Segun I. Popoola

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• Doctor of Philosophy
• Senior Lecturer at Anglia Ruskin University

Blockchain (BC) and artificial intelligence (AI) are often utilised separately in energy trading systems (ETS). However, these technologies can complement each other and reinforce their capabilities when integrated. This paper provides a comprehensive review of consensus algorithms (CA) of BC and deep reinforcement learning (DRL) in ETS. While the...

Deep Learning (DL) is an efficient method for botnet attack detection. However, the volume of network traffic data and memory space required is usually large. It is, therefore, almost impossible to implement the DL method in memory-constrained IoT devices. In this paper, we reduce the feature dimensionality of large-scale IoT network traffic data u...

Deep Learning (DL) has been widely proposed for botnet attack detection in Internet of Things (IoT) networks. However, the traditional Centralized DL (CDL) method cannot be used to detect previously unknown (zero-day) botnet attack without breaching the data privacy rights of the users. In this paper, we propose Federated Deep Learning (FDL) method...

In this paper, we propose Federated Deep Learning (FDL) for intrusion detection in heterogeneous networks. Local Deep Neural Network (DNN) models are used to learn the hierarchical representations of the private network traffic data in multiple edge nodes. A dedicated central server receives the parameters of the local DNN models from the edge node...

Consumer-centric Internet of Things (CIoT) will play a pivotal role in the fifth industrial revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various cyberattacks. Recent studies have explored the potential of Federated Learning (FL) for privacy-preserving intrusion detection in IoT. However, the developmen...

The Industrial Internet of Things (IIoT) facilitates enhanced automation, predictive maintenance, real-time monitoring, and data analytics across various sectors, including manufacturing, energy, transportation, agriculture, and supply chain management, thereby improving productivity, efficiency, and operational safety. However, as IIoT networks co...

The book covers the exploitation of computational models for effectively developing and managing large-scale wireless communication systems. The goal is to create and establish computational models for seamless human interaction and efficient decision-making in beyond 5G wireless systems. Computational Modeling and Simulation of Advanced Wireless...

p>In this paper, we propose an optimized lightweight Federated Deep Learning (FDL) method for botnet attack detection in smart critical infrastructure. First, an optimization method is developed to determine the most appropriate combination of model hyperparameters for local Deep Learning (DL) at the edge nodes. Then, an oversampling algorithm is c...

p>In this paper, we propose an optimized lightweight Federated Deep Learning (FDL) method for botnet attack detection in smart critical infrastructure. First, an optimization method is developed to determine the most appropriate combination of model hyperparameters for local Deep Learning (DL) at the edge nodes. Then, an oversampling algorithm is c...

Academic and research institutions need to be at the forefront of research and development efforts on sustainable energy transition towards achieving the 2030 Sustainable Development Goal 7. Thus, the most economically feasible hybrid renewable energy system (HRES) option for meeting the energy demands of Covenant University was investigated in thi...

Deep Learning (DL) models can be trained to automatically learn the underlying features of the traffic patterns in IoT networks to detect complex botnet attacks. However, the performance of a neural network model largely depends on the set of hyperparameters that is used for the model development. In this paper, an algorithm is proposed to determin...

Deep Learning (DL) models can be trained to automatically learn the underlying features of the traffic patterns in IoT networks to detect complex botnet attacks. However, the performance of a neural network model largely depends on the set of hyperparameters that is used for the model development. In this paper, an algorithm is proposed to determin...

Multisource energy data, including from distributed energy resources and its multivariate nature, necessitate the integration of robust data predictive frameworks to minimise prediction error. This work presents a hybrid deep learning framework to accurately predict the energy consumption of different building types, both commercial and domestic, s...

This paper investigates the effect of number and shape of membership function (MF), and training data size on the performance of ANFIS model for predicting path losses in the VHF and UHF bands in built-up environments. Path loss propagation measurements were conducted in four cities of Nigeria over the cellular and broadcasting frequencies. A total...

Internet of Things (IoT) devices in Smart Home Network (SHN) are highly vulnerable to complex botnet attacks. In this paper, we investigate the effectiveness of Recurrent Neural Network (RNN) to correctly classify network traffic samples in the minority classes of highly imbalanced network traffic data. Multiple layers of RNN are stacked to learn t...

Cyber attackers exploit a network of compromised computing devices, known as a botnet, to attack Internet-of-Things (IoT) networks. Recent research works have recommended the use of Deep Recurrent Neural Network (DRNN) for botnet attack detection in IoT networks. However, for high feature dimensionality in the training data, high network bandwidth...

Nowadays, hackers take illegal advantage of distributed resources in a network of computing devices (i.e., botnet) to launch cyberattacks against the Internet of Things (IoT). Recently, diverse Machine Learning (ML) and Deep Learning (DL) methods were proposed to detect botnet attacks in IoT networks. However, highly imbalanced network traffic data...

Bidirectional gated recurrent unit (BGRU) can learn hierarchical feature representations from both past and future information to perform multi-class classification. However, its classification performance largely depends on the choice of model hyperparameters. In this paper, we propose a methodology to select optimal BGRU hyperparameters for effic...

Artificial Neural Networks (ANNs) have been recently exploited to develop suitable models for path loss predictions . However, the ANN algorithm that provides the best results has not been well established neither has the models been characterized to limit their performances and applications in the various frequency bands. In this paper, we charact...

Indiscriminate disposal of solid waste is a major issue in urban centers of most developing countries and it poses a serious threat to healthy living of the citizens. Access to reliable data on the state of solid waste at different locations within the city will help both the local authorities and the citizens to effectively manage the menace. In t...

Unfortunately, in the original publication of the article the third author name was misspelled as Faisal Abnisal.

The reliability and accuracy of radio propagation models depends on the unique localized features in the area under study. In this paper, we calibrate empirical radio propagation models for 1800 MHz cellular network planning in Lagos Metropolis, Nigeria. Drive test are conducted to obtain measured data within suburban and dense urban propagation en...

Path Loss (PL) propagation models are important for accurate radio network design and planning. In this paper, we propose a new radio propagation model for PL predictions in urban environment using Support Vector Machine (SVM). Field measurement campaigns are conducted in urban environment to obtain mobile network and path loss information of radio...

Steering angle prediction is critical in the control of Autonomous Vehicles (AVs) and has attracted the attention of researchers, manufacturers, and insurance companies in the automotive industry. Different Deep Learning (DL) architectures have been applied to predict the steering angle of AVs in various scenarios. A survey on steering angle predic...

In Content-Based Image Retrieval (CBIR) system, one approach of image representation is to employ combination of low-level visual features cascaded together into a flat vector. While this presents more descriptive information, it however poses serious challenges in terms of high dimensionality and high computational cost of feature extraction algor...

High consumption of paracetamol (PCM) has resulted to discharge of a large quantity of its metabolite into the environment and there is an urgent need to remove this harmful contaminant in a sustainable manner. In this work, Artificial Neural Network (ANN) was used as a Machine Learning tool for prediction of PCM adsorption efficiency on chemically...

In this work, an artificial neural network (ANN) was developed to model the Pseudo- Second Order (PSO) kinetics of orange peel-paracetamol adsorption process. The orange peel used for the adsorption process was prepared, activated, and characterized using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) techniqu...

Negative resistance devices have attracted much attention in the wireless communication industry because of their low cost, better performance, high speed, and reduced power requirements. Although negative resistance circuits are non-linear circuits, they are associated with distortion, which may either be amplitude-to-amplitude distortion or ampli...

Access to quality healthcare is a major problem in Sub-Saharan Africa with a doctor-to-patient ratio as high as 1:50,000, which is far above the recommended ratio by the World Health Organization (WHO) which is 1:600. This has been aggravated by the lack of access to critical infrastructures such as the health care facilities, roads, electricity, a...

The future of Africa is too important to be left alone in the hands of the Government and African Union. As Africa arises and begins to journey towards the Africa we want, we look forward to actualizing Agenda 2063. We do not see it only as a vision, but also as an action plan set in place, geared towards achieving the Africa of our dreams. The pur...

This study explored the predictive modelling of the pyrolysis of rice husk to determine the thermal degradation mechanism of rice husk. The study can ensure proper modelling and design of the system, towards optimising the industrial processes. The pyrolysis of rice husk was studied at 10, 15 and 20 °C min⁻¹ heating rates in the presence of nitroge...

Path loss models are veritable tools for estimation of expected large-scale signal fading in a specific propagation environment during wireless network design and optimization. In this paper, the capability of Adaptive Neuro-Fuzzy Inference System (ANFIS) to establish non-linear relationship between related variables was explored for path loss pred...

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translate...

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translate...

It is very important to understand the input features and the neural network parameters required for optimal path loss prediction in wireless communication channels. In this paper, an extensive investigation was conducted to determine the most appropriate neural network parameters for path loss prediction in Very High Frequency (VHF) band. Field me...

This work investigates and show the performance of destination assisted node in ensuring secure communication in a dual-hop broadcast system. The information transmission occurs between the transmitters which is assumed to be equipped with single antenna through a number of intermediate untrusted relays to the receiver in the presence of multiple p...

Deployment of heterogeneous networks (HetNets) is a veritable solution to the challenges of coverage and capacity in meeting the unprecedented future mobile data traffic. However, the high density of small base stations (SBS) in future HetNets may increase the complexity of backhauling with higher capital expenditure (CAPEX), operating expenditure...

Artificial Neural Networks (ANNs) which are one of the main tools used in machine learning have often been utilised in developing models for path loss modelling in recent times. However, the ANN algorithm that provides the best results has not been well established neither has the models been characterized to limit their performances and applicatio...

In this paper, we present and analyze comprehensive data about scholarly contributions that were indexed in Scopus database between 2012 and 2017. The datasets are categorized (based on the country where the research was carried out) into: Africa; Asia Pacific; Europe; Middle East; North America; and South America. Scholarly contributions of each r...

The very limited nature of the GSM spectrum, coupled with the increasing demand by an extending number of subscribers place a strain on the network capacity. This leads to an equally raised number of calls that dropped and hence, subscriber dissatisfaction. Several strategies have been implemented in order to minimize these occurrences, with the mo...

Peer tutoring is a unique and efficient method of teaching that has been widely investigated. Related works in the literature ranges from cross-age peer tutoring, peer tutoring for the disabled, reciprocal peer tutoring, to peer tutoring for children. One unique method that has been scarcely documented, however, is peer tutoring with the aid of the...

Electricity consumption has been on a rapid increase worldwide and it is a very vital component of human life in this age. Hence, reliable supply of electricity from the utility operators is a necessity. However, the constraints that electricity supplied must be the same as electricity consumed puts the burden on the utility operators to make sure...

Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have b...

Path loss propagation is a vital concern when designing and planning networks in mobile communication systems. Propagation models such as the empirical, deterministic and theoretical models, which possess complex, inconsistent, time-consuming and non-adaptable features, have proven to be inefficient in designing of wireless systems, thereby resulti...

In recent year electroless Ni–P coatings with the incorporation of metallic oxides have received profound interest due to their unique properties and ability to enhance the operational performance of the based metal. These coatings have been utilised for numerous applications such as aerospace, automotive and industrial field where materials with e...

In spite of the prominence of extreme learning machine model, as well as its excellent features such as insignificant intervention for learning and model tuning, the simplicity of implementation, and high learning speed, which makes it a fascinating alternative method for Artificial Intelligence, including Big Data Analytics, it is still limited in...

Among other things, the performance of a university can be measured based on the volume and the impact of their scholarly research publications. However, the empirical evidence that are needed for objective analysis, evaluation, and ranking of universities based on this factor are often not readily and freely accessible to the public. In this paper...

Indiscriminate disposal of solid waste is a major issue in urban centers and it poses a serious threat to healthy living of the citizens. Timely access to reliable information on the level of solid waste at different locations within the city will help both the local authorities and the citizens to effectively manage this menace. In this paper, an...

Gender equality in access to higher education is an important factor in building a sustainable world. Although a good number of countries across the globe have achieved parity in primary education between boys and girls, the target is yet to be widely attained at tertiary level of education. In this data article, empirical data on yearly admissions...

Efficient broadband Internet access is required for optimal productivity in smart campuses. Besides access to broadband Internet, delivery of high speed and good Quality of Service (QoS) are pivotal to achieving a sustainable development in the area of education. In this data article, trends and patterns of the speed of broadband Internet provided...

This is a list of various research articles published by collaborative efforts of IoT-enabled Smart and Connected Communities cluster members.

Image retrieval via traditional Content-Based Image Retrieval (CBIR) often incurs the semantic gap problem—non-correlation of image retrieval results with human semantic interpretation of images. In this paper, Relevance Feedback (RF) mechanism was incorporated into a traditional Query by Visual Example CBIR (QVER) system. The inherent curse of dim...

This paper is concerned with how the implementation of Mobile Number portability in Nigeria (MNP) has affected the revenue of mobile operators in Nigeria. It gives an overview of marked effect of MNP on revenue of mobile operators in Nigeria by comparing statistics, rate of porting and taking case studies. When MNP was launched on the 22 nd of Apri...

Linearity plays an important role in the design and implementation of radio frequency power amplifier. Although negative resistance circuits are non-linear circuits, they are associated with distortion, which may either be amplitude-to-amplitude distortion or amplitude-to-phase distortion. In this paper, a unique way of realizing a negative resista...

Utilization of software-defined radio (SDR) and open-source technologies in the next evolution of cellular communication networks may significantly reduce the capital expenditure (CAPEX) and operating expenditure (OPEX) of mobile network operators in emerging economies. In this paper, a novel cellular communication architecture named NomadicBTS was...

Robotic lawn mowers have come to stay. The ease with which lawns and fields can be maintained without any human input is mind-blogging. As technology improves, the complexity and diversity of robotic lawn mowers keeps pushing into realms only imagined in the immediate time past. But in this age of interconnected things and interwoven thinking, ther...

In this data article, an analysis on the strategies for talent retention in Covenant University and the corresponding effects on employees’ attitude to work was presented. The study population included the academic staff of Covenant University, which has a population of 530 employees, but a sample size was determined using Yamen's formula. The data...

In practice, appropriate computer vision and image processing techniques are usually employed to obtain image visual features. Central to functional Content Based Image Retrieval (CBIR) system is effective indexing and fast searching of images based on the visual features. Effective indexing is also essential to make CBIR system scalable for large...

In this paper, an alcohol detection system was developed for road transportation safety in smart city using Internet of Things (IoT) technology. Two Blood Alcohol Content (BAC) thresholds are set and monitored with the use of a microcontroller. When the first threshold is reached, the developed system transmits the BAC level of the driver and the p...

In this data article, a robust data exploration is performed on daily Internet data traffic generated in a smart university campus for a period of twelve consecutive (12) months (January–December, 2017). For each day of the one-year study period, Internet data download traffic and Internet data upload traffic at Covenant University, Nigeria were mo...

An easy-to-use and accurate multi-frequency path loss model is a necessary tool for heterogeneous radio network planning and optimization towards achieving a smart campus. The learning ability in artificial intelligence may be exploited to reduce computational complexity and to improve prediction accuracy. In this research project, an optimal heter...

Electronic Toll Collection (ETC) systems may be adopted by city managers to combat the problems of long vehicular queues, fuel wastage, high accident risks, and environmental pollution that come with the use of traditional or manual toll collection systems. In this paper, an intelligent system is developed to eliminate long vehicular queues, fuel w...

This document provides a summary of the scholarly research output of Segun I. Popoola in two active years of research (June, 2016 - May, 2018). Segun has authored and co-authored a total of fifty (50) internationally peer-reviewed sholarly publications namely: twenty-six (26) journal articles, twenty-three (23) conference papers, and one (1) book c...

Citation is one of the important metrics that are used in measuring the relevance and the impact of research publications. The potentials of citation analytics may be exploited to understand the gains of publishing scholarly peer-reviewed research outputs in either Open Access (OA) sources or Subscription-Based (SB) sources in the bid to increase c...

Cassava mosaic disease (CMD) is one of the most economically important viral diseases of cassava, an important staple food for over 800 million people in the tropics. Although several Cassava mosaic virus species associated with CMD have been isolated and characterized over the years, several new super virulent strains of these viruses have evolved...

Path loss prediction is an important process in radio network planning and optimization because it helps to understand the behaviour of radio waves in a specified propagation environment. Although several models are currently available for path loss predictions, the adoption of these models requires a tradeoff between simplicity and accuracy. In th...

Empirical measurement, monitoring, analysis, and reporting of learning outcomes in higher institutions of developing countries may lead to sustainable education in the region. In this data article, data about the academic performances of undergraduates that studied engineering programs at Covenant University, Nigeria are presented and analyzed. A t...

In this paper, an optimal model is developed for path loss predictions using the Feed-Forward Neural Network (FFNN) algorithm. Drive test measurements were carried out in Canaanland Ota, Nigeria and Ilorin, Nigeria to obtain path loss data at varying distances from 11 different 1,800 MHz base station transmitters. Single-layered FFNNs were trained...

In a typical outdoor environment, the propagation of radio waves is usually random in nature, to the extent that the characterization of the wireless channel often becomes very difficult. Several models have been developed to predict the average Received Signal Strength (RSS) for specified distance ranges. However, the use of deterministic models r...

In this data article, we present and analyze the demographic data of undergraduates admitted into engineering programs at Covenant University, Nigeria. The population distribution of 2,649 candidates admitted into Chemical Engineering, Civil Engineering, Computer Engineering, Electrical and Electronics Engineering, Information and Communication Eng...

Empirical models are most widely used for path loss predictions because they are simple, easy to use, and require less computational efficiency when compared to deterministic models. A number of empirical path loss models have been developed for efficient radio network planning and optimization in different types of propagation environments. Howeve...

This data article presents data of academic performances of undergraduate students in Science, Technology, Engineering and Mathematics (STEM) disciplines in Covenant University, Nigeria. The data shows academic performances of Male and Female students who graduated from 2010 to 2014. The total population of samples in the observation is 3046 underg...

This data article represents academic performances of undergraduate students in a select Nigerian Private Tertiary institution from 2008 to 2013. The 2413 dataset categorizes students with respect to their origins (ethnicity), pre-university admission scores and Cumulative Grade Point Averages earned at the end of their study at the university. We...

Path loss prediction models are essential in the planning of wireless systems, particularly in built-up environments. However, the efficacies of the empirical models depend on the local ambient characteristics of the propagation environments. This paper introduces artificial intelligence in path loss prediction in the VHF band by proposing an adapt...

In this data article, the Key Performance Indicators (KPIs) for Quality of Service (QoS) of Global System for Mobile Communications (GSM) networks in Nigeria are provided and analyzed. The data provided in this paper contain the Call Setup Success Rate (CSSR), Drop Call Rate (DCR), Stand-alone Dedicated Channel (SDCCH) congestion, and Traffic Chann...

The behaviour of radio wave signals in a wireless channel depends on the local terrain profile of the propagation environments. In view of this, Received Signal Strength (RSS) of transmitted signals are measured at different points in space for radio network planning and optimization. However, these important data are often not publicly available f...

In Nigerian universities, enrolment into any engineering undergraduate program requires that the minimum entry criteria established by the National Universities Commission (NUC) must be satisfied. Candidates seeking admission to study engineering discipline must have reached a predetermined entry age and met the cut-off marks set for Senior School...

Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Therefore, efficient radio network planning and optimiza...

This data article presents comparisons of energy generation costsfrom gas-fired turbine and diesel-powered systems of distributed generation type of electrical energy in Covenant University, Ota, Nigeria, a smart university campus driven by information and Communication Technologies (ICT). Cumulative monthly data of the energy generation costs, for...