In October 2017, the Eco-Bot project was launched with the aim to change energy consumption behaviour towards energy efficiency. Eco-Bot is a EU research project led by RISA Sicherheitsanalysen GmbH and co-funded by the EU H2020 research and innovation programme. It brings together technology developers and providers in the energy field as well as universities and high tech small and medium sized enterprises (SMEs) from Germany, Greece, Poland, Spain, and the UK.
The urgent need to tackle climate change emphasises the importance of finding effective and affordable ways to turn to sustainable energy solutions; engagement of consumers towards more energy efficient behaviour is a key factor in this endeavour, and this is what Eco-Bot aspires to achieve.
In the past 28 months, Eco-Bot has come a long way. We are now getting ready to launch the large scale pilot that will enable demonstration and validation of our system through the involvement of approximately 300 consumers and facility managers from Germany, Spain, Italy, and the UK.
Stay tuned to the progress and achievements of the Eco-Bot project by following our newsletter, website and social media accounts!
Eco-Bot at a glance
Eco-Bot (“Personalised ICT-tools for the Active Engagement of Consumers towards Sustainable Energy”) is a 43-month project co-funded by the European Commission under the “H2020-EU.3.3.1. – Reducing energy consumption and carbon footprint by smart and sustainable use” programme topic. The Eco-Bot consortium consists of nine partners, namely RISA, Estabanell Energia, adelphi, SEnerCon, DEXMA, the University of Strathclyde, Plegma Labs, the University of Economics in Katowice, and ERRA.
Eco-Bot aims to provide a personalised virtual energy assistant that will deliver information about energy consumption on an appliance level and user-tailored advice on energy efficiency measures, aspiring to engage users towards more energy efficient behaviour. To this end, Eco-Bot explores non-intrusive load monitoring (NILM) algorithms, multi-factorial behaviour modelling, and natural language processing.
The solution will be demonstrated in three different pilot sites, in order to validate the Eco-Bot system across real and diverse conditions and to explore its potential in different business cases:
- Estabanell Energia (the power utility of Catalonia) – B2C business model
- DEXMA (SaaS Building Energy Management System provider with two ESCO/building managers in Spain and the UK) – B2B business model
- SEnerCon (household energy users with smart meters in Germany) – B2B2C business model
Eco-Bot system overview
The Eco-Bot project utilises recent advances in chatbot technologies, advanced signal processing, and multi-factorial behavioural modelling, to offer personalised information and energy efficiency recommendations. Eco-Bot is a set of different components that are working together to provide all the information and analysis of data needed towards personalised energy efficiency guidance.
The system is comprised of the following main components: the frontend, the backend platform incorporating a knowledge-based expert system and the integrated behavioural module, the pilots’ backends, and the Non-Intrusive Load Monitoring (NILM) module. Integration and communication with third parties to enrich the system’s features is also enabled.
Eco-Bot offers a wide range of features aiming to address the requirements and expectations of consumers and facility managers.
Indicatively, the consumers are enabled to receive information on their consumption, both total and on appliance level, tailored recommendations for energy efficiency investments, e.g. regarding insulation and other home improvements, as well as for behaviour change, alerts for overconsumption, and notifications so as to be informed, for instance, in case a new subsidy that is relevant to them is announced, or to be given advice on appropriate actions during high peak periods.
The users are also motivated towards behaviour change by being given the option to set their own energy saving goals in terms of consumption, cost, and environmental impact. Furthermore, the system supports tackling the rebound effect by keeping the user aware through reminders of his/her energy consumption on a frequent basis as well as through the comparison of the consumption before and after energy saving events.
Facility managers, on the other hand, are enabled to receive, among others, information about energy consumption per building, league tables with the total consumption of their whole portfolio of buildings, energy and cost savings after the implementation of energy saving events performed in one or more buildings, tailored energy efficiency recommendations, etc. They are also enabled to set their own saving goals for each of the buildings they handle and easily monitor their progress in achieving their goals.
Watch our first demo video through our YouTube channel.
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