Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …

Demographic changes in peripheral areas are pressuring the regional public transport
systems to adopt innovative strategies. The employment of internet of things (IoT) …

Operating data-intensive applications on edge systems is challenging, due to the extreme
workload and device heterogeneity, as well as the geographic dispersion of compute and …

Recent studies have demonstrated that mobile sampling can improve the spatial granularity
of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (< …

Recent theoretical and methodological advances in urban sociology, including spatially
located data, provide new opportunities to consider the joint influence of mobility and place …

This paper presents faas‐sim, a simulation framework tailored to serverless edge computing
platforms. In serverless computing, platform operators are tasked with efficiently managing …

This paper presents Eclipse, a platform for low-cost urban environmental sensing using
solar-powered and cellular-connected devices. Dense sensor networks promise to monitor …

The integration of the Internet of Things (IoT) and Distributed Computing Systems (DCS) is
transforming business models across industries. IoT devices allow immediate monitoring of …

Applications incorporating DNN-based visual analytics are growing in demand. This class of
data-intensive and latency-sensitive workloads has an opportunity to benefit from the …

The space of Internet-of-things has exploded, with billions of interconnected devices ranging
from mainframes to refrigerators and thermostats. These devices offer the promise of greater …