Sup­por­ting cri­ti­cal infra­st­ruc­ture with AI

When all the lights go out…

Using AI to pre­dict dis­rup­ti­ons to cri­ti­cal infra­st­ruc­ture before all the lights go out.

The pro­blem 

Incre­a­sed energy demand in dis­as­ter situa­tions, plan­ning for repla­ce­ment of regu­lar infra­st­ruc­tures in case of main­ten­ance or sup­por­ting exis­ting regu­la­ti­ons for cri­ti­cal infra­st­ruc­tures with AI, these are tar­gets for the deve­lo­p­ment of the PAIRS plat­form. Spe­ci­fi­cally, the goal is to be able to fore­cast dis­rup­ti­ons before all the lights go out.

The Solu­tion

To this end, exis­ting and cur­r­ently detec­ted fault data from net­work ope­ra­tors are lin­ked with other exter­nal data (wea­ther, traf­fic, natu­ral dis­as­ter moni­to­ring, etc.) in order to be able to pre­dict new faults. This gives ope­ra­tors an over­ar­ching over­view and enab­les them to manage cri­ses dynamically.

The fin­dings and recom­men­da­ti­ons from the PAIRS plat­form are also ide­ally sui­ted for use in other cri­sis sce­n­a­rios, e.g., in hos­pi­tals or sup­ply chains, in order to pre­pare for emer­gen­cies in good time.

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Bene­fit from active pro­ject par­ti­ci­pa­tion with many advantages

The joint pro­ject PAIRS is fun­ded as an AI light­house pro­ject wit­hin the frame­work of the “Inno­va­tion Com­pe­ti­tion Arti­fi­cial Intel­li­gence” by the Federal Minis­try of Eco­no­mics and Cli­mate Pro­tec­tion (BMWK).

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