Department of Architecture

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Author: search.filters.author.Ene, Vincent Onyedikachi

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    Design of a Therapeutic Student Centre in Covenant University, Ota, Nigeria: User-Centred Approach
    (2024) Babalola, Daniel Olatunde; Sholanke, Anthony Babatunde; Adewale, B. A.; Ene, Vincent Onyedikachi
    This qualitative study addresses the pressing need for a therapeutic and supportive student center at Covenant University, Nigeria, to tackle escalating mental health concerns and the absence of dedicated well-being spaces on campus. Through semi-structured interviews with 100 undergraduate and postgraduate students, it gathers comprehensive insights into their needs, preferences, and perspectives regarding such a center. Employing a combined inductive-deductive approach to thematic analysis, grounded in trustworthiness strategies like prolonged engagement and member checking, key findings underscore the importance of natural lighting, private comfortable rooms, counseling services, art activities, and a welcoming atmosphere. These insights directly shape recommendations for the center's layout, furniture, services, and stigma-reduction campaigns. The study's rigorous methodology, emphasizing trustworthiness, highlights its contribution to capturing authentic student voices and translating them into actionable recommendations. Acknowledging limitations, such as cultural specificity, it calls for future cross-cultural studies and architectural expertise integration. By centering on students’ perspectives, this research advances discourse on therapeutic architectural design's mental health impact, offering a model for higher education institutions to co-create supportive, user-centered spaces prioritizing holistic well-being
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    An Assessment of the Implementation of Green Design Strategies in Selected Museums in Abuja, Nigeria
    (Civil Engineering and Architecture e 12(3A), 2024) Adewale, B. A.; Ene, Vincent Onyedikachi
    This study evaluates the implementation of green design strategies in selected museums in Abuja, Nigeria to inform sustainable approaches tailored to the local context. The qualitative study utilizes observational assessments of 3 major museums – Discovery Museum, Nike Art Gallery, and Retro Africa Gallery. A comparative analysis investigates the adoption of passive design, alternative energy, and water efficiency strategies based on a structured criterion aligned with global sustainability standards. The findings reveal a moderate integration of fundamental techniques like proper orientation, thermal mass walls, solar PV panels, and native drought-resistant plants across the museums. However, substantial gaps exist in implementing more comprehensive solutions like building insulation, greywater recycling, rain gardens, eco fixtures, and real-time metering. While initial steps have been taken, holistic opportunities remain to transform the museums into genuinely sustainable, net-zero facilities through extensive daylighting, diverse renewable systems, and total water recycling. The Retro Africa Gallery emerges as a leader, exemplifying an integrated green design approach. Recommendations are provided focused on state-of-the-art passive design, diversified alternative energy generation, and closed-loop water conservation strategies tailored to the contextual needs of Nigerian museums. The study concludes these institutions can become inspiring models of ecological design, leading broad climate action through pioneering sustainable architecture.
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    Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review
    (Preprints, 2024) Adewale, B. A.; Ene, Vincent Onyedikachi; Ogunbayo, Babatunde Fatai; Aigbavboa, Clinton Ohis
    With buildings accounting for a significant portion of global energy consumption and greenhouse gas emissions, the application of artificial intelligence (AI) holds promise for enhancing sustainability in the building lifecycle. This systematic literature review addresses the current understanding of AI’s potential to optimize energy efficiency and minimize environmental impact in building design, construction, and operation. A comprehensive literature review and synthesis were conducted to identify AI technologies applicable to sustainable building practices, examine their influence, and analyze the challenges of implementation. The review was guided by a meticulous search strategy utilizing keywords related to AI application in sustainable building design, construction, and operation. The findings reveal AI’s capabilities in optimizing energy efficiency through intelligent control systems, enabling predictive maintenance, and aiding design simulation. Advanced machine learning algorithms facilitate data‐driven analysis and prediction, while digital twins provide real‐time insights for informed decision‐making. Furthermore, the review identifies barriers to AI adoption, including cost concerns, data security risks, and challenges in implementation. AI presents a transformative opportunity to enhance sustainability in the built environment, offering innovative solutions for energy optimization and environmentally conscious practices. However, addressing technical and practical challenges will be crucial for the successful integration of AI in sustainable building practices.