1
| D.WG2-1
| Environmental impact self-check assessment
| Technical Specification
| This document will contain a scorecard for an organization to grade itself on how well they have built a product or service based upon environmental impacts. It will define a set of standard areas to be scored (e.g. power consumption, water consumption, etc.) as well as standardized scoring criteria so that scoring is measured the same across industries and products/services.
| Completed
Download the report here
[Word | PDF]
| Matthew Edgerton,
Accenture
|
2
| D.WG2-2
| Computer processing, data management and energy perspective
| Technical Report
| We live in an era that is defined the “Cambrian explosion of data”, and advanced data analytics (Deep and Machine Learning, mainly) is ready to drive us in this world. The volume of data produced hourly and daily is enormous and is intended to dramatically increase in the next years –just consider the IoT revolution. Data centers of the future will be data driven. A clear limiting factor is their energy consumption. Presently, data centers consume more power than several European Union Member States, producing a larger footprint than all aircrafts. For these reasons, innovative strategies and technological solutions are needed to allow a scalability that is essential to enable and support the AI revolution. The document aims at recognizing important areas of innovation addressing this issue and facilitating the AI uptake by our Society.
| Completed
Download the report here
[Word | PDF]
| Stefano Nativi, European Commission
|
3
| D.WG2-3
| Requirements on energy efficiency measurement models and the role of AI and big data
| Technical Report
| This document focuses on
the impact of AI and big data on energy efficiency. It identifies a model that can calculate the energy efficiency in an urban space, from
an AI and big data perspective. It uncovers the requirements for energy efficiency assessment, and features affecting energy demand. This document also defines a unified assessment model for energy efficient cities.
| Completed
Download the report here
| Leonidas Anthopoulos, University of Thessaly
|
4
| D.WG2-4
| Effective use cases on artificial intelligence for smart sustainable cities
| Technical Report | This document will present effective use cases of technologies that contribute to sustainable smart cities.
| Completed
Download the report here
[Word | PDF]
| Abdelnasser Abdelaal, King Faisal University, Saudi Arabia
|
5
| D.WG2-5
| Guidelines on Energy Efficient Blockchain Systems
| Technical Specification
| This document focuses on the impact
of blockchain on energy efficiency. It provides an overview of blockchain's energy demand and consumption, defines blockchain's energy model and describes a set of energy efficiency parameters that can be calibrated in
order to enhance blockchain's energy efficiency.
| Completed
Download the report here
[Word | PDF]
| Leonidas Anthopoulos, University of Thessaly |
6
| D.WG2-6
| Assessing Environmentally Efficient Data Centre and Cloud Computing in the framework of the Sustainable Development Goals (SDGs)
| Technical Report | This document aims to conduct an environmental sustainability assessment, encompassing the entire life cycle and factoring in a broad spectrum of energy and environmental problems that are needed to support the development of sustainably efficient data centres and cloud computing services. The documents proposes a multi-impact and life cycle approach and include the following aspects:
- An assessment of environmental impacts of data centre and cloud computing through a life cycle approach
- A mapping of available sustainability and energy measurements of data centre and cloud computing
An analysis on the links to the 17 SDGs with breakdown indicators being evaluated
A gap analysis of policies that facilitating the development of environmentally efficient data centre and cloud in support of the achievement of the Paris agreement and the UN SDGs A policy gap analysis of policies that facilitating the development of environmentally efficient data centre and cloud in support of the achievement of the Paris agreement and the UN SDGs - Conclusions
| Completed
Download the report here
[Word | PDF]
| Paolo Bertoldi & Tiago Serrenho
European Commission, Joint Research Centre
|
