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Leveraging NVIDIA AI technologies in the development of REQAPP: a machine learning platform for gathering and defining requirements for smart cities applications

Author

Listed:
  • Andra Paula AVASILOAIE

    (POLITEHNICA Bucharest)

  • Augustin SEMENESCU

    (POLITEHNICA Bucharest)

  • Eduard Cristian POPOVICI

    (POLITEHNICA Bucharest)

  • Razvan CRACIUNESCU

    (POLITEHNICA Bucharest)

  • Ionut Cosmin CHIVA

    (POLITEHNICA Bucharest)

Abstract

This paper introduces REQAPP, an innovative machine learning (ML)-powered platform utilizing NVIDIA AI technologies, such as Retrieval-Augmented Generation (RAG) chatbots, to optimize the elicitation and definition of software requirements. The platform is designed for smart city applications, including e-government, social innovation, urban planning, and urban development. REQAPP addresses the challenge of accurately gathering and refining user needs, especially for complex public sector projects, by learning and adapting from iterative interactions. The study builds on advancements in requirement engineering and the integration of ML in software development. By leveraging NVIDIA AI frameworks and tools, it extends existing research on adaptive learning systems and interactive AI solutions to meet the unique needs of smart city stakeholders. The development and evaluation of REQAPP are demonstrated through four case studies, each focusing on a distinct application domain, such as online stores, ticket booking systems, resource-sharing platforms, and urban planning tools. Using NVIDIA AI technologies, including RAG chatbots, the platform offers a conversational interface that guides users through the requirements elicitation process while dynamically refining its models based on feedback and context. The results showcase REQAPP’s ability to reduce ambiguity in requirement definitions and improve user engagement. The incorporation of RAG chatbots enhances the system's capacity to provide accurate and context-aware suggestions, accelerating the requirements gathering process and ensuring alignment with stakeholder expectations. REQAPP presents a significant advancement for academics, practitioners, and policymakers involved in smart city projects. This study contributes to the field by introducing an original AI-driven framework that combines state-of-the-art NVIDIA technologies with a machine learning-centric approach. REQAPP’s adaptability and focus on real-world smart city applications make it a valuable tool for future AI-enhanced development processes.

Suggested Citation

  • Andra Paula AVASILOAIE & Augustin SEMENESCU & Eduard Cristian POPOVICI & Razvan CRACIUNESCU & Ionut Cosmin CHIVA, 2024. "Leveraging NVIDIA AI technologies in the development of REQAPP: a machine learning platform for gathering and defining requirements for smart cities applications," Smart Cities International Conference (SCIC) Proceedings, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 12, pages 465-480, september.
  • Handle: RePEc:pop:procee:v:12:y:2024:465-480
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    References listed on IDEAS

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    1. Stefano CARBONI, 2024. "Smart Cities in comparison: An analysis of the best Smart Cities," Smart Cities and Regional Development (SCRD) Journal, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 8(3), pages 65-78, April.
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    JEL classification:

    • O35 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Social Innovation

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