Project Management Predictive Framework

dc.contributor.authorDasanya, S
dc.contributor.authorSamarakoon, K
dc.contributor.authorPerera, S
dc.contributor.authorTennakoon, K
dc.contributor.authorAttanayaka, B
dc.contributor.authorKahandawaarachchi, C
dc.date.accessioned2026-11-01T09:18:33Z
dc.date.issued2025-12-09
dc.description.abstractProject Planning is a critical phase in the software project management cycle. Traditional project management tools rely heavily on manual processes and do not provide accurate insights for the planning phase. This research focuses on developing an advanced software project management solution that utilises machine learning and AI technologies to enhance and provide accurate results. The system will automatically generate tasks from user stories, accurately estimate effort, budget, and identify risks. It also assesses team members' skills for an accurate task assignment and assignments and predicts infrastructure resource needs, suggesting cost-effective options to optimise resource use.
dc.identifier.citationS. Dasanya, K. Samarakoon, S. Perera, K. Tennakoon, B. Attanayaka and C. Kahandawaarachchi, "Project Management Predictive Framework," 2025 7th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2025, pp. 1-6, doi: 10.1109/ICAC69156.2025.11361461.
dc.identifier.doidoi: 10.1109/ICAC69156.2025.11361461
dc.identifier.isbn979-833156222-9
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/5403
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofseriesICAC 2025 - 7th International Conference on Advancements in Computing: The Future of Computing; AI, Quantum, and Beyond
dc.subjectBudget Prediction
dc.subjectHuman and Infrastructure Resource Allocation
dc.subjectJob Role Effort Estimation
dc.subjectTask Generation
dc.titleProject Management Predictive Framework
dc.typeConference Paper

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