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CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities
As more distributed energy resources become part of the demand-side infrastructure, it is important to quantify the energy flexibility they provide on a community scale, particularly to understand the impact of geographic, climatic, and occupant behavioral differences on their effectiveness, as well as identify the best control strategies to accelerate their real-world adoption.
EnergAIze: Multi Agent Deep Deterministic Policy Gradient for Vehicle to Grid Energy Management
This paper investigates the increasing roles of Renewable Energy Sources (RES) and Electric Vehicles (EVs).
From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
The emergence of smart cities demands harnessing advanced technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) and promises to unlock cities' potential to become more sustainable, efficient, and ultimately livable for their inhabitants.
Constrained Adversarial Learning and its applicability to Automated Software Testing: a systematic review
Every novel technology adds hidden vulnerabilities ready to be exploited by a growing number of cyber-attacks.
An IoT Cloud and Big Data Architecture for the Maintenance of Home Appliances
Billions of interconnected Internet of Things (IoT) sensors and devices collect tremendous amounts of data from real-world scenarios.
A Multi-Policy Framework for Deep Learning-Based Fake News Detection
Connectivity plays an ever-increasing role in modern society, with people all around the world having easy access to rapidly disseminated information.
