Cédric Stéphane Koumetio Tekouabou

• PhD
• Professor (Assistant) at University of Yaoundé I

Dear Professors, Researchers, and Academicians, We invite you to contribute high-quality chapters for the upcoming book "Technological Innovation and Sustainability through AI: Cutting-Edge Solutions for a Sustainable Future", to be published by CRC Press. This book will explore advanced AI-driven solutions for sustainability across various domain...

Rapid urbanization poses several challenges, especially when faced with an uncontrolled urban development plan. Therefore, it often leads to anarchic occupation and expansion of cities, resulting in the phenomenon of urban sprawl (US). To support sustainable decision–making in urban planning and policy development, a more effective approach to addr...

In the burgeoning landscape of African smart cities, education stands as a cornerstone for sustainable development and unlocking future potential. Accurate student performance prediction holds immense social importance, enabling early intervention, improved learning outcomes, and equitable access to quality education, aligning with sustainable deve...

In the era of the Industrial Revolution 4.0 (IR 4.0), the adequacy of training models for industrial needs is being challenged. Africa is a skills hub, threatened by unemployment among young people, especially graduates, competition, and the sustainability of industrial fabrics. By carrying out a systematic literature review, this article aims to h...

As the demand for efficient and lightweight models in image classification grows, knowledge distillation has emerged as a promising technique to transfer expertise from complex teacher models to simpler student models. However, the efficacy of knowledge distillation is intricately linked to the choice of datasets used during training. Datasets are...

Automating freehand sketches is a complex process due to their diverse and abstract characteristics. Recently, there has been significant interest among researchers in machine learning algorithms, owing to their emergence. Nevertheless, many utilized models are either inadequate or overly complex, featuring processes that lack clarity and consisten...

People rely extensively on online social networks (OSNs) in Africa, which aroused cyber attackers’ attention for various nefarious actions. This global trend has not spared African online communities, where the proliferation of OSNs has provided new opportunities and challenges. In Africa, as in many other regions, a burgeoning black-market industr...

This study employs a logistic regression model to offer an in-depth understanding of disparities in the access to essential urban services, specifically focusing on electricity and Internet services, in Nouakchott, Mauritania. Through a comprehensive analysis of demographic, geographic, and socioeconomic data, we identify key determinants of access...

The advanced urban digitization enhancing a huge volume of data collected in many areas has led to the emergence of artificial intelligence (AI) based tools in decision support systems. These use various machine learning algorithms to extract valuable information for important decision-making such as house price predictions. The urban real estate i...

This paper uses machine learning to predict road accidents in Morocco, a country marked by high annual accident rates. Our model employs data such as weather, time of day, and road conditions, derived from historical accidents and environmental records. Findings suggest that such predictive modeling can enable traffic authorities to anticipate high...

Urban mobility is one of the most important factors in the development of any nation and can act as a strong stimulant for economic expansion. Moreover, the rapid urban population growth in recent years has resulted in a substantial rise in the number of urban vehicles. But, the infrastructure on urban routes frequently isn’t adequate for a big num...

Accurate housing price forecasts are essential for several reasons. First, it allows individuals to make informed decisions about buying or selling real estate and to determine appropriate prices. Secondly, it helps real estate agents and investors make better investment decisions and negotiate contracts more effectively. In addition, housing price...

Building Information Modelling (BIM) is implemented in several sectors of the Architecture, Engineering, and Construction (AEC) industry. Faced with the challenges of urban management, smart cities are a response to this situation. Research indicates that BIM is one of the technological approaches with great potential for designing, constructing, a...

Inclusive smart cities aim to create a more equitable and accessible urban environment for all citizens, including people with disabilities, low-income individuals, and marginalized communities. This concept involves using technology and data to improve urban services and infrastructure while ensuring that everyone can benefit from these advances....

The objective of this work is to create an intelligent routing system based on machine learning methods, the usage of which opens up yet another opportunity to classify bundles as having successfully reached their destination or not. These networks periodically do an assessment, enabling the selection of the sort of routing appropriate for a certai...

This article examines the use of multisensor data fusion for land classification in three Moroccan cities. The method employs a Random Forest classification algorithm based on multispectral, synthetic aperture radar (SAR), and derived land surface temperature (LST) data. The study compares the proposed approach to existing datasets on impervious su...

The world’s cities, particularly African cities, are experiencing rapid exponential population growth. They need to respond dynamically to major challenges, such as digitalisation, the connected and smart city, sustainability, resilience, inclusion and economic development. To do so, modern and innovative urban planning actors must enable urban for...

Urban data strongly favored by urban digitization and web 2.0 constitute the raw material whose sources often diverge. However, as far as we know, little or no work has been done to explore the sources and targeted applications for urban planning indicators modelling. We aim to guide neophytes who seek to integrate smart data-driven applications in...

Air quality monitoring in developing countries is in deplorable condition despite its impact on many aspects of life such as population health. Among the very fine particulate pollutants in the air, PM2.5 and PM10 are more numerous and therefore more dangerous. Higher exposure to these fine particles, which are difficult to perceive by the eye, wou...

With the increase in the amount and variety of data that are constantly produced, collected, and exchanged between systems, the efficiency and accuracy of solutions/services that use data as input may suffer if an inappropriate or inaccurate technique, method, or tool is chosen to deal with them. This paper presents a global overview of urban data...

The world’s cities are facing various challenges such as rapid urbanization, poverty, climate change, pollution, sustainable and inclusive development. Building futuristic smart and sustainable cities is proving to be a response to these challenges. Recent publications show that urban planning decision support is increasingly using artificial intel...

Crowdsourcing could potentially have great benefits for the development of sustainable cities in the Global South (GS), where a growing population and rapid urbanization represent serious challenges for the years to come. However, to fulfill this potential, it is important to take into consideration the unique characteristics of the GS and the chal...

Wireless Sensor Networks (WSNs) are used to gather data in a variety of sectors, including smart factories, smart buildings, and so on, to monitor surroundings. Different medium access control (MAC) protocols are accessible to sensor nodes for wireless communications in such contexts, and they are critical to improving network performance. The prop...

The diversity of data collected on both social networks and digital interfaces is extremely increased, raising the problem of heterogeneous variables that are not often favourable to classification algorithms. Despite the significant improvement in machine learning (ML) and predictive analysis efficiency for classification in customer relationship...

Recently, the diversity of data collected on both social networks and digital interfaces is extremely increased. This diversity of data raises the problem of heterogeneous variables that are not favourable to classification algorithms. Although machine learning and predictive analysis have significantly improved the efficiency of the classification...

The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in every field. For the automatic targeting of customers in...

Renewable solar energy is one of the most preferable clean energy sources with no environmental impacts. The Marrakech Safi region (Moroccan context), with its arid and semi‐arid climate, can ensure sustainable energy production‐oriented for a green economy. This paper aims to perform a decision analysis using the analysis hierarchical process (AHP...

The communication protocols of wireless networks have experienced great advances in recent years, specifically with the evolution of new technologies such as the Internet of Things (IoT). However, certain problems remain unsolved, in particular for wireless networks, and more specifically for DTN networks, which represent a major challenge in terms...

Artificial Intelligence is booming and many issues of research are being explored to improve technical performance in health systems. But also making them suitable for targeted medical practices. Their cost must also be justified by real added value for medical practitioners and patients. Extracting accurate information from data sets usually comes...

Modern cities dynamically face several challenges including digitalization, sustainability, resilience and economic development. Urban planners and designers must develop urban forms that address these challenges. With the integration of new communication and information technologies (Smartphone, GIS, Drones, IoT, Sensors, etc.), urban activities h...

Surface temperature is one of the critical factors used to study microclimate conditions through Land surface Temperature (LST), a widely used data source. This paper tests a classification approach using moderate spatial satellite resolution images to extract surface properties of Local Climate Zones (LCZs) in a semi-arid region against measured L...

Nowadays, data mining is widely used to mine business information and make them very strategic for decision. Many data mining techniques can be according to the large variety of datasets. Our paper aims to optimize the prediction of telemarketing target calls for selling bank long-term deposits in smart cities using improved KNN model. The dataset...

The problem of 3D hand pose estimation has aroused a lot of attention in computer vision community for long time. It has been studied in computer vision for decades, as it plays a significant role in human-computer interaction such as virtual/augmented reality applications, computer graphics and robotics. Because of the practical value associated w...

Smart cities are part of continuous advances in technology to provide a better quality of life for its inhabitants. Important topics in smart cities include urban mobility. Due to the increasing number of vehicles passing through cities, traffic and traffic are becoming common problems. In addition, finding places to park in the city center is not...

The Internet of Things (IoT) includes a variety of heterogeneous wireless network technologies such as Delay Tolerant Networks (DTN) and all kinds of smart devices connected over a wireless network. The strong size and cost constraints of DTN nodes lead to corresponding constraints on resources such as energy, memory, communication speed and bandwi...

Since the beginning of the global health crisis attributed to the new coronavirus (COVID-19), several announcements of new diagnostic tests have been made. It has suddenly become complicated to provide a comprehensive overview detailing the specificity of each of them. In the absence of therapeutic drugs or vaccines specific for COVID-19, these tes...

Soft Tissue Tumors (STT) are a form of sarcoma found in tissues that connect, support, and surround body structures. Because of their shallow frequency in the body and their great diversity, they appear to be heterogeneous when observed through Magnetic Resonance Imaging (MRI). They are easily confused with other diseases such as fibroadenoma mamma...

Global ecological requirements are pushing city actors to opt for ecological solutions at all levels, including urban mobility. More sustainable Bike-sharing systems (BSS) have become an indispensable part of the transport offer by world's major metropolis. Like any computerized service system, they generate voluminous and complex data that the use...

Waiting time at a bus station is sometimes long, or can seem very long for travellers. This feeling is caused by the multiple stops in the bus route as well as the time interval between the different stations. Indeed, people are always looking for the best way to plan their trips in the city and do not like waiting long hours at bus stops to reach...

Smart cities are part of the ongoing advances in technology to provide a better life quality to its inhabitants. Urban mobility is one of the most important components of smart cities. Due to the growing number of vehicles in these cities, urban traffic congestion is becoming more common. In addition, finding places to park even in car parks is not...

New technologies have been expanding rapidly in recent years. These new technologies require new communication systems, such as delay tolerant networks (DTN). However, establishing communications is not enough. Networks must allow data to be exchanged and these data must be understood by the entities that receive them. Although a lot of DTN routing...

In this paper, we present a new data modeling approach for five common classification algorithms to optimize the prediction of telemarketing target calls for selling bank long-term deposits. A Portuguese retail bank addressed, from 2008 until 2013, data on its clients, products and social-economic attributes including the effects of the financial c...