Devel­op­ment of vari­ous ML use cases with AWS


short to story

Innogy oper­ates dis­tri­bu­tion grids, sells energy and gen­er­ates most of its elec­tri­city from renew­able ener­gies. The com­pany is primar­ily act­ive as a grid oper­ator and in energy sales. The com­pany also plans, builds and oper­ates elec­tri­city gen­er­a­tion plants, primar­ily wind power plants (onshore and off­shore), hydro­elec­tric power plants and photo­vol­taic plants.

Goals & challenges

  • Devel­op­ment of com­plex ML models
  • Auto­mated deploy­ment of mod­els via Amazon ECS
  • Con­tri­bu­tion of phys­ical expert knowledge
  • Coach­ing of internal data scientists
  • AWS-Best-Prac­tices

key points

  • Use and integ­ra­tion of a vari­ety of dif­fer­ent data sources (geodata, sensor data, optical and infrared images, weather data, etc.)
  • Re-eval­u­ation of data col­lec­tion pro­ced­ures to cor­rect iden­ti­fied prob­lems in the data sets for the future
  • Exe­cu­tion of data engin­eer­ing tasks in the AWS
  • Close coöper­a­tion with end users to ensure the use­ful­ness and sub­sequent accept­ance and use of the developed solu­tions from the outset
  • Sub­tasks required a sig­ni­fic­ant fur­ther devel­op­ment of the “usual” algorithms (e.g. fea­ture detec­tion on low-struc­ture surfaces)

ser­vices accom­plished by syn­vert saracus

As a competent partner, synvert saracus has provided the following services:

  • Devel­op­ment of vari­ous use cases (hydro­power plants, wind tur­bines and e‑mobility)
  • CRISP-Work­flows
  • „The Data Sci­ence Pro­cess“ – Meth­od­o­logy (Busi­ness Under­stand­ing, Data Under­stand­ing, Data Pre­par­a­tion, Mod­ell­b­ildung, Fea­ture Engin­eer­ing, Eval­u­ation, Deployment)
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