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Shamsudeen Musa

Publications (8)

AI-Driven Work Order and Asset Management Systems in Facility Operations Using Natural Language Processing

Shamsudeen Musa, Abass J. O, Obaju B. N. & Babalola A. A. · Asian Journal of Research in Computer Science · 2025

Manual work orders and asset management systems often result in delays, inefficiencies, and communication errors in facility operations. This study proposes an AI-driven framework that employs Natural Language Processing (NLP) to automate the classification, prioritisation, and p...

Open access Research Article 10.9734/ajrcos/2025/v18i8742

A Machine Learning Framework for Predictive Maintenance in Smart Facilities Using IoT Sensor Data

Shamsudeen Musa, Abass J. O. & Obaju B. N. · Journal of Engineering Research and Reports · 2025

Background: The integration of smart technologies into modern facilities has underscored the need for proactive maintenance strategies to minimize unplanned equipment failures and enhance operational efficiency. Traditional maintenance approaches, including reactive and time-base...

Open access Research Article 10.9734/jerr/2025/v27i81601

The Effect of Technology Adoption on the Profitability of Construction Businesses: A Qualitative Evaluation of Present Trends in Developing Nations

Shamsudeen Musa, Babalola Anthony Ayotunde, Aina Yetunde Josephine & Abass Jimoh Owolabi · Asian Research Journal of Arts & Social Sciences · 2024

This study examined the impacts of technology adoption on the profitability of construction businesses. A theoretical approach was used to identify various construction companies adopting different technologies. The qualitative component of the survey research method was employed...

Open access Research Article 10.9734/arjass/2024/v22i7555

Energy Optimization in Smart Buildings Using Deep Q-Network-based Reinforcement Learning

Abass J. O, Shamsudeen Musa & Obaju B. N. · Asian Journal of Advanced Research and Reports · 2025

The rapid expansion of smart building technologies demands innovative solutions to optimize energy consumption while preserving comfort. Traditional rule-based and supervised learning approaches often lack adaptability to dynamic environmental conditions, leading to inefficiencie...

Open access Research Article 10.9734/ajarr/2025/v19i81114

An Evaluation of Built Environment Students’ Training in Building Maintenance (A Case Study of Federal Polytechnics in Osun State, Nigeria)

B. N. Obaju, Shamsudeen Musa, J. O. Abass & A. A. Babalola · Asian Research Journal of Arts & Social Sciences · 2022

Aims: This study is aimed at evaluating the training acquired by built environment students in maintenance courses to determine areas of training inadequacy and improvements. This is achieved by identifying of learning outcomes in maintenance courses acquired by built environment...

Open access Research Article 10.9734/arjass/2022/v18i130323

Assessment of Students’ Experience on Industrial Training Program in Polytechnic Sector: A Case Study of Some Selected Polytechnics in Osun State, Nigeria

B. N. Obaju, Shamsudeen Musa & J. O. Abass · Journal of Education, Society and Behavioural Science · 2022

Industrial training is a program that aims to provide supervised training within a particular time frame which can be carried out either in the private sector or in government organizations. The purpose of this study is to evaluate the students experience in industrial training p...

Open access Research Article 10.9734/jesbs/2022/v35i730445

The Effect of Knowledge Management Practices on Enhancing Construction Industry Performance in Nigeria

Aina Yetunde Josephine, Babalola Anthony Ayotunde, Shamsudeen Musa & Abass Jimoh Owolabi · South Asian Journal of Social Studies and Economics · 2024

This study aims to assess the impact of knowledge management practices on process improvement in a contracting firm in Lagos State to enhance the overall performance of the construction industry in Nigeria. The study surveyed 159 registered construction firms in Lagos State. Desc...

Open access Research Article 10.9734/sajsse/2024/v21i8872