Power Aware

Status: 
concluded
Period: 
March 2017 - May 2018
Funding: 
50.000 USD
Funding organization: 

Siebel Energy Institute

Executive summary: 

Power Aware is a research program that won the 2016 Siebel Energy Grants and the 2013 MIUR (Ministery of Italian Education) Smart City and Social Innovation competition.
It concerns the use of collaborative web platforms to enhance citizens’ awareness on key factors of energy costs.

Background: 

Collective Awareness Platforms (CAPs) aim to tackle issues in different focus areas (such as consumption, economy, open democracy, etc.) by harnessing participation of citizens on the online platforms in order to create a social networking effect that would lead to shared knowledge and collective intelligence.
The process of exchanging information among users, in fact, is finalized to find the best possible solution to a given challenge in order to induce social innovation and to address citizens towards more aware lifestyles.

Objectives: 

Power Aware is a research project aimed at understating the key requirements for building up a CAP focused on the development of a network of knowledge shared among citizens about energy consumption issues and possible solutions. The project exploits ICT tools and data visualization in order to drive behavioral changes at individual and collective level, encouraging participation of users through competition and cooperation among them. Therefore, the goal of the platform is to engage citizens in the process of change of consumption patterns.

The mission of Power Aware is to enhance citizens’ awareness on key factors of energy costs, to reduce energy use by changing the consumption habits.

The research activities of Power Aware are conducted in collaboration with Midori, an innovative start up operating since 2012 in the field of energy analytics.

Results: 

The project has been conducted in collaboration with the Italian start-up Midori (http://it.midorisrl.eu/) and with the Electronic Design Automation Group at Polytechnic University of Turin (http://eda.polito.it/) . The deliverables produced by the research team are available on the project website and are the following ones:
D1) Parameters for users profiling and clustering
D2) Data privacy issues
D3) Model for the classification of clustering and machine learning algorithms
D4) Classification of clustering algorithms from literature
D5) Evaluation of the algorithms
D6) Elaboration of a visualization for user’s comparison and power forecasting
D7) Evaluation of the visualization involving users
Emanuele Mottola spent the research fellowship studying parameters for users profiling and clustering algorithms. He also dealt with data visualization.