The Eco-Bot “Package” is a chatbot that serves the user as a virtual energy-saving assistant. It engages with the user in near real-time communication and uses AI to constantly improve its skills. Our chatbot provides the user with very precise information concerning their energy consumption (for a specific period and for specific appliances) and related costs. It also offers goal-setting functions that are tailored to distinct user groups with specific energy-saving recommendations. It signals energy-saving events and information on the rebound effect. We call it Eco-Bot “package” because, supporting the chatbot front end with personalized content, the package includes the backend platform which comprises the following components:
- a Behavioural Model,
- an Operational Backend including a rule engine
- Non-Intrusive Load Management (NILM) modules
Our chatbot addresses both professional users such as building managers and private households.
Through the combination of the above-mentioned state-of-the-art components, it is anticipated to achieve a higher level of user engagement than previous energy bots. The chatbot can be integrated into the website of a utility, the utilities service modules or it can be used as an app. It has been tested and approved in different business models: B2B, B2C, and B2B2C.
Non-Intrusive Load Management (NILM) software platform
This platform, at its core, comprises NILM algorithms for residential buildings and different types of non-residential buildings that calculate the estimated energy consumption of individual electrical appliances’ or of large commercial loads for a fixed period of time, e.g., daily or weekly. As input, it uses only smart meter electricity data at different sampling resolutions (10 seconds to 1 hour) without resorting to additional submetering and other sensors or household information such as demographics.
The NILM software platform, with its suite of algorithms, is ready for evaluation and integration into commercial apps, for example, in the fields of building energy management, smart home automation, healthcare or home safety. It offers targeted energy efficiency feedback, improved demand response, customer safety feedback, and improved smart home automation. Customers do not need to invest in additional hardware besides their smart meter. Everything is managed within the software platform on the cloud, from which the customer can view and manage their energy feedback via a web interface.
Back End including Rule Engine
The Eco-Bot backend is a stand-alone expert system including a rule engine. A rule engine is a technical software component as part of a business rule management system that enables the efficient execution of business rules. The Eco-Bot backend can be integrated with other chatbot frontends and could include alternative data sources (beside NILM data) such as submetering or smart-plugs of a smart building, for example. The envisioned target markets for the Eco-Bot backend are either chatbot developers in need of energy market expertise or existing customer care software integrators in need of a cost-efficient and ready to integrate backend system – with a proven high technology readiness level.
Front End “Chatbot”
The Eco-Bot front end is stand-alone software that can simulate conversations with users by using natural language. From a user perspective, it provides proactively and reactively detailed and tailored information to the user, collects information for queries and responds accordingly. From a business perspective, it can automate processes (e.g. customer service), saving time and cost. The front end is the central user interface of the Eco-Bot “Package” and therefore the contact point for the end-user. The innovative part of the bot in comparison to other bots is that it provides detailed information on energy topics that are tailor-made for the end-user, who can be a professional user or a private household. The Eco-Bot front end as a stand-alone software can be used by utilities, energy consultants, consumer organizations with direct integration with their backend system.