| responsive-algorithmic-enterprise |
endDate |
2020-02-01 |
| responsive-algorithmic-enterprise |
hasPrincipalInvestigator |
ed73bd81ffb6a518cb15fc394fb2be9e |
| responsive-algorithmic-enterprise |
startDate |
2018-06-01 |
| responsive-algorithmic-enterprise |
type |
Project |
| responsive-algorithmic-enterprise |
comment |
Energy management system for SMEs |
| responsive-algorithmic-enterprise |
label |
RAE (Responsive Algorithmic Enterprise) |
| responsive-algorithmic-enterprise |
depiction |
default.gif |
| responsive-algorithmic-enterprise |
homepage |
myaems.com |
| responsive-algorithmic-enterprise |
name |
RAE (Responsive Algorithmic Enterprise) |
| responsive-algorithmic-enterprise |
page |
responsive-algorithmic-enterprise |
| responsive-algorithmic-enterprise |
Description |
In this project, we work with AND technology and research (https://andtr.com/) to
develop new methods and algorithms to better understand current and anticipate future
electric demand of small and medium enterprises (SMEs). The recurrence quantification
analysis based-method is capable of alerting users of unusual behaviour, exceeded
budget constraints or faulty equipment. Consequently, this work has been incorporated
into a system and app AEMS, www.myaems.com by ANDtr. During 2018-2020, trials toward
commercialisation are funded by the UK government, Dept. for Business, Energy and
Industrial Strategy (BEIS), expecting a commercial product to be released in 2020. |
| responsive-algorithmic-enterprise |
in dataset |
kmifoaf |
| responsive-algorithmic-enterprise |
organization |
responsive-algorithmic-enterprise |
| responsive-algorithmic-enterprise |
organization |
responsive-algorithmic-enterprise |
