Journal of Intelligent Computing, Digital Technologies and New Media Systems

Integration of Building Information Modeling (BIM) with Artificial Intelligence for Real-time Cost Estimation in Megaprojects

2026-06-08T00:05:18+00:00

The increasing complexity of megaprojects has intensified the need for more efficient and accurate cost estimation systems within the construction industry. Conventional quantity surveying methods are often characterized by manual calculations, fragmented information management, and delayed cost reporting, which contribute to budget overruns and poor financial decision-making. Building Information Modelling (BIM) has improved digital coordination in construction projects by enabling integrated project visualization and automated quantity extraction. More recently, Artificial Intelligence (AI) technologies have been introduced into BIM environments to support intelligent data processing, automated classification, and predictive cost analysis. This study investigates the integration of AI with BIM for real-time cost estimation in megaprojects. A mixed-methods research design was adopted, involving comparative analysis of documented project case studies and semi-structured interviews with industry professionals. The findings reveal that AI-assisted BIM systems improve estimation efficiency, reduce manual errors, and enhance coordination between design and commercial teams. However, challenges relating to data standardization, interoperability, implementation costs, and workforce competence continue to affect adoption. The study concludes that AI-enabled BIM systems have significant potential to improve quantity surveying and commercial management practices when supported by appropriate digital standards and organizational readiness.

Digital Transformation and Governance Reform in Public Sector Institutions: A Conceptual Review of ICT Adoption and Institutional Performance in Developing Economies

2026-06-10T03:49:50+00:00

Digital transformation has become a central pillar of public sector reform across both developed and developing economies. Governments increasingly rely on Information and Communication Technology (ICT) to enhance transparency, efficiency, accountability, and service delivery. However, despite widespread adoption efforts, many public institutions in developing countries continue to experience implementation gaps, structural resistance, and limited performance gains. This paper presents a conceptual review of ICT adoption within public sector governance, synthesizing existing theoretical and empirical literature to explain how digital transformation influences institutional reform and performance outcomes. Drawing on institutional theory, the Technology Acceptance Model, and public value theory, the paper develops a conceptual framework linking ICT adoption to governance efficiency, employee responsiveness, and service delivery quality. The study further identifies key barriers including infrastructural deficits, organizational culture, and policy inconsistency that hinder effective digital transformation. The paper concludes by proposing an integrated model for sustainable ICT-driven governance reform in developing economies and offers implications for policymakers and future research.

Ethical and safety implications of artificial intelligence-driven surveillance on construction sites in Nigeria: a case study approach

2026-07-16T01:40:11+00:00

In Nigeria today, there is a significant shift happening in the construction industry in Nigeria due to the rising use of technologies associated with Artificial Intelligence (AI), which are designed to improve productivity, efficiency, and safety performance. Surveillance technologies that involve computer vision, smart cameras, drones, sensors, machine learning, and predictive analytics become more and more popular among construction project managers. Certain opportunities exist for the application of those technologies in order to detect threats, observe behavior, prevent accidents and make sure that the safety regulations are adhered to. However, the use of AI surveillance technologies poses many ethical and safety concerns about the protection of privacy, worker autonomy, data ownership, algorithmic bias, cyber-security, and the creation of highly monitored workplaces. The paper explores the ethical and safety issues raised by the implementation of AI-based surveillance systems at construction sites. This research will analyze the connection between technological innovation and responsible safety management from the perspective of construction professionals, employees, and organizational stakeholders. This research is based on the qualitative methodology with the use of case studies along with a literature review, which will include information on the use of artificial intelligence, construction safety management, workplace surveillance, and responsible governance of technology. It has been found that artificial intelligence-based workplace surveillance has a huge potential for improving construction safety as a result of hazards early detection, predictive risk assessment, and regulatory compliance. But at the same time, the lack of responsible ethical frameworks can harm the trust of workers, raise issues about the breach of their privacy, as well as increase problems related to transparency and accountability. The research findings highlight the need to apply a human-centered approach to the use of artificial intelligence in construction, meaning that technologies should be used to help professionals and workers in making decisions

Artificial intelligence and the revitalization of the Yoruba language: prospects, challenges, and digital sustainability in Nigeria

2026-07-16T02:52:54+00:00

This study examined the role of Artificial Intelligence (AI) in the revitalization, preservation, and digital sustainability of the Yoruba language in Nigeria. The study adopted a qualitative descriptive research design because it focused on exploring existing scholarly perspectives, technological developments, and digital preservation strategies associated with AI-driven indigenous language revitalization. Data were obtained from secondary sources, including peer-reviewed journal articles, books, conference proceedings, policy documents, institutional reports, and publications from international organizations such as UNESCO. Materials published between 2018 and 2026 were selected to ensure relevance and alignment with contemporary technological advancements. The study employed content analysis to identify and interpret recurring themes relating to AI technologies, Yoruba language preservation, digital sustainability, opportunities, and implementation challenges. Findings revealed that AI-driven technologies such as Natural Language Processing (NLP), machine translation systems, speech recognition applications, chatbots, digital dictionaries, predictive text systems, and language-learning platforms possess significant potential for strengthening Yoruba language revitalization. The study further revealed that AI can enhance language accessibility, documentation, learning, cultural preservation, and digital participation among younger generations. However, challenges such as inadequate funding, limited digital corpora, insufficient technological infrastructure, poor policy implementation, and weak collaboration among stakeholders continue to hinder effective integration of AI into Yoruba language development. The study concludes that AI has become a strategic tool for ensuring the survival and digital relevance of the Yoruba language in contemporary society. It recommends increased investment in indigenous language technologies, corpus development, educational integration, and collaborative partnerships among linguists, software developers, policymakers, and cultural organizations to ensure the long-term digital sustainability of the Yoruba language in Nigeria

Public Perception on the Role of the Media in Nigeria’s Electoral Reforms in South-South Nigeria

2026-07-17T09:38:30+00:00

This study examined public perception of media coverage of electoral reforms in South-South Nigeria. Elections in Nigeria have historically been characterized by electoral malpractice, violence, rigging, and political manipulation, thereby necessitating continuous electoral reforms to strengthen democratic governance. The study specifically investigated the level of media attention to electoral reform issues, public perception of media contents on electoral reforms, public perception of media contributions to electoral reforms, and the level of public acceptance of media contents on electoral reforms in South-South Nigeria. The study adopted the Rational Choice Theory and Media Framing Theory as its theoretical foundations. A cross-sectional survey research design was employed, while the Krejcie and Morgan table was used to determine a sample size of 384 respondents through a multi-stage sampling procedure. Data collected were analyzed using descriptive and inferential statistics, including percentages, tables, and regression analysis. Findings revealed that the public in South-South Nigeria has a high level of confidence in media coverage of electoral reforms. The study further showed that media coverage has significantly increased public interest in political issues and intensified public calls for reforms in Nigeria’s electoral system. It was also found that the public perceives media contributions to electoral reforms positively and generally accepts media contents relating to electoral reforms. The study concluded that the media play a vital role in promoting awareness, political participation, and democratic consolidation in Nigeria. It therefore recommended that media practitioners sustain objective, credible, and consistent reportage of electoral reform issues to strengthen public trust and democratic development in Nigeria

Digital Twin Synchronization Strategies for Real-Time Control of Distributed Production Networks

2026-07-18T17:38:32+00:00

Digital twin synchronization is central to reliable real-time control in distributed production networks, yet current implementations remain constrained by latency, state inconsistency, heterogeneous data structures, limited scalability, cybersecurity exposure, and weak industrial validation. This review critically examines the conceptual foundations, architectures, performance metrics, synchronization strategies, control mechanisms, applications, and research gaps associated with physical–virtual alignment across geographically dispersed manufacturing systems. The reviewed strategies comprise time-driven, event-driven, hybrid, edge–cloud coordinated, AI-driven predictive, and blockchain-based synchronization. Their suitability depends on the required balance among update frequency, state accuracy, communication delay, computational burden, data consistency, security, and control criticality. Evidence from manufacturing, robotics, logistics, energy-aware production, and multi-plant coordination shows that effective synchronization can support closed-loop control, adaptive scheduling, predictive maintenance, resource allocation, energy optimisation, and disturbance response. However, no single strategy performs optimally under all operating conditions. Fixed updates may waste resources, event-triggered methods may overlook gradual drift, predictive approaches remain vulnerable to model error, and secure consensus mechanisms may introduce unacceptable delay. The review therefore positions synchronization as a first-class control and systems-engineering problem rather than a secondary data-management function. Future research should prioritise self-adaptive and uncertainty-aware synchronization, deterministic low-latency communication, causal and federated twin architectures, energy-efficient computing, secure governance, standardised metrics, shared benchmarks, and long-term industrial field validation. These advances are required to move digital twins from passive monitoring tools to dependable operational intelligence systems for distributed manufacturing