A Review of Artificial Intelligence and Lot Applications in Green Building Design for Economic Sustainability

Abstract

Rapid urbanisation, escalating energy demands, and climate change underscore the urgent need for

sustainable architectural practices that integrate economic and environmental performance. This study critiques the

implementation of Artificial Intelligence (AI) and the Internet of Things (IoT) in green building design (GBD), prioritising

the enhancement of sustainability within an economic context. A convergent parallel mixed-methods design was

employed, involving the concurrent collection of quantitative and qualitative data through structured surveys, post-

occupancy evaluations, field measurements, and semi-structured interviews with professionals in the built

environment, building occupants, and facility managers. Building performance reports, scholarly literature, and

sustainability certifications formed the secondary data. Case studies drawn from Nigeria’s six geopolitical regions were

analysed, citing Nestoil Tower in Lagos State as a significant exemplar of AI- and IoT-driven green design. Metrics of

performance showed that a mean reduction in energy usage (27%) and first-year expenditure gains (64%) optimised

thermal comfort and levels of occupant satisfaction by 68% and 80%, respectively. Analyses of regression and

correlation relationships revealed a high-positive correlation between the adoption of AI/IoT and economic

performance (R² = 0.79; r = 0.82, p < 0.01). Qualitative analyses acknowledged barriers in technology, economic

incentives and policy gaps as critical drivers of adoption. Findings indicate that leveraging AI- and IoT-driven plexuses

such as predictive HVAC controls, automated lighting, and occupancy-responsive management of energy can

notably lower costs of operation, improve life-cycle value, and enhance occupant wellness. Recommendations

propose ingraining AI/IoT templates into national building codes, encouraging smart green high-ends, fostering

professional training, and embedding climate-adaptive, data-powered design approaches into teaching and learning

modules of Architecture. This way, AI- and IoT-enabled green buildings will be appropriately situated as cost-effective,

environmentally sustainable, and resilient solutions, with Nestoil Tower acting as a reproducible framework for

prospective initiatives in Nigeria and other analogous developing economies.