The falling cost of IoT cameras, the advancement of AI-based computer vision algorithms,
and powerful hardware accelerators for deep learning have enabled the widespread …

Internet of Things and big data are important technical means to enhance human resilience
to natural hazards in Earth Science. Continuous geospatial data streams generated from in …

Platforms that run artificial intelligence (AI) pipelines on edge computing resources are
transforming the fields of animal ecology and biodiversity, enabling novel wildlife studies in …

Stream processing applications are increasingly de-ployed on hierarchical geo-distributed
edge-cloud environments. Applications in such environments require frequent deployment …

Edge applications generate a large influx of sensor data on massive scales, and these
massive data streams must be processed shortly to derive actionable intelligence. However …

Stream processing is an attractive paradigm for deploying applications in geo-distributed
edge-cloud environments. However, the reverse economics of scale in edge networks and …

With the growth of multi-cloud computing across a heterogeneous substrate of public cloud,
edge, and on-premise sites, observability has been gaining importance in compre-hending …

Edge intelligence has been gaining traction and sophistication. The execution settings may
range from a small cluster as an edge cloud to on-device inference on embedded devices …

The advent of Internet of Things (IoTs) promise significant data growth as devices continue
to proliferate, requiring robust solutions for data management and analysis. Edge …

The falling cost of cameras, the advancement of AI based computer vision algorithms, and
powerful hardware accelerators for deep learning have enabled wide-spread deployment of …