In the rapidly evolving landscape of IoT-Edge-Cloud continuum (IECC), effective management of computational tasks offloaded from mobile devices to edge nodes is crucial.

The term ‘Dynamic Heterogeneous Computing Sphere’ is used to describe a computing paradigm that is heterogeneous, volatile and highly dynamic.

In recent years, the development and refinement of artificial intelligence (AI) technologies have revolutionised various fields, including computer vision.

A proposal for a predictive analysis model for bike-sharing systems based on a mixed model of statistical and machine-learning approaches.The model assumes a Poisson distribution on bike station arrival and departures.