Research project “Nebu­lOuS”

One of the most diffi­cult chal­lenges in deal­ing with large-scale disas­ters such as floods, earth­quakes, and wild­fires is coor­di­nat­ing response crews, mate­ri­als, and equip­ment from vari­ous stake­hold­ers. Obtain­ing a clear picture of the situ­a­tion in the affected area is crit­i­cal for oper­a­tional manage­ment, allow­ing for the effi­cient and safe deploy­ment of avail­able resources. However, because these crisis situ­a­tions are inher­ently hazy, even answer­ing simple ques­tions, such as the acces­si­bil­ity of specific areas or the struc­tural stabil­ity of struc­tures, is a tedious and time-consum­ing task. 

However, because these crisis situ­a­tions are inher­ently hazy, even answer­ing simple ques­tions, such as the acces­si­bil­ity of specific areas or the struc­tural stabil­ity of struc­tures, is a tedious and time-consum­ing task. The tech­no­log­i­cal poten­tial for data collect­ing and process­ing has quickly risen over the previ­ous decade and is now being used in almost all indus­tries. However, in crisis scenar­ios, the exist­ing commu­ni­ca­tion infra­struc­ture and hence process­ing capac­i­ties are inter­rupted and cannot be conve­niently utilized. As a result, plan­ning tools for day-to-day emer­gency services are frequently only used to a limited level. 

During the 2021 flood in south­ern Germany, a full break­down of mobile commu­ni­ca­tion networks and even digi­tal radio commu­ni­ca­tion systems not only hampered commu­ni­ca­tion, but also severely limited access to process­ing capa­bil­i­ties for analyz­ing the data at hand. Nebu­lOuS’ purpose is to enable wide­spread commu­ni­ca­tion and comput­ing even in crisis scenar­ios by deliv­er­ing a flex­i­ble fog comput­ing plat­form that can adapt to the situ­a­tion at hand. 

By combin­ing the Nebu­lOuS plat­form with modern LPWAN tech­nolo­gies, not only can the situ­a­tional map system devel­oped by @Fire during the 2021 flood be used and managed more broadly, but AI algo­rithms can also be deployed on multi­ple levels of the edge-cloud-contin­uum for the first time to process avail­able data in order to verify infor­ma­tion and signif­i­cantly improve the situ­a­tional aware­ness of crisis manage­ment staff and response teams. 

BIBA (Germany, RTD) will imple­ment the dynamic situ­a­tional map in the Nebu­lOuS system and extend it with its “USGn­ode” LPWAN sensor system as a key part­ner in the use case. @fire (Germany, Indus­try) is a German national disas­ter response orga­ni­za­tion that will test the Nebu­lOuS plat­form and dynamic map with local commu­ni­ca­tion infra­struc­ture in disas­ter scenarios. 

When the @fire crisis response team is deployed to a disas­ter area, the OSIRAS (Ordnance Shel­ter for Inter­ven­tion Rescue and Ambu­lance SlideOn) station serves as the unit’s mobile coor­di­na­tion point. Nebu­lOuS will extend it with LPWAN commu­ni­ca­tion and an edge cloud, which will be linked to other public cloud resources managed by Nebu­lOuS if inter­net connec­tiv­ity is avail­able. The teams deployed in the region will report infor­ma­tion to the system via an app, which will be directly incor­po­rated into the situ­a­tional assess­ment. Data from LPWAN sensors report­ing rele­vant field data, such as water levels, struc­tural changes, weather condi­tions, and equip­ment loca­tions, will supple­ment this data.