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Collective intelligence for community energy initiatives.

Cavero, Jose; Kortuem, Gerd and Wolff, Annika (2015). Collective intelligence for community energy initiatives. In: Encouraging Collective Intelligence for the Common Good: , 28 June 2015, Limerick, Ireland.

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Abstract

In this paper we present an approach aimed at overcoming barriers to the success of community energy initiatives in urban areas. The proposed methods will support communities in identifying and adopting community energy solutions by connecting citizens with a collection of relevant datasets including satellite, energy and socio-economic data. Citizens will be provided with the ability to explore the data and with advanced urban data analytics methods to identify key aspects and potential areas where initiatives could be successful. Communities will be supported with advice and expertise and in identifying dedicated and enthusiastic participants. To meet all these requirements is a difficult task, but the benefits include: reduction of carbon emissions, generation of savings for communities, reduction of fuel poverty and creation of local jobs.
The concept of urban area is a key one in this approach, because energy efficient cities will only be possible through a broad-based consensus between science, politics, industry and citizens. Traditionally citizens have played a passive role in the energy market, but now they have the opportunity of being involved in generation, reduction of consumption and management and purchasing of energy, becoming new actors in the market and using collective intelligence for the common good.

Item Type: Conference or Workshop Item
Copyright Holders: 2015 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
MK:SMART, an integrated innovation and training programme leveraging large-scale city data to drive economic growth (Q-13-037-EM)H04HEFCE
Keywords: community energy; energy; citizens; bottom-up initiatives
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Related URLs:
Item ID: 43772
Depositing User: Jose Cavero
Date Deposited: 21 Jul 2015 09:36
Last Modified: 05 Oct 2016 19:58
URI: http://oro.open.ac.uk/id/eprint/43772
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