Mohamed Al-Hussein

dblp:70/5012 · DBLP profile ↗
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7ranked-venue papers
0as first author
4since 2021 · last 2026
0000-0002-1774-9718ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 5 · 3 since 2021Artificial intelligence and machine learning · 2 · 1 since 2021
YearPublicationVenuePosition
2026 Stochastic production scheduling in modular construction: A digital twin case study of a wood framing machine
Djamel Eddine Touil, Jordan Kolb, Ahmed Bouferguene, Yasser Mohamed, Mohamed Al-Hussein, Simaan M. AbouRizk
Adv. Eng. Informatics5
2026 A multi-user game-based system for planning modular construction activities
abstract
Supply chain (SC) planning in modular construction (MC) can be challenging because it requires interconnected and complex activities among various teams and across different project stages. Recently, game engines have been increasingly used to resolve these challenges, as they create realistic virtual environments and simulations of possible scenarios before actual project implementation. However, game engine applications have been restricted to single-user and centralized models, limiting real-time collaboration among MC teams. Within a Design Science Research methodology, this study proposes an intelligent game-based modular planning (GAMMOD) system, supported by multi-user functions, which is flexible in terms of access, allowing for either non-immersive or immersive mode, depending on the available hardware tools, for collaborative planning of the MC-SC. The GAMMOD system integrates a blockchain protocol for data security in the non-immersive mode, while the immersive mode relies on user credentials authorization. The GAMMOD system considers both numerical key performance indicators, such as sustainability, cost, and time, as well as practical ones, including road dimensions, module clearance, and possible clashes. Two distinct case studies, representing different MC types, are presented to illustrate the features of the GAMMOD system. The evaluation tests of the GAMMOD system conducted by 14 MC experts have shown a general consensus on its functionality, with 80% to 100% of the participants agreeing or strongly agreeing on the GAMMOD system’s performance. Additionally, the GAMMOD system demonstrated a usability score of 75.7, surpassing the established threshold of 70. The GAMMOD system is expected to help MC stakeholders make informed, collaborative decisions and develop a shared understanding of decision feasibility, potential conflicts, and constraints before the commencement of the MC project.
Mohamed Assaf, Sena Assaf, Mohamed Al-Hussein
Expert Syst. Appl.4
2022 A machine learning approach to predict production time using real-time RFID data in industrialized building construction
Osama M. Mohsen, Yasser Mohamed, Mohamed Al-Hussein
Adv. Eng. Informatics3
2022 Vision-based method for semantic information extraction in construction by integrating deep learning object detection and image captioning
Ahmed Bouferguene, Mohamed Al-Hussein
Adv. Eng. Informatics4
2020 Improvement of transportation cost estimation for prefabricated construction using geo-fence-based large-scale GPS data feature extraction and support vector regression
SangJun Ahn, SangUk Han, Mohamed Al-Hussein
Adv. Eng. Informatics3
2018 Design of a Saw Cutting Machine for Wood and Aluminum
Jawad Ul Haq, Ahmed-Jawad Qureshi, Mohamed Al-Hussein
ICINCO (2)3
2016 Ontology-based semantic approach for construction-oriented quantity take-off from BIM models in the light-frame building industry
Hexu Liu, Ming Lu 0005, Mohamed Al-Hussein
Adv. Eng. Informatics3