{"id":81298,"date":"2023-05-01T03:01:26","date_gmt":"2023-05-01T01:01:26","guid":{"rendered":"https:\/\/blog.bluebeam.com\/se\/?p=81298"},"modified":"2023-05-30T10:31:15","modified_gmt":"2023-05-30T08:31:15","slug":"gni-construction-innovation","status":"publish","type":"post","link":"https:\/\/blog.bluebeam.com\/se\/gni-construction-innovation\/","title":{"rendered":"Fr\u00e4mja innovationer: Georg Nemetschek Institute of AI for the Built World"},"content":{"rendered":"\n

Professor Georg Nemetschek, vars koncern Nemetschek Group best\u00e5r av 13 varum\u00e4rken som producerar alla typer av byggteknologi (d\u00e4ribland Bluebeam), grundade Georg Nemetschek Institute<\/a> of Artificial Intelligence for the Built World (GNI) 2020.<\/p>\n\n\n\n

GNI \u00e4r ett samarbete mellan Nemetschek Innovation Foundation och M\u00fcnchens tekniska universitet (TUM), och har som m\u00e5ls\u00e4ttning att finansiera prim\u00e4r forskning inom artificiell intelligens relaterad till bygg- och fastighets\u00e4garbranschen. Institutet publicerade sin f\u00f6rsta inbjudan att l\u00e4mna f\u00f6rslag i november 2020.<\/p>\n\n\n\n

GNI, som har sitt huvudkontor p\u00e5 TUM:s Garching-campus i M\u00fcnchen, har hittills finansierat tv\u00e5 huvudsakliga forskningsomr\u00e5den: forskningsprojekt och st\u00f6d till enskilda forskare genom postdoktorala program.<\/p>\n\n\n\n

Medan byggbranschen forts\u00e4tter att anamma ny teknologi \u00e4r initiativ som GNI avg\u00f6rande f\u00f6r att kunna utforska och anv\u00e4nda verktyg som kan bli omv\u00e4lvande f\u00f6r hur v\u00e5r v\u00e4rld byggs. AI har redan n\u00e5gra begynnande anv\u00e4ndningsomr\u00e5den i branschen, men GNI:s arbete syftar till att st\u00e4rka potentiella anv\u00e4ndningsfall genom forskning som bidrar till att bef\u00e4sta n\u00e4sta generations bygginnovationer.<\/p>\n\n\n\n

Sedan GNI startades har sex innovativa forskningsprojekt f\u00e5tt finansieringsgodk\u00e4nnande.<\/p>\n\n\n\n

Samtliga sex projekt har bildats och inlett sitt arbete p\u00e5 ett tidigt stadium. Projekten \u00e4r verkligen sp\u00e4nnande, eftersom de har potential att g\u00f6ra viktiga genombrott som f\u00f6r byggbranschen fram\u00e5t.<\/p>\n\n\n\n

H\u00e4r f\u00f6ljer en sammanfattning av varje projekt:<\/p>\n\n\n\n

Projekt 1: Artificiell intelligens f\u00f6r att automatiskt skapa flerskaliga digitala tvillingar f\u00f6r den byggda v\u00e4rlden (AI4TWINNING)<\/strong><\/h3>\n\n\n\n

Digitala tvillingar h\u00f6r till de mest efterl\u00e4ngtade teknologierna f\u00f6r bygg- och fastighets\u00e4garbranschen, tack vare att de inneb\u00e4r v\u00e4rdefulla kostnadsbesparingar och produktivitetsf\u00f6rb\u00e4ttringar. En digital tvilling \u00e4r inte bara en statisk kopia av en byggnad, utan skapar snarare en realtidskoppling mellan den digitala och den fysiska tvillingen. M\u00e5let med projektet \u00e4r inte att skapa en enda monolitisk digital tvilling utan ist\u00e4llet ett system av sammankopplade tvillingar i olika skalor, vilket ger m\u00f6jlighet att s\u00f6ml\u00f6st integrera modeller av st\u00e4der, distrikt och byggnader samt h\u00e5lla dessa aktuella och konsekventa.<\/p>\n\n\n\n

L\u00e4s mer h\u00e4r<\/a>.<\/p>\n\n\n\n

Projekt 2: Artificiell intelligens f\u00f6r smart design och testning av cement och betong (AICC)<\/strong><\/h3>\n\n\n\n

Cement och betong h\u00f6r till byggbranschens vanligaste material. Anv\u00e4ndningen av materialen har en enorm inverkan p\u00e5 koldioxidutsl\u00e4ppen \u2013 inte bara p\u00e5 grund av den stora m\u00e4ngd material som bearbetas varje \u00e5r utan ocks\u00e5 f\u00f6r att de f\u00f6rbrukar mycket energi under tillverkningen. I det h\u00e4r projektet f\u00f6resl\u00e5s metoder baserade p\u00e5 maskininl\u00e4rning f\u00f6r att karakterisera betongens luftporsystem. Dessa p\u00e5verkar nedbrytnings- och f\u00f6rs\u00e4mringsprocesserna, fr\u00e4mst p\u00e5 grund av mekanismerna f\u00f6r gas- och fukttransport i den fasta fasen. M\u00e5let med projektet \u00e4r att unders\u00f6ka olika in- och utmatningsvariabler fr\u00e5n nuvarande standardiserade metoder i syfte att g\u00f6ra dem mer exakta och tillf\u00f6rlitliga.<\/p>\n\n\n\n

Titta in i projektet h\u00e4r<\/a>.<\/p>\n\n\n\n

Projekt 3: Intelligent infrastrukturunderh\u00e5ll med djupinl\u00e4rning<\/strong> (INFRA.RELEARN)<\/strong><\/h3>\n\n\n\n

Underh\u00e5llet av v\u00e4g- och vattensystem, inklusive transport-, energi- och vattenn\u00e4t, inneb\u00e4r en betydande kostnad f\u00f6r samh\u00e4llet. F\u00f6r n\u00e4rvarande sker planeringen av underh\u00e5lls\u00e5tg\u00e4rder (d\u00e4ribland besiktning) fr\u00e4mst baserat p\u00e5 en kombination av fasta regler och tillf\u00e4llig optimering. Projektet syftar till att ta ett viktigt steg mot AI-st\u00f6dd underh\u00e5llsplanering genom att uppr\u00e4tta formella beskrivningar av underh\u00e5llsplanering f\u00f6r infrastruktur som ett sekventiellt beslutsproblem och utveckla skr\u00e4ddarsydda DRL-algoritmer f\u00f6r att identifiera optimala underh\u00e5llsstrategier.<\/p>\n\n\n\n

Uppt\u00e4ck mer h\u00e4r<\/a>.<\/p>\n\n\n\n

Projekt 4: Djup, fysikbaserad \u00f6vervakning av byggnadsh\u00e4lsa (DeepMonitor)<\/strong><\/h3>\n\n\n\n

Att hitta dolda konstruktionsfel \u00e4r en viktig uppgift inom v\u00e4g- och vattenbyggnad. Hittills har uppt\u00e4ckten av s\u00e5dana fel genom sensorsignaler varit allt fr\u00e5n tidskr\u00e4vande till om\u00f6jlig, eftersom de tillh\u00f6rande inverterade problemen \u00e4r sv\u00e5rl\u00f6sta och allt f\u00f6r ofta d\u00e5ligt l\u00e4mpade f\u00f6r praktiska till\u00e4mpningar inom v\u00e4g- och vattenbyggnad.<\/p>\n\n\n\n

F\u00f6r att l\u00f6sa det h\u00e4r problemet ska ett forskarteam unders\u00f6ka alla tillg\u00e4ngliga alternativ inom datavetenskap, fr\u00e5n datadrivet \u00f6vervakat l\u00e4rande till o\u00f6vervakat l\u00e4rande som h\u00e4mtar information fr\u00e5n fysiken. Vi kommer att utveckla datadrivna ers\u00e4ttningsmodeller f\u00f6r att st\u00f6dja eller helt ers\u00e4tta konventionella metoder. Problemet kommer ocks\u00e5 att hanteras genom inl\u00e4rning av regulariseringen fr\u00e5n data med hj\u00e4lp av neurala n\u00e4tverk. Samtliga metoder kommer att utv\u00e4rderas f\u00f6rst genom riktm\u00e4rkesexempel och i projektets sista fas testas p\u00e5 konstruktioner av praktiskt intresse inom v\u00e4g- och vattenbyggnad.<\/p>\n\n\n\n

H\u00e4r<\/a> finns mer information om projektet.<\/p>\n\n\n\n

Projekt 5: Utformning av infrastruktur och n\u00e4tverk f\u00f6r cykling \u2013 en m\u00e4nniskocentrerad, datadriven metod som bygger p\u00e5 rumslig-temporal maskininl\u00e4rning (RADELN)<\/strong><\/h3>\n\n\n\n

Projektet syftar till att utveckla en m\u00e4nniskocentrerad, datadriven metod f\u00f6r att hitta optimala utformningar av infrastruktur och n\u00e4tverk f\u00f6r cykling i storstadsregioner som bidrar till att omvandla bilresor till cykelresor.<\/p>\n\n\n\n

I ramverket utnyttjas all potential f\u00f6r trafikomst\u00e4llning genom att man inf\u00f6rlivar l\u00e4ngre resor och skiljer ut de heterogena preferenserna hos tidigare identifierade cyklisttyper. F\u00f6r att s\u00e5 realistiskt som m\u00f6jligt f\u00f6ruts\u00e4ga den resespecifika cykelinfrastrukturens inverkan p\u00e5 andelen cykelresor ska projektets forskare f\u00f6rst bakl\u00e4ngeskonstruera den faktiska realiserade rutten och valet av transportmedel utifr\u00e5n verkliga data. De ska ocks\u00e5 utveckla en datadriven modell f\u00f6r att hitta flaskhalsar i de befintliga cykeln\u00e4tverken.<\/p>\n\n\n\n

L\u00e4s mer h\u00e4r<\/a>.<\/p>\n\n\n\n

Projekt 6: Samarbetsrobotar f\u00f6r byggbranschen med spatial AI (SPAICR)<\/strong><\/h3>\n\n\n\n

Till\u00e4mpningen av mobila samarbetsrobotar i byggprocessen kan inneb\u00e4ra en enorm potential f\u00f6r arkitekt-, ingenj\u00f6rs- och byggbranschen. Anv\u00e4ndningen av robotar kan leda till \u00f6kad effektivitet och s\u00e4kerhet, minskade kostnader och fel samt st\u00f6rre m\u00f6jlig noggrannhet. Det g\u00e4ller s\u00e5v\u00e4l nya byggnader som befintliga med avseende p\u00e5 renovering, reparation och underh\u00e5ll.<\/p>\n\n\n\n

Byggarbetsplatserna medf\u00f6r dock avsev\u00e4rda utmaningar f\u00f6r robotanv\u00e4ndningen. Byggprocessen i sig kan leda till att platsen f\u00f6r\u00e4ndras. Milj\u00f6erna karakteriseras som d\u00e5ligt konstruerade och dynamiska, eftersom olika akt\u00f6rer (s\u00e5v\u00e4l m\u00e4nniskor som robotar) m\u00e5ste utf\u00f6ra olika heterogena uppgifter.<\/p>\n\n\n\n

D\u00e4rf\u00f6r har man \u00e4nnu inte lyckats demonstrera storskalig anv\u00e4ndning av mobila samarbetsrobotar i byggbranschen med en acceptabel niv\u00e5 av noggrannhet, stabilitet och samordning. Med det h\u00e4r projektet hoppas forskarna g\u00f6ra framsteg mot anv\u00e4ndningen mobila samarbetsrobotar i den verkliga v\u00e4rlden genom att med hj\u00e4lp av avancerad spatial artificiell intelligens och spatiala datatekniker fr\u00e5n datorseende och robotteknik skapa och underh\u00e5lla en digital tvilling f\u00f6r samarbetsrobotprocessen.<\/p>\n\n\n\n

L\u00e4s om projektets omfattning h\u00e4r<\/a>.<\/p>\n\n\n\n

H\u00e5ll dig informerad<\/em> genom att bes\u00f6ka <\/em>GNI:s webbplats<\/em><\/a> d\u00e4r du kan l\u00e4sa mer om GNI, f\u00f6lja projektens framsteg och f\u00e5 uppdateringar om institutets senaste nyheter.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

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