Member - Bandora Systems

Artificial Intelligence platform developed to improve Buildings Energy Efficiency, using Big Data technologies

Type Startup or self-employed
Founder 2017
Company Size 2
Member Type
Innovator
Founders Márcia Pereira; Ricardo Gomes
Headquarters 4200-375 Porto, Portugal
Social network

About

Bandora is an artificial intelligence platform which correlates all data generated inside a building, in order to programme the logic controllers and other devices in real time and optimize its operation towards a reduction up to 40% of energy consumption. At the same time we will increase building’s occupants satisfaction, environmental awareness and social engagement.
Headquarters 4200-375 Porto, Portugal

SDG’s of application

The Sustainable Development Goals are a call to action to end poverty, protect the planet and ensure peace and prosperity everywhere.
SDG 6
Clean Water and
Sanitation
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SDG 7
Affordable and
Clean Energy
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SDG 9
Industry, Innovation
and Infrastructure
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SDG 11
Sustainable Cities
and Communities
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SDG 12
Responsible Consumption
and production
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Offers from Bandora Systems

Other products

Reduce energy consumption and eliminating wastage are among the main goals of the European Union. New Public Building must be NZEB by the end of 2018, New Commercial Buildings at 2020 and all existing ones until 2030. European Energy DG says that there is an opportunity of 50% savings with measures applied to the building shell, equipments and user’s behaviour. Bandora is an ingest engine towards energy efficiency inside a building to manage equipments and users. Gathering inputs from BMS, user’s experience feedbacks, regular sensors (light, temperature, humidity, space occupancy) and Financials data from Facilities Managers, we analyse the energy demand, the way it’s used and wasted in a Building. Using predictive algorithms, we're able to reconfigure BMS setup automatically and in real time, in order to reduce energy costs while increasing users comfort and satisfaction with their workplace. Bandora is based on machine learning technologies, so it applies recurrently new measures to reduce up to 40% the energy consumption.

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Available inWorldwideCategories of applicationSustainable cities and communitiesSector of applicationBuilding and shelters Status R&D