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7 months ago User Story: As a faculty member, I want an AI-driven system that can analyse historical data to predict peak times for library usage, allowing me to better plan my lectures and allocate resources efficiently.
Must: This AI-driven system is crucial for optimizing lecture planning and resource allocation in academic environments, addressing a key need in modern educational settings.
High Value: The system offers substantial benefits by enhancing the efficiency and quality of educational planning and resource management, directly impacting the academic experience.
High Risk: The project involves significant risk due to the complexities of accurately implementing AI for predictive analytics in a dynamic and unexplored academic context.
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AI in University Libraries: AI has significantly impacted university libraries, notably in enhancing information retrieval efficiency. By analysing vast data and user behaviour, AI systems generate more relevant search results. This is a step towards the kind of predictive analytics we're interested in, as it involves understanding and predicting user needs and behaviours. Furthermore, AI in libraries is also being used for intelligent resource management, which includes analysing usage patterns and predicting future demands for resources. This aligns closely with our goal of predicting peak library usage times https://librarynews.blog.fordham.edu/2023/05/23/the-future-of-libraries-ai-and-machine-learning/
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AI-Powered Patron Assistance and Data Analytics: AI technologies are increasingly being used in libraries for patron assistance and data analytics. This includes the use of AI-powered chatbots and algorithms that can provide insights into resource utilization. These systems can analyse usage patterns and could potentially be adapted to predict peak usage times for library resources. The evolution of these AI applications suggests a growing capability in handling and interpreting complex usage data, which is essential for our project https://the-digital-librarian.com/2023/01/23/artificial-intelligence-in-the-library/
- Applications Beyond Current Use: While the direct application of AI in predicting peak library times in libraries isn't extensively documented, the existing use cases of AI in library settings for data analysis, user behaviour understanding, and resource management provide a solid foundation. Our project could build on these existing applications, using AI to analyse historical usage data and predict peak times, thus aiding faculty members in planning their lectures and resource allocation more efficiently.
As a faculty member, I want an AI-driven system that can analyse historical data to predict peak times for library usage, allowing me to better plan my lectures and allocate resources efficiently.
Definition of Done (DoD): 4 examples of solutions of AI systems that can be used to predict footfall.