead to incorrect soil management decisions and negatively impact crop yield and environmental sustainability. Due to the mentioned challenges, this work aims to develop a Sensor-based Data Acquisition System for Soil Parameters that will enable users to observe various soil parameters like temperature, humidity, water level and soil pH. The system was developed using the combination of hardware and software components. The hardware component comprises of sensory and processing parts. The study calibrates sensors using known pH, moisture, and temperature values for specific crops to grow in Nigeria. The system will aid farmers in determining suitable crops for their farmland and increasing crop yield. The system collects data through a network of sensors installed in the soil and wirelessly transmits the data to a cloud-based server. The collected data is then analyzed and visualized in through a web-based dashboard, providing farmers with information about the state of their soil. The performance evaluation of the system was carried out using response time and accuracy. The average response time of the system was 4 seconds, and the percentage error for temperature and humidity readings when compared to weather forecast readings were 8.20% and 5.08%, respectively. The results show that the proposed system can provide accurate and reliable measurements of soil parameters and can be easily deployed and operated by small-scale farmers. Using this system can result in improved crop yields, reduced wastage, and better overall efficiency in agricultural operations.
An Intelligent Financial Fraud Indication System Using Fuzzy Logic
(African Journal of Computing & ICT, 2014-06-22) Maliki, D., Aibinu, A. M., & Olaniyi, O. M
The issue of financial fraud is taking different dimensions in various countries due to rise in fraud enabling factors emanating from internal and external challenges. The internal challenges from unemployment rate depend on overpopulation, poor standard of living and nature of existing leadership of government. Recent advancement in modern technology and increase in tourist activities have contributed to the existing external challenges. In this paper, an intelligent financial fraud indication system using fuzzy logic is proposed, which involves the use of fuzzy arithmetic, fuzzy degree of association, fuzzy inference, fuzzy rules and different surface plot in determination of different relationship as it relate to certain choice of inputs. The selected input indices were meant to determine how certain degree of changes in inputs can affect the nature of fraud indication. The proposed system also depends on fraud enabling factors in the determination of appropriate fraud indication level. From the results obtained, it is shown that people from areas with high population, high political activities and high education are likely to be engaged in more financial fraud compare to an area in which population, political activities and education are low
Automatic Photovoltaic Solar Panel Dust Cleaning System
(IGI Global, 2021) Shibane, N.; Nwulu, N.; Dogo, E. M.
Renewable energy sources are currently regarded as viable options for stabilizing the energy crisis globally as well as addressing global warming challenges. Solar energy is the most promising and sustainable energy source as compared to other renewable energy sources such as coal, nuclear, wind, gas, and hydro energy. The increasing demand for solar panels should be reason enough to investigate ways in which we can increase their efficiency as much as possible. Dust, dirt, and bird dropping are major factors that can affect the performance of solar panel systems. This work presents the development of a solar panel cleaning system that automatically detects dust particles and cleans the solar panel to ensure the continues efficiency of the solar system is at an optimal level. The system comprises of five subsystems: dust sensing, water pumping, microcontroller, cleaning mechanism, and the power system. Tests carried out on the system shows its quick response to signals and effectiveness in cleaning the solar panel whenever dust particles are detected.
Blockchain and Internet of Things-Based Technologies for Intelligent Water Management System
(Springer, 2019) Dogo, E.M., Salami, A.F., Nwulu, N.I., Aigbavboa, C.O.
Water is a critical and indispensable resource for the sustainability of life, economic development, and the environment. According to the United Nations (UN) estimates, 70% of the world’s population will live in cities by the year 2025, and the current centralized piped infrastructure relied upon by water utilities will be inadequate. Leveraging on the advancement in emerging blockchain, Internet of Things (IoT), and sensor technologies offers a means for efficient water management. In this era of Fourth Industrial Revolution (4IR), human creativity will be a critical requirement in this regard. This chapter explores the impact of blockchain and IoT on water management and examines the feasibility of its adoption in multiple case scenarios and instances such as stormwater management, water quality monitoring and reporting directly to consumers and other relevant stakeholders, and smart payment and contract, in order to sustainably deal with the challenges of global water crisis induced by climate change and rapid population growth. This chapter makes special and unique emphasis on the relevance of the research through an African perspective and view. Furthermore, the technical advantages, socioeconomic gains, and technological benefits of synergizing blockchain and IoT such as enhanced security and transparency, reduced operational cost, overall efficiency, and other merits are expatiated.
Blockchain for securing electronic voting systems: a survey of architectures, trends, solutions, and challenges
(Springer, 2025) Ohize, H. O.; Onumanyi, A. J.; Umar, B. U.; Ajao, L. A.; Isah, R. O.; Dogo, E. M.; Nuhu, B. K.; Olaniyi, O. M.; Ambafi, J. G.; Sheidu, V. B.; Ibrahim, M. M.
Electronic voting (e-voting) systems are gaining increasing attention as a means to modernize electoral processes, enhance transparency, and boost voters’ participation. In recent years, significant developments have occurred in the study of e-voting and blockchain technology systems, hence reshaping many electoral systems globally. For example, real-world implementations of blockchain-based e-voting have been explored in various countries, such as Estonia and Switzerland, which demonstrates the potential of blockchain to enhance the security and transparency of elections. Thus, in this paper, we present a survey of the latest trends in the development of e-voting systems, focusing on the integration of blockchain technology as a promising solution to address various concerns in e-voting, including security, transparency, auditability, and voting integrity. This survey is important because existing survey articles do not cover the latest advancements in blockchain technology for e-voting, particularly as it relates to architecture, global trends, and current concerns in the developmental process. Thus, we address this gap by providing an encompassing overview of architectures, developments, concerns, and solutions in e-voting systems based on the use of blockchain technology. Specifically, a concise summary of the information necessary for implementing blockchain-based e-voting solutions is provided. Furthermore, we discuss recent advances in blockchain systems, which aim to enhance scalability and performance in large-scale voting scenarios. We also highlight the fact that the implementation of blockchain-based e-voting systems faces challenges, including cybersecurity risks, resource intensity, and the need for robust infrastructure, which must be addressed to ensure the scalability and reliability of these systems. This survey also points to the ongoing development in the field, highlighting future research directions such as improving the efficiency of blockchain algorithms and integrating advanced cryptographic techniques to further enhance security and trust in e-voting systems. Hence, by analyzing the current state of e-voting systems and blockchain technology, insights have been provided into the opportunities and challenges in the field with opportunities for future research and development efforts aimed at creating more secure, transparent, and inclusive electoral processes.
Combating Road Traffic Congestion with Big Data: A Bibliometric Review and Analysis of Scientific Research
(Springer, 2021) Dogo, E.M.; Makaba, T.; Afolabi, O.J.; Ajibo, A.C.
Road traffic congestion is one of the challenging problems confronting city dwellers globally. It is majorly caused by either one or a combination of recurrent congestion, nonrecurrent congestion, and pre congestion conditions in urban road networks. This chapter performs a bibliometric analysis and reviews the volume of literature linking big data with combating road traffic congestion between 2011 and 2020. The review employs a quantitative analysis of bibliometric science mapping tool to highlight features that affect knowledge accumulation. The chapter also reviews the intellectual structure of knowledge based on total publications and citations. The key scholars, documents, affiliations, regions, data, and algorithms that influenced the development of this research area are analyzed. The results of documents co-citation evaluation show that the key research clusters are salient elements linked with the development and deployment of connected and autonomous vehicles (CAVs) technology. These research clusters are traffic flow prediction, congestion and accidents alert systems, security and privacy mitigation, vehicle emission profiles, travel time estimation, optimization of vehicular routing, journey planning and congestion prediction, and travel and parking guidance. Finally, the chapter presents the way forward and future research direction for sustainable road traffic management in the context of smart city initiatives leveraging on big data.
Development and Implementation of Microcontroller-based Improved Digital Timer and Alarm System
(Federal University of Technology Minna, 2016-05-06) Ajao, L. A., Adegboye, M. A., Dogo, E. M., Aliyu, S. O., & Maliki, D
Time plays an important role in our daily activities, more particularly in sectional events or conference arena where there is need for accurate time management. This paper focuses on the development and implementation of an improved digital timer with audio-visual unit using (PIC16F887) microcontroller chip and other electronics component such as LCD, 7-segment display, LED and buzzer as an I/O device. Thus, the need for this device in our daily activities is to monitor the time scheduled for events, updating and alert the audience using an audio-visual approach. The proposed system allows apt time management and avoids time wastage during seminar presentations and the likes. It particularly helps presenters to be time conscious, thus, making them to naturally adjust such that the allotted time is enough to cover up their presentation. The digital timer and alarm system presented herewith is also of advantage to the physically challenged like the deaf and blind in monitoring their sectional activities and to be fully involved about the event situation. The system was designed in different modules, and all were interfaced together with firmware chip to simplify the mechanism’s fault diagnoses and fault corrections.
Development of an Intelligent Aquaculture Control System for Fish Farm”, Journal of Science Technology Mathematics and Education (JOSTMED)
(Journal of Science Technology Mathematics and Education (JOSTMED), 2017-06-17) Maliki, D., Lawrence, C., Nuhu B. K., Abdullahi I. M., & Umar, B. U.
Fish farming has become an important practice worldwide and it has been existence for many years. The growing and cultivation of fish which is an important branch of agriculture has served as a source of protein, vitamin and oil for mankind. Manual method of feeding at any choice of tie and inadequate water level monitoring device has been identified to be a limitation affecting the survival of fish in the pond. To this extend, there is a need to constantly monitor water level in the pond due to the fact that water can be lost as a result of seepage and inadequate watershed area which also interferes with fish movement to see and capture prey. In this research, an intelligent aquaculture control system using a fuzzy logic approach has been developed. The developed system is capable of providing feed to fishes at a selected time interval and also detecting and maintaining the level of water in the fish pond by pumping water if the need arises. The overall system performance was achieved base don the system response from generated rules of the fuzzy logic system. This research can further be improved by using the internet and data transmission system for further analysis and remote monitoring of the fish pond.
Development of an Intelligent Evaporative Cooling System for Post-harvest Storage of Tomato
(University of Ilorin, Nigeria, 2024-06-04) Isah, O.R., Adebayo S.E., Nuhu, B.K., Umar, B.U., Maliki, D., Abdullahi, I.M., Dogo, E.M, Olaniyi, O.M., & Agajo, James
This research developed an intelligent evaporative cooling system for post-harvest tomato preservation that adapts to its suitable temperature, humidity, and CO 2 states to store, preserve quality, and increase the shelf life of the fruits. This was accomplished through the use of transfer learning for fruit classification, the Internet of Things (IoT) for remote monitoring and shelf life tracking, and the integration of the evaporative cooling system with a CO 2 sensor, a temperature sensor, a humidity sensor, an Arduino Uno, and a Raspberry Pi 4b. The system can classify tomato fruit status as ripe or overripe with a prediction accuracy of 87.5% and a receiver operating characteristic (ROC) value of 88.89%. The developed evaporative cooling system extended the shelf life of ripe tomatoes from 5 to 14-17 days at 20℃ and 90% relative humidity and overripe tomatoes from 3 to 9-11 days at 18℃ and 95% relative humidity. These results emphasize the crucial function of evaporative cooling in fruit and vegetable storage, as it extends the shelf life of tomatoes by 180–200%, hence minimizing post-harvest loss as it also increases the farmers’ income, thereby contributing positively to the economy.
Development of Animal Health Monitoring System based on Wireless Sensor Network
(Journal of Contents Computing, 2022-12-10) Maliki, D., Ogunbase, E. F., Abdullahi, I. M., Aliyu, I., Oh, S., & Dauda, I. A
Clinical methods for tracking animal health are inadequate as they only include intermittent data which entail too much time and veterinarian knowledge expenditure in equipment. The animal health monitoring system which allocates equipment to be installed on the animal body does provide way of keeping the health of the animal in check. This project seeks to solve the problem of integration in system developed. Also, monitoring of psychological parameters has to be consistent (precision), accuracy and the response time of the system has to be low for a real time monitoring system. The project seeks to achieve a level of accuracy and precision to help diagnose the health situation of the animal. The system consists of two sensors (a temperature sensor, a heart rate sensor). For the implementation of the temperature node, esp 32 which has wifi capability was used while in the case of heart rate, Arduino Nano was interfaced alongside with esp32. The sensor nodes communicate with the sink node which serves as the display unit and also transmit the data to the cloud for real time monitoring. The precision and accuracy achieved by the ECG, modularity built into the system and the deep sleep energy-saving mechanism of the sensor nodes are achievement made by this work.
Enhanced Adaptive Threshold Median Filter For Medical Image Filtering
(OURNAL OF SCIENCE TECHNOLOGY AND EDUCATION, 2023-06-12) Adamu, M., Jiro, A.A., Abdul-Malik, U. T
In the field of medical image processing, mitigating the impact of noise is of paramount importance. Conventional median filters primarily target the elimination of medical image noise occurring as a single layer, characterized by a constant level of noise gray value. However, these filters encounter challenges when faced with images corrupted by noise that extends beyond a single layer. This study presents the Enhanced Adaptive Threshold Median Filter (EATMF) as a solution to naddress the aforementioned challenge. The proposed filter combines the Adaptive Median Filter (AMF) with thresholds (ATMF) and incorporates a Laplacian filter. By introducing changes in the thresholds, the EATMF achieves a balance between effectively removing both low and high density noise while preserving image quality. A comparative analysis between the EATMF and the ATMF is presented, accompanied by visual examples that showcase the performance of the newly introduced filter. The results demonstrate that the EATMF outperforms the ATMF in terms of Peak Signal-to-Noise Ratio (PSNR), indicating its superior noise reduction capabilities. This study highlights the significance of the EATMF in medical image processing, particularly in scenarios where images are corrupted by multi-layer noise. The proposed filter offers an enhanced approach to noise reduction, contributing to improved image quality and accuracy in medical diagnostics and analysis.
Food Safety 4.0: The Future of Food Safety Leveraging Industry 4.0 Technologies
(Springer, 2024) Dogo, E. M.; Bokaba, T.; Makun, H. A.; Aliyu, A.; Kparbong, P. B.
The convergence of several factors, including population growth, scarce natural resources, climate change, globalization, sustainability, and advances in modern and emerging technologies, in addition to growing demand by consumers, retailers, regulators, and stakeholders to raise the level of food protection is increasingly driving the global food safety agenda. Industry 4.0 technologies are fast infusing into all fields of human endeavor including the food safety ecosystem, serving as catalysts for innovation and sustainability. However, there is no empirical evidence regarding the extent of their application and the level of acceptance within the food safety domain. This study explored the relationship between Industry 4.0 technologies and food safety by evaluating the applications of the Fourth Industrial Revolution technologies in addressing food safety challenges. The objectives are achieved using qualitative methodology and bibliometric analysis of content. Our analysis indicates that artificial intelligence, the Internet of Things, machine learning, and big data are prominent topics related to the 4IR and food safety, while blockchain and smart manufacturing are emerging topics.
Mathematical Modeling of an Intelligent Poultry Feed Dispensing System
(The AIMS Research Publications, 2017) Ameh, C. A., Olaniyi, O. M., Dogo, E. M., Usman, A., Aliyu, S., Alkali, B.
The mathematical modeling of control systems and other industrial applications has helped to shape the design and performance of different systems. One of the problems faced by existing designs of poultry feed dispensing system in the tropics is feed wastage often resulting in high cost of production. Several measures that can be used to evaluate the performance of poultry flock especially broilers are growth rate, days to market, mortality, and feed efficiency. Feed is typically the most costly expense in broiler production. As a result, feed efficiency is typically the primary tool by which a flock is evaluated. This research mathematically model an intelligent poultry feed dispensing system that will dispense both solid and liquid feed which will reduce the unusual level of human involvement, feed wastage, contamination and high cost of production. The mathematical model encompasses the speed control of a DC motor which will regulate the to and fro motion of the conveyor brushes and control the flow of the solid feed. The control of the digital valves regulates the flow rate of the liquid feed in and out of the dispensing system. The mathematical model was simulated in MATLAB r2015b environment. The simulated results showed that the system under state-space is controllable and observable when the Kalman matrix test was carried out. At the end, a dynamic model for optimized balance among better yield, returns on investment and cost of operation in dispensing poultry feed was developed.
Modification of Bacterial Foraging Optimization Algorithm Using Elite Opposition Strategy
(IEEE Nigeria Computer Chapter, 2019-05-06) Maliki, D., Muazu, M.B., Olaniyi, O. M., & Kolo, J.G. (2019)
This research work presents the modification of Bacterial Foraging Optimization Algorithm (BFOA) using the elite opposition strategy. The BFOA uses a random search strategy which affect it convergence performance due poor diversification in the search process and the possibility of Oscillatory behaviour towards the search process. The Elite Opposition BFOA is developed to provide more search space so as to enhance more exploitation. The Elite Opposition BFOA (EOBFOA) and the BFOA have been tested using twelve standard benchmark functions (Unimodal and Multimodal benchmark functions). From the simulation result obtained, the EOBFOA outperform BFOA by obtaining better global minimum solution.
On the Relative Impact of Optimizers on Convolutional Neural Networks with Varying Depth and Width for Image Classification
(MDPI, 2022) Dogo, E. M.; Afolabi, O. J.; Twala, B.
The continued increase in computing resources is one key factor that is allowing deep learning researchers to scale, design and train new and complex convolutional neural network (CNN) architectures in terms of varying width, depth, or both width and depth to improve performance for a variety of problems. The contributions of this study include an uncovering of how different optimization algorithms impact CNN architectural setups with variations in width, depth, and both width/depth. Specifically in this study, three different CNN architectural setups in combination with nine different optimization algorithms—namely SGD vanilla, with momentum, and with Nesterov momentum, RMSProp, ADAM, ADAGrad, ADADelta, ADAMax, and NADAM—are trained and evaluated using three publicly available benchmark image classification datasets. Through extensive experimentation, we analyze the output predictions of the different optimizers with the CNN architectures using accuracy, convergence speed, and loss function as performance metrics. Findings based on the overall results obtained across the three image classification datasets show that ADAM and NADAM achieved superior performances with wider and deeper/wider setups, respectively, while ADADelta was the worst performer, especially with the deeper CNN architectural setup.
Paillier Cryptosystem Based ChainNode for Secure Electronic Voting
(Frontiers in Blockchain, 2022) Umar, B,U.; Olaniyi, O.M.; Olajide, D.O.; Dogo, E.M.
Blockchain is a distributed and decentralized ledger of transactions that are linked together cryptographically leading to immutability and tamper-resistance, thereby ensuring the integrity of data. Due to the ability of blockchain to guarantee the integrity of data, it has found wide-range adoption in electronic voting (e-voting) systems in recent years, this is in a bid to prevent manipulation of votes. However, due to the distributed nature of the blockchain, opportunities arise for privacy intrusion of the data being secured. The translation of this privacy flaw in blockchain to e-voting systems is the possibility of violation of the privacy of the electorates. Consequently, in a bid to achieve integrity and privacy of votes in e-voting, this study presents the use of an open-source blockchain system, coupled with a privacy-oriented cryptosystem known as the Paillier cryptosystem, towards addressing the privacy concerns of the blockchain. The performance of the system was evaluated and a transaction throughput of 1424 tps was obtained for ten thousand simulated ballot transactions. Further evaluation was carried out on the system, by increasing the number of system transactions. This showed that the mining time of the blockchain increased by an average factor of 0.18 s for every thousand increases in the number of transactions. Also, the response time of the system to a range of user actions was evaluated over an increasing number of voters. Results obtained showed that the response time of the system for vote casting operations increased by an average of 0.33 min per thousand voters while for vote tallying there was an increase in response time by an average of 0.848 min per thousand voters. The scientific value of this study is the development of an integrity and privacy-preserving e-voting system consisting of an open-source nodechain coupled with a privacy-oriented cryptosystem known as the Paillier cryptosystem following the security requirements of e-voting systems. The proposed system addresses the issue of integrity in e-voting while still maintaining the privacy of the electorates.
Performance Evaluation of Data Mining Techniques in Steel Manufacturing Industry
(Elsevier, 2019) Nkonyana, T.; Sun, Y.; Twala, B.; Dogo, E.
Industry 4.0 has evolved and created a huge interest in automation and data analytics in manufacturing technologies. Internet of Things (IoT) and Cyber Physical System (CPS) are some of the recent topics of interest in the manufacturing sector. Steel manufacturing process relies on monitoring strategies such as fault detection to reduce number of errors which can lead to huge losses. Proper fault diagnosis can assist in accurate decision-making. We use in this study predictive analysis to help solve the complex challenges faced in industrial data. Random Forest, Artificial Neural Networks and Support Vector Machines are used to train and test our industrial data. We evaluate how ensemble methods compare to classical machine learning algorithms. Finally we evaluate our models’ performance and significance. Random Forest outperformed other ML methods in our study. Keywords: Machine Learning; Manufacturing; Fault Diagnostics
Taking Cloud Computing to the Extreme Edge: A Review of Mist Computing for Smart Cities and Industry 4.0 in Africa
(Springer, 2019) Dogo, E.M., Salami, A.F., Aigbavboa, C.O., Nkonyana, T.
The advancement and convergence of Internet of Things (IoT), mobile devices technology, big data and cloud computing with its various technological implementations are finally enabling the vision of Smart Cities and Industry 4.0. However, cloud computing concept has been built with the assumptions of good network connectivity, adequate bandwidth and low latency. But with the proliferation of interconnected smart devices and the expected huge amount of traffic and data to be generated, coupled with the stringent and extremely demanding connectivity, high bandwidth and low latency requirements placed on applications and services were embedded in Smart Cities and Industry 4.0 concepts. The traditional cloud-centric architectural arrangement no longer holds due to these cloud architectural model assumptions. Cloud computing is therefore gradually evolving into new complementary concepts as edge and fog computing, and now mist and dew computing. Mist computing addresses these concerns by extending the capabilities and features of cloud and fog computing, with some level of computing intelligence further on the extreme edge of the network closer or on the sensing devices. With the technological revolution currently spreading across Africa, policy makers, academics and businesses in Africa are gradually recognizing the potential opportunities embedded in embracing emerging and future technologies to tackle issues related to urbanization and industrialization as catalyst for sustainable development and growth. This chapter studies the current trend in mist computing and discusses the application and the potential use case scenarios for Smart Cities and Industry 4.0 in the context of Africa. The chapter also explores practical implementation challenges and drivers supporting growth of these emerging cloud technologies in the region. Finally, pertinent technical recommendations were proposed as solution to the challenges identified together with a qualitative analysis of future opportunities of mist computing in the overall vision of Smart African Cities and Industry Africa 4.0.
Toward Sustainable Domestication of Smart IoT Mobility Solutions for the Visually Impaired Persons in Africa
(Springer, 2020) Salami, A.F.; Dogo, E.M.; Nwulu, N.I.; Paul, B.S.
According to World Health Organization (WHO) estimates, Africa accounts for 10% of the global visually impaired persons (VIPs). This visual impairment burden is exacerbated by the shortage of specialist medical human resources, orientation and mobility specialists, and high cost of assessing primary eye care services. These render the majority of VIPs to rely heavily on human-assisted guides and ineffective navigation aids for their daily routines and movements. A viable technological solution that can fill this void and meet these mobility needs is the Internet of Things (IoT). This chapter provides an assessment of smart IoT mobility solutions pertinent to the African context. Furthermore, the barriers to the realization of technology domestication as well as growth catalysts are examined. Lastly, this chapter proffers technical recommendations for sustainable domestication of smart IoT mobility solutions for VIPs in Africa.