Akademska digitalna zbirka SLovenije - logo
ALL libraries (COBIB.SI union bibliographic/catalogue database)
  • On-premise artificial intelligence as a service for small and medium size setups [Elektronski vir]
    Fortuna, Carolina ...
    Artificial Intelligence (AI) technologies are moving from customized deployments in specific application domains towards generic solutions horizontally permeating vertical domains and industries. For ... instance, decisions on when to perform maintenance of roads or bridges, or how to optimize public lighting in view of costs and safety in smart cities are increasingly informed by AI models. With new services introduced to smart cities, and the increasing amount of data collected thereof, the in-time decision support will require the transition from developing mostly static AI models to so called AI as a Service (AIaaS) approach. Various commercial solutions, typically deployed in public cloud, already offer user friendly and easy to use AIaaS, functionality-wise enabling the democratization of such ecosystems. However, open-source equivalent ecosystems supporting private deployment for better control over data, processes and costs, where this is needed, are lagging behind, mostly because they require different sets of advanced skills to select and integrate the most suitable technologies for a given application area. In this chapter, we discuss AIaaS functionality and corresponding technology stack and analyze possible realizations using open source user friendly technologies that are suitable for on-premise small and medium sized setups allowing full control over the data and technological platform without any third-party dependence or vendor lock-in.
    Source: Advances in engineering and information science toward smart city and beyond [Elektronski vir] (Str. 53-73)
    Type of material - e-article ; adult, serious
    Publish date - 2023
    Language - english
    COBISS.SI-ID - 154298371

    Link(s):

    https://link.springer.com/chapter/10.1007/978-3-031-29301-6_3
    DOI

Shelf entry