MACHINE LEARNING-BASED PATH LOSS MODELS FOR HETEROGENEOUS RADIO NETWORK PLANNING IN A SMART CAMPUS

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 heterogeneous model was developed for path loss predictions in a typical university campus propagation environment using machine learning approach. Radio signal measurements were conducted within the campus of Covenant University, Ota, Nigeria to obtain the logs of signal path loss at 900, 1800, and 2100 MHz. Different path loss prediction models were developed based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) learning algorithms. The prediction accuracy and generalization ability of the ANN-based model, which has seven input nodes (distance, frequency, clutter height, elevation, altitude, latitude, and longitude), single hidden layer with 43 neurons and logarithmic sigmoid (logsig) activation function, and a single output neuron (for path loss variable) with tangent hyperbolic sigmoid (tansig) activation function, was found to be the best when compared to the prediction outputs of SVM-based model, and popular empirical models (i.e. Okumura-Hata, COST 231, ECC-33, and Egli). The ANN-based path loss model was trained based on Levenberg-Marquardt learning (LM) learning algorithm. The prediction outputs of the ANN-based path loss model has the lowest Root Mean Square Error (RMSE) of 4.480 dB, Standard Error Deviation (SED) of 4.479 dB, and the highest value of correlation coefficient (R) of 0.917, relative to the measured path loss values. This finding was further validated by the results of Analysis of Variance (ANOVA) and multiple comparison post-hoc tests. In essence, ANN-based path loss model was found to be the optimal model for heterogeneous radio network planning, deployment, and optimization in a smart campus propagation environmen

Federated deep learning for botnet attack detection in IoT networks

The wide adoption of the Internet of Things (IoT) technology in various critical infrastructure sectors has attracted the attention of cyber attackers. They exploit the vulnerabilities in IoT to form a network of compromised devices, known as botnet, which is used to launch sophisticated cyber-attacks against the connected critical infrastructure. Recently, researchers have widely explored the potentials of Machine Learning (ML) and Deep Learning (DL) to detect botnet attacks in IoT networks. However, there are still some challenges that need to be addressed in this area, which include the determination of optimal model hyperparameters, low classification performance due to imbalanced sample distribution in the training set, high memory space requirement for network traffic data storage, inability to detect zero-day attacks, and lack of data privacy. In order to address these problems, a Federated Deep Learning (FDL) method is developed for botnet attack detection in IoT-enabled critical infrastructure. First, a hyperparameter optimisation method is developed for DL-based botnet attack detection in IoT networks to achieve high classification performance. The effectiveness of the method is evaluated using the Bot-IoT and N-BaIoT datasets, and the DL models achieved 99.99 ± 0.02% accuracy, 97.85 ± 3.77% precision, 98.72 ± 2.77% recall, and 97.72 ± 4.51% F1 score. Then, an oversampling algorithm is combined with DL models to improve the classification performance when the training data is highly imbalanced, without any significant increase in the overall computation time. This method improved the precision, recall, and F1 score of the DL models by 1.66-13.23%. Furthermore, a hybrid DL method is developed to reduce the amount of memory space required to store the network traffic data. This method reduced the memory space requirement for DL-based botnet attack detection by 86.45-98.26%. Finally, a FDL method, which also employed the hyperparameter optimisation, class balance, and memory space reduction methods, is developed to detect zero-day botnet attacks in IoT edge nodes, while preserving the data privacy of IoT users. The FDL models achieved high classification performance, and they had low communication overhead and low network latency

Effective Usage of Information and Communications Technology by Career Administrators in Tertiary Institutions: The Obafemi Awolowo University Experience

The study identified the information and communication technology tools used by career administrators in Obafemi Awolowo University, Ile-Ife; determined the level of ICT compliance in the performance of administrative tasks by the career administrators in the said institution; examined the attitude of the respondents to the adoption and use of information and communication technologies in performing administrative tasks; and identified the challenges militating against the optimum deployment of information and communication technologies by career administrators in the institution under reference. These were with the view to understanding the use of information and communication technologies by professional or career Administrators in the study area. Both primary and secondary data sources of data collection were employed for the study. The former were obtained through a structured questionnaire and complemented by an interview guide. Out of a study population of 109, 85 respondents were selected by a simple random technique. Secondary data were obtained from relevant university books and digests, previously published and unpublished studies related to the use of ICT in different sectors of national life, official documents and internet sources on ICT. Data collected were analyzed using simple percentages. The study showed that access to basic ICT hardware such as desktop computers (85.8%) and printers (77.6%) in the workplace was fairly adequate, though, usage had to be negotiated in some instances. 92.9% of the respondents were able to use Microsoft Word and 5% were able to use Microsoft Access, while only 1.2% each were able to deploy the use of Prezi and Evernote in providing administrative services. The study also revealed that the major challenges militating against the maximal deployment of ICT tools by the respondents are epileptic power supply, unstable internet connectivity and the need to have to negotiate with other users of ICT hardware such as desktop, laptops and scanners in the workplace, before gaining access to such tools. The study concluded that information and communication technologies have been widely embraced by career Administrators in the University and this has to a large extent improved effectiveness, accuracy and efficiency in the area of service delivery. However, there was need for further training especially with regards to the use of some software with advanced features in Microsoft Word as well as Power Point, Prezi, Evernote, and Microsoft Access for improved administrative services in the University. Keywords: Information and Communications Technology; Higher Education Administration, Career Administrators, Prezi, Evernote DOI: 10.7176/JESD/10-16-21 Publication date: August 31st 201

Development of a Solar Photovoltaic Vulcanizing Machine towards Extreme Poverty Eradication in Africa

The number of African families living in extreme poverty has continued to increase even though the proportion of the citizens in such situation in this region declined in recent years. This is traceable to unemployment, underemployment, and income inequalities that have generated social unrest as joblessness persist. However, entrepreneurship through small and medium-scale enterprises (SMEs) has the capacity to drive economic growth and national development through job creation, income empowerment, and poverty eradication. Roadside vulcanizing business in towns and cities of Africa is a viable job that can be run by any age group and it requires no formal training or long apprenticeship to develop expertise. Unfortunately, the cost of running the fossil fuel-powered vulcanizing machine will leave the technician with little or no profit due to the recent fuel subsidy removal by some countries like Nigeria. In addition, overdependence on fossil fuel as a primary source of energy promotes the negative effects of carbon dioxide and other global warming emissions on environment, climate, and public health. In this paper, considering the abundant solar energy potential across all the Sub-Saharan countries, we designed and constructed a solar photovoltaic vulcanizing machine as a practical means of eradicating extreme poverty in line with the 2030 Sustainable Development Goals (SDGs) agenda. The implementation of this project will create employment opportunities for millions of Africans, reduce social violence and crime, provide affordable and clean energy, and save our planet

Plastic Mannequin-Based Robotic Telepresence for Remote Clinical Ward Rounding

Mobile robotic telepresence is a potential solution to addressing the problem of access to quality healthcare delivery in rural areas. Despite the availability of this system in its different forms, the capital and operating costs are unffordable for people living in rural areas, particularly in emerging economies. In this paper, the authors reduced the cost of mobile robotic telepresence solution for remote ward rounding using plastic mannequin and solar photovoltaic technology. An IP camera was fixed in each of the eye sockets of the plastic mannequin. These cameras are connected to a mini-computer embedded in the plastic mannequin. A Wi-Fi module establishes an Internet connection between remote physicians and rural healthcare facilities. In addition, most of these communities are not even connected to the power grid. Therefore, the system is powered by a solar photovoltaic energy source to provide a cheap and reliable power system. Another unique feature of this solution is that it gives the patient a better impression of the physical presence of a physician. This development will increase the adoption of robotic telepresense for remote clinical ward rounding in developing countrie

Smart Vehicular Traffic Management System using RFID Technology

Public places are often characterized with incessant traffic congestion, especially during special occasions and events, as large number of automobiles attempt to use the same parking lot concurrently. This usually result in confusion and dispute, auto crashes, waste of time and resources, and release of more carbon into the ecosystem. Radio Frequency Identification (RFID) technology offers effective solution for distant object identification without requiring a line of sight. In this paper, the authors developed an intelligent, cost-effective, and eco-friendly park management system for scalable traffic control using RFID and Solar photovoltaic (SPV) technologies. Pre-registered and visiting vehicles are assigned tags to access designated parking lots. However, large-scale implementation of the technology for intelligent park management requires a stable power supply with no threat to our ecosystem. SPV-powered UHF RFID readers transmit vehicle information via wireless data links to a host system application at the SPV-powered central database management system for further processing. This system will ensure effective traffic control during peak periods in order to avoid crashes, save time and resources, and as well save our plane

Development of Smart Assistive DTMF Home Automation System for Ageing Population

According to recent statistics, there is an increasing growth in the percentage of older persons in almost every part of the world today is recorded. The rate at which the proportion of older persons increases in the population of developing countries is much faster than what is experienced in developed regions. Specifically, this trend is more predominant in developing economies with relatively much lower level of socio-economic development, particularly in Africa. In response to this, modern technological advances in semiconductor technology and wireless communication can be significantly exploited to drive the economic and social paradigm shifts associated with population ageing towards achieving the Sustainable Development Goals (SDGs) in Africa. In this paper, we designed and implemented a cost-effective smart assistive DTMF home automation system that utilizes a tele-remote circuit to control home appliances via existing cellular communication networks. This system adopted a GSM module as feedback device. Dual Tone Multi Frequency (DTMF) tones generated from keypads of mobile cell phones remotely control home devices and appliances. An integrated DTMF receiver decodes the tones and processes the information to control several devices using a relay switching system with an effective feedback mechanism. The digitallycontrolled system overcomes the limited range of infrared and radio remote controls with the aid of available cellular communication systems. Therefore, older people of the populace can be provided with better ease of living at home by minimizing their movement and dependency at affordable cost

Development of a Wireless Power Transfer System using Resonant Inductive Coupling

Access to power is a fundamental requirement for the effective functioning of any electrical/electronic circuit. The conduit of transfer of power can be either physical (wires, cables etc.) of non-physical (i.e. wireless). Wireless power transfer is a broad term used to describe any means used to transmit power to electricity dependent systems and devices. In this paper, a wireless power transfer system is developed to provide an alternative to using power cords for electrical/electronic devices. With this technology, challenges like damaged or tangled power cords, sparking hazards and the extensive use of plastic and copper used in cord production are resolved and also the need for batteries in non-mobile devices is eliminated. In this system, electromagnetic energy is transmitted from a power source (transmitter) to an electrical load (receiver) via resonant inductive coupling. The performance achieved is a good indication that power can still be transmitted over a medium range. In addition, possible ways of improving the efficiency of the system are discussed

Digital Speed Control of DC Motor for Industrial Automation using Pulse Width Modulation Technique

Precise speed control is an important requirement for efficient industrial automation. Direct current (DC) motors have been extensively used for this purpose. The conventional method employs analog circuits to control the speed of the DC motor by varying the voltage of the armature while the field voltage is kept constant. In this paper, a digital speed control of DC motor using pulse width modulation technique was implemented by replacing analog circuit with an Atmel AT89S52 microcontroller circuit. An experimentation of the design showed that the DC motor can run forward motoring, forward regeneration, reverse motoring and reverse regeneration. This digital approach proved to have increased precision and greater control efficiency. Thus, a centralized control of several motors can also be achieve