Use Cases

Smart city
cross­ing safety

Ped­es­tri­ans are nowadays more eas­ily dis­trac­ted, giv­en the increase of inform­a­tion com­ing at them from dif­fer­ent sources. The best example is of smart­phone activ­it­ies while walk­ing. These kinds of dis­trac­tions are com­mon, as ana­lysed by the Euro­stat.

Improv­ing the citizen’s safety in cross­roads is of par­tic­u­lar import­ance for vari­ous muni­cip­al­it­ies, and also a main con­cern in the EU.

The object­ive of this use case is to increase the ped­es­tri­an cross­ing safety by lever­aging the IoT and edge infra­struc­tures of a smart city.

This approach focuses on equip­ping a num­ber of ped­es­tri­an cross­ings with devices exist­ing on the mar­ket that enable mon­it­or­ing of ped­es­tri­ans intend­ing to cross the road.

The object­ive of the use case is to spot any poten­tial dangers that might be nearby put­ting their safety at risk and provide means for noti­fic­a­tion alerts.

pic­ture of the cross­ing where we will set up our pilot (before)

Fea­tures
from DECENTER’s archi­tec­ture

  • Resource orches­tra­tion
    (Ver­tic­al)

  • Pri­vacy-pre­serving AI

  • Hier­arch­ic­al /distributed AI

  • Digit­al twin

Smart city cross­ing design

In sum what we would like to achieve with this use case is to cre­ate a solu­tion to help people cross the road safely.

And also we aim to help DECENTER to test dif­fer­ent func­tion­al­ity on our pilot. (resource orches­tra­tion, pri­vacy pre­serving AI, hier­arch­ic­al /distributed AI, and digit­al twin)

pic­ture of the cross­ing where we will set up our pilot (before)

Robot­ic
Logist­ics

Great num­bers of companies/organizations accom­mod­ated in small build­ings involve a vast amount of mater­i­al trans­port through hall­ways, on elev­at­ors, in base­ments and to customer/patient units.

Logist­ic trans­port­ing robots are used on big hos­pit­als, malls and indus­tri­al areas, but there is not any cost-effect­ive autonom­ous logist­ic robot­ic sys­tem really adap­ted to small res­id­ences, ware­houses or medi­um sized indus­tri­al facil­it­ies.

The object­ive of this use case is to test a new, cost-effect­ive, robot­ic indoor trans­port solu­tion that will be spe­cially suited for ware­houses and will auto­mate the trans­port pro­cess and free work­force for tasks that entail high­er added value. To this end, the use case will per­mit the incor­por­a­tion of the swarm robot sys­tem from Robot­nik into the cloud/edge sys­tem ser­vices, allow­ing enhan­cing the func­tion­al­ity of the robots by the use of Edge Com­put­ing and a cent­ral­ized Cloud.

Fea­tures
from DECENTER’s archi­tec­ture

  • Resource orches­tra­tion
    (Ver­tic­al)

  • Pri­vacy-pre­serving AI

  • Hier­arch­ic­al /distributed AI

  • Digit­al twin

This use case envis­ages demon­strat­ing the applic­ab­il­ity of DECENTER plat­form, Edge and Cloud-to-Things Con­tinuum devel­op­ments, to the field of robot­ics as a mech­an­ism that allows rich­er inform­a­tion shar­ing and com­pu­ta­tion­al sup­port

Smart and safe
con­struc­tion site

Con­struc­tion is a very dynam­ic pro­cess. Each build­ing pro­ject is unique and usu­ally requires the col­lab­or­a­tion of sev­er­al com­pan­ies and act­ors.

Due to its very dynam­ic nature, it is a chal­len­ging engin­eer­ing work to organ­ise, mon­it­or, and imple­ment a con­struc­tion pro­ject includ­ing the vari­ous safety, secur­ity, logist­ics, inspec­tion and oth­er aspects, which require spe­cif­ic inform­a­tion sup­port.

The goal of the “Smart and safe con­struc­tion” use case is to explore mech­an­isms for inform­a­tion gath­er­ing, fusion and enrich­ment, which can provide intel­li­gence dur­ing the con­struc­tion pro­cess and help improve vari­ous aspects of the work.
Col­lect­ing rel­ev­ant inform­a­tion related to the con­struc­tion pro­cess, can be used for both time-crit­ic­al oper­a­tions and longer-term logist­ic and oth­er oper­a­tions.

design study of a pilot

Fea­tures
from DECENTER’s archi­tec­ture

  • Resource orches­tra­tion
    (Ver­tic­al)

  • Algorithms for QoS assur­ances, rank­ing and veri­fic­a­tion of Cloud deploy­ment options 
  • Pri­vacy-pre­serving AI

  • Hier­arch­ic­al /distributed AI

  • Digit­al twin

Use Case Pro­cess View

UC related lec­tures from Vlado Stankovski (UL) at World Con­struc­tion For­um 2019, Build­ings and Infra­struc­ture Resi­li­ence, April 8–11 2019, Ljubljana, Slov­e­nia

THEME 2
Con­struc­tion 4.0 – Advanced Con­struc­tion Engin­eer­ing:


Build­ing Smart And Safe Con­struc­tion Sites With Depend­able Decent­ral­ised Arti­fi­cial Intel­li­gence Applic­a­tions

Work­ers at a con­struc­tion site without DECENTER.
Work­ers at a con­struc­tion site with safety hel­met and without pro­tec­tion vests detec­ted.

Ambi­ent
Intel­li­gence

The focus of IoT-based ser­vices is mainly lim­ited to remotely mon­it­or­ing the cur­rent situ­ation using devices such as mobile phones, and these ser­vices are typ­ic­ally in the cloud. Round-trip delay caused by data trans­fer to the cloud may not be suit­able for real-time ser­vices. In addi­tion, there may be pri­vacy issues when upload­ing video streams to the pub­lic cloud.

In this use case, we test the mem­ber veri­fic­a­tion ser­vice at the edge using AI mod­els without send­ing any per­son­al inform­a­tion to the cloud.
This use case will show the main fea­tures of DECETNER based on an AI applic­a­tion for ambi­ent intel­li­gence.

This applic­a­tion checks the face of users vis­it­ing a cer­tain space and veri­fies wheth­er the per­son is author­ised to con­sume cer­tain con­tent in that space or not. For this use-case, the edge will use two veri­fi­ers veri­fy­ing each group mem­bers respect­ively.: A group veri­fi­er, and B group veri­fi­er. We assume that only these two groups are tar­get­ing to see spe­cif­ic con­tent. Thus the pro­cesses at the edge can veri­fy wheth­er the vis­it­or of a cer­tain space can con­sume cer­tain con­tent or not in that space, without shar­ing per­son­al inform­a­tion with the cloud.

design study of a pilot

Fea­tures
from DECENTER’s archi­tec­ture

  • Resource orches­tra­tion
    (Ver­tic­al)

  • Pri­vacy-pre­serving AI
  • Hier­arch­ic­al /distributed AI

  • Digit­al twin

In sum what we would like to achieve with this use case is to cre­ate a solu­tion to veri­fy mem­ber­ship at any edges without addi­tion­al per­son­al inform­a­tion.

After each edge has cre­ated an AI mod­el that iden­ti­fies spe­cif­ic group mem­bers and registered it on the cloud plat­form, it is easy to reuse this mod­el at oth­er edges without private inform­a­tion.