28 citations · 56 across the 17 of their papers we have counts for
18 papers
The More the Merrier? Navigating Accuracy vs. Energy Efficiency Design Trade-Offs in Ensemble Learning Systems
Rafiullah Omar, Justus Bogner, Henry Muccini +3
Background: Machine learning (ML) model composition is a popular technique to mitigate shortcomings of a single ML model and to design more effective ML-enabled systems. While ense…
How to Sustainably Monitor ML-Enabled Systems? Accuracy and Energy Efficiency Tradeoffs in Concept Drift Detection
Rafiullah Omar, Justus Bogner, Joran Leest +3
ML-enabled systems that are deployed in a production environment typically suffer from decaying model prediction quality through concept drift, i.e., a gradual change in the statis…
A Synthesis of Green Architectural Tactics for ML-Enabled Systems
Heli Järvenpää, Patricia Lago, Justus Bogner +3
The rapid adoption of artificial intelligence (AI) and machine learning (ML) has generated growing interest in understanding their environmental impact and the challenges associate…
The BET project: Behavior-enabled IoT
Henry Muccini, Barbara Russo, Eugenio Zimeo
IoT is changing the way Internet is used due to the availability of a large amount of data timely collected from every-day life objects. Designing applications in this new scenario…
Modeling Data Analytics Architecture for Smart Cities Data-Driven Applications using DAT
Moamin Abughazala, Henry Muccini
Extracting valuable insights from vast amounts of information is a critical process that involves acquiring, storing, managing, analyzing, and visualizing data. Providing an abstra…
Data Architecture for Digital Object Space Management Service (DOSM) using DAT
Moamin Abughazala, Henry Muccini
The Internet of Things (IoT) data and social media data are two of the fastest-growing data segments. Having high-quality data is crucial for making informed business decisions. Th…