GeoAI-enabled Transformation of Urban Environmental Aesthetics in Nigerian Cities: Challenges, Opportunities, and Implementation Strategies | Chapter 1 | Current Research on Geography, Earth Science and Environment Vol. 4

 

Urban aesthetics encompasses the visual and spatial quality of a city, significantly affecting residents' well-being and economic growth. Theories of urban design emphasise the importance of spatial organisation, green spaces, and architectural coherence in fostering aesthetically appealing cities. Nigeria’s economic diversification hinges on transforming its urban centres into aesthetically vibrant, sustainable hubs, moving beyond reliance on crude oil. Geospatial technology has been shown to be affordable and efficient in understanding the varying forms of cities, their continuous expansion, and the processes responsible for their growth pattern. Cities like Lagos, once celebrated for their cultural and architectural heritage, now grapple with aesthetic decline driven by rapid urbanisation, inadequate planning, environmental degradation, and socio-economic disparities.

 

This study critically examines the challenges undermining urban environmental quality in Nigeria, focusing on hotspot cities like Lagos, Port Harcourt, Abuja, Kano, among others, as a case study, and identifies gaps in knowledge, infrastructure, and institutional support that exacerbate these issues. Key obstacles include limited geospatial data, high costs of GeoAI adoption, technical expertise deficits, and socio-cultural resistance to technology-driven urban interventions.

 

Employing a multidisciplinary approach, such as a systematic literature review, the study proposes novel contributions to innovative solutions, integrating sustainable urban planning, inclusive governance, public participation, and advanced geospatial technologies to restore and enhance urban beauty. The systematic literature review involves an extensive examination of 80 published academic sources, policy documents, and case studies relevant to urban aesthetics, GeoAI, governance, and sustainable city planning.

 

The study highlights the role of GeoAI in enabling precise urban design, green space optimisation, and infrastructure monitoring, drawing on best practices from cities like Singapore and Kigali that have successfully revitalised their urban aesthetics.

 

Advanced GeoAI technologies— encompassing satellite imagery, predictive analytics, and real-time urban monitoring—offer transformative potential to redeem the environmental aesthetics of Nigerian cities, fostering tourism, employment, and foreign exchange. However, incomplete data remains a critical barrier, undermining the reliability of spatial predictive models and their applications in urban planning and social sensing. Challenges such as missing features, sparse observations, temporal snapshot limitations, and mismatched spatial scales hinder GeoAI’s ability to capture the complex interplay of human–environment interactions in cities like Lagos.

 

This study argues that successful implementation in Nigeria demands robust policy frameworks, capacity building, and equitable technology access to bridge systemic inequalities. Through addressing these challenges, this study provides a new roadmap for policymakers, city planners, and stakeholders to leverage GeoAI for urban renewal, ensuring Nigerian cities reclaim their aesthetic allure while fostering economic and environmental resilience. This study's recommendations underscore that structuring Nigeria’s urban environmental aesthetics requires not only technological innovation but also a commitment to social equity and community-driven urban transformation.

 

Author(s) Details

 

Ugochukwu Udonna Okonkwo
Department of Geography and GIS / Department of Computer Management and Information Systems, Southern Illinois University, Edwardsville, U.S.A.

 

Ezekiel Tosin Babatunde
Department of Environmental Sciences, Southern Illinois University Edwardsville, U.S.A.

 

Philip Ugbede-Ojo Onuche
Department of Chemistry / Department of Management and Marketing, Southern Illinois University, Edwardsville, U.S.A.

 

Enoh Martha Francis
Department of Geography and Geospatial Sciences, Oregon State University, U.S.A.

 

Paul Osazuwa
Illinois Environmental Protection Agency (EPA), U.S.A.

 

Olumide S. Ogungbemi
Department of Geography and Geospatial Sciences, Oregon State University, U.S.A.

 

Please see the book here :- https://doi.org/10.9734/bpi/crgese/v4/6261

Cybersecurity and Privacy in 6G-Enabled Internet of Things (IoT) Ecosystems | Chapter 8 | New Horizons of Science, Technology and Culture Vol. 5

 

The advent of sixth-generation (6G) wireless networks marks a paradigm shift beyond incremental gains in speed and latency toward AI-native, hyper-connected ecosystems supporting trillions of Internet of Things (IoT) devices. With projected terabit-per-second throughput, sub-millisecond latency, and integration of terahertz communication, holographic MIMO, and distributed edge computing, 6G promises transformative applications in healthcare, transportation, smart cities, and immersive digital environments. However, this evolution also introduces unprecedented cybersecurity and privacy challenges. AI-driven network management creates new attack surfaces vulnerable to data poisoning, adversarial manipulation, and model inversion. Quantum computing threatens to render classical cryptography obsolete, while insecure IoT devices and distributed edge nodes amplify systemic risks. Moreover, centimetre-level localisation and behavioural profiling capabilities raise profound privacy concerns that existing regulatory frameworks, such as GDPR and CCPA, are ill-prepared to address. This study examines these multi-layered vulnerabilities and highlights mitigation strategies, including zero-trust architectures, post-quantum cryptography, blockchain-based accountability, and AI-enhanced defences. It further explores societal and policy implications, emphasising the need for international collaboration, ethical AI governance, and security-by-design principles. The findings underscore that the next decade represents a critical window to embed robust cybersecurity and privacy protections in 6G infrastructure, ensuring that the networks underpinning future digital societies are both innovative and trustworthy.

 

 

Author(s) Details

Emma Junior Emmanuel
Department of Computer Science, Prairie View A&M University, United States of America.

 

Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v5/6425

Study of an Innovative Approach to IoT Based Human Activity Recognition | Chapter 19 | Leading the Charge: A Guide to Management, Entrepreneurship and Technology in the Dynamic Business Landscape Edition 1

Recognizing human activities is vital for numerous contemporary applications rooted in the Internet of Things (IoT) framework, spanning from the creation of intelligent video surveillance setups to the advancement of robotic assistants for the elderly. Recently, there has been significant exploration into machine learning algorithms to enhance the recognition of human activities. Despite these research endeavors, there remains a notable dearth of studies focusing on efficiently recognizing complex human activities, particularly those involving transitions, and no research has been conducted to assess the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities, designed to optimize the classification of both transitional and non-transitional human activities. Utilizing unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely-used smartphones, the system effectively identifies human activities [1,2]. The key feature of the proposed system lies in leveraging a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the reliability and accuracy of the proposed system compared to state-of-the-art classifiers, highlighting its robustness in handling noisy data. Human Activity Recognition (HAR) is essential for various modern applications within the Internet of Things (IoT) framework, from developing intelligent video surveillance systems to enhancing robotic assistants for the elderly. Despite significant advancements in machine learning algorithms for HAR, there is a notable lack of research on effectively recognizing complex human activities, particularly those involving transitions, and assessing the impact of noise in training data on algorithm performance. This paper addresses these gaps by presenting an innovative activity recognition system centered on a neural classifier with memory capabilities. Designed to optimize the classification of both transitional and non-transitional human activities, the system employs unobtrusive IoT devices such as accelerometers and gyroscopes integrated into widely used smartphones [1,3]. A key feature of the proposed system is the utilization of a neural network augmented with short-term memory to retain information about preceding activities' characteristics. Experimental validation demonstrates the system's reliability and accuracy compared to state-of-the-art classifiers, emphasizing its robustness in handling noisy data.

 

Author (s) Details

 

Motashim Rasool
Integral University, India.

 

Rizwan Akhtar
Integral University, India.

 

Uvais Ahmad
Integral University, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48859-98-3/CH19

Biomaterials in Architecture, and Biomimicry Principles, as Tools for Envisioning the Sustainable Cities of the Future | Chapter 7 | Emerging Issues in Environment, Geography and Earth Science Vol. 2

 It is widely accepted that the impact of human activities on the Earth's air following the first industrial rebellion was so significant that it was named as a new geological period with the term "Anthropocene." The follow a new design strategy that integrates the type of urban countrysides with their design is critical in the Anthropocene age. Modern instances of green capitals and smart cities are the direct result of the rise of a value structure with a very aesthetic view of worldwide ecosystems, inciting us to seek a non-anthropocentric means of reasoning and, suitable way, planning. In this study, we present creative city design that controls environmental determinants and is based on city planning of downtowns approached for one principles of biomimicry. The research question is either natural fabrics with new construction procedures and biomimicry principles can bring about the design of cities that face the abundant challenges of temperature change. Three examples of downtowns that have adopted the model of biomimicry design standard will be presented, (the city of Lavasa in India, Rocinha squalid district in Rio de Janeiro, and an industrial environment in the Danish city of Kalundborg), in parallel with a article review of natural fabrics. Conclusions will be drawn that will be followed for one formulation of suggestions for the optimal preparation of cities in agreements of sustainability. The goal search out develop a design process point or direct at a goal at the efficient design of centers in response to surroundings change.

Author(s) Details:

Christine Dikou,
Department of Civil Engineering, University of West Attica, Athens, Greece.

Please see the link here: https://stm.bookpi.org/EIEGES-V2/article/view/12194

Iot Technologies: Remote Health Monitoring Systems, Security Risks and Recommendations | Chapter 3 | Novel Research Aspects in Mathematical and Computer Science Vol. 7

 In recent years, IoT technologies have been making headlines. Smart gadgets including smartphones, Internet of Things (IoT) wearables, and automation systems are legendary. Globally, the IoT's new wave of technology has brought about some surprising enchantments. In order to improve quality and strike a balance between efficiency and workability, all industries in the world today, including the healthcare sector, are eager to embrace IoT technologies. From smart cities, supply chains, energy conservation, healthcare, and other areas, IoT has expanded greatly in effectiveness. Among the aforementioned sectors, healthcare is the one that has to advance the most in order to save lives. IoT technology have also revealed a number of difficulties that weren't present before. The capabilities of the Internet of Things, its connection with cloud computing, the applications of IoT in healthcare as well as its drawbacks.

Author(s) Details:

Basant Kumar,
Department of Computer Science, Modern College of Business and Science Muscat, Sultanate of Oman.

Sulaiman Al Rawahi,
Department of Computer Science, Modern College of Business and Science Muscat, Sultanate of Oman.

Abdullah Al Kharusi,
Department of Computer Science, Modern College of Business and Science Muscat, Sultanate of Oman.

Please see the link here: https://stm.bookpi.org/NRAMCS-V7/article/view/7948

Arising Internet of Everything: Business Modeling and Architecture for Smart Cities| Chapter 7 | Recent Developments in Engineering Research Vol. 8

 The Internet has grown into a global marketplace where it is possible to find knowledge on virtually any current product or service. Smart devices and cyber-physical networks interconnected to IT systems and services form the foundation of the evolving Internet of Everything, opening up new economic possibilities beyond its technical dimensions and challenges for its participants and users. While a few centralised online platforms still dominate today's e-business scenarios, potential business models, which would be feasible for the Internet of All, need to meet special requirements. Currently, the quantity of data, as well as the sum of products and services available, in conjunction with potential customizations, is already overstraining users in their quest for the optimum option. According to the theory of adverse selection, this leads to a decision making process. In a highly distributed and competitive world, such business models, for example, exploiting the possibilities of smart cities, need to cope with arbitrary combinations of goods and services orchestrated into complex products. In addition, these arbitrary combinations are affected by real-time background data extracted from sensor networks or IT systems, as well as the demands and expectations of users. The challenge of seeking the ideal combination of product/service overstrains users and According to the theory of adverse selection leads to decisions (i.e., choosing good enough instead of optimal). These e-business models require an adequate architecture of underlying value generation that helps users in this process. We are designing a business model in this chapter that tackles these issues. In addition, we present the software-system architecture of Distributed Market Spaces (DMS) as a potential implementation that makes the aforementioned decentralised and context-centered e-business scenario and leverages the smart cities' commercial possibilities.

Author (s) Details

Mirjana Radonjic-Simic
Baden-Wuerttemberg Cooperative State University, Mannheim 68163, Germany.


Dennis Pfisterer
Institute of Telematics, University of Lübeck, Lübeck 23562, Germany.


Petko Rutesic
Baden-Wuerttemberg Cooperative State University, Mannheim 68163, Germany.


View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/333