Integrating Advanced Analytics for Sustainable Technology and Energy Management

The recent developments in the research area of sustainable technology and energy management have shown a significant shift towards integrating advanced analytics and machine learning techniques to optimize resource utilization and reduce environmental impact. A notable trend is the use of recommender systems and reinforcement learning to influence consumer behavior and decision-making processes, aiming to promote sustainable practices. Additionally, there is a growing focus on the environmental consequences of digital technologies, such as Bitcoin mining, and efforts to mitigate these impacts through innovative solutions and policy interventions. The field is also witnessing advancements in the application of time series foundation models for building energy analytics, which promise to enhance the accuracy of energy forecasting and management. Furthermore, the integration of renewable energy sources and the development of carbon-aware real-time workload management frameworks in cloud systems are emerging as key strategies to balance technological innovation with sustainability goals. Overall, the research is moving towards creating more holistic and data-driven approaches to address the complex challenges of sustainable development in the digital age.

Sources

Do Data Center Network Metrics Predict Application-Facing Performance?

Why has advanced commercial HVAC control not yet achieved its promise?

ElectricityEmissions.jl: A Framework for the Comparison of Carbon Intensity Signals

The Unintended Carbon Consequences of Bitcoin Mining Bans: A Paradox in Environmental Policy

A Framework for Carbon-aware Real-Time Workload Management in Clouds using Renewables-driven Cores

Advancing Sustainability via Recommender Systems: A Survey

Everything You Wanted to Know About Consumer Light Management in Smart Energy

Recommender systems and reinforcement learning for building control and occupant interaction: A text-mining driven review of scientific literature

Exploring Capabilities of Time Series Foundation Models in Building Analytics

Balancing Innovation and Sustainability: Addressing the Environmental Impact of Bitcoin Mining

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