Seite - 61 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

With the aim of saving energy, thework in [1] presents design of a high-level ar- chitecture for smart building control systemwith a software systemperspective to im- prove energyefficiency for buildings.The authors of [2] aim topropose amethodology to automate the design process of smart energy-efficient buildings since these type of smart environmentscanbeused for anefficientmanagementof theenergyconsumption ofbuildingsbasedongivenpolicies.With thegoalof identifying theexistinggaps in the area of Fault Detection andDiagnosis (FDD) for buildings, thework in [3] presents a reviewof the latest researchandanalyze the typesoffaults thatcouldoccur inaBuilding ManagementSystem(BMS), aswell asgeneralFDDmethods, inanattempt todiscover potential matches. Thework in [4] introducesBOnSAI, an ontology for incorporating Ambient Intelligence inSmartBuildings. It extends existing ontologies in thefield and also adds classes to sufficientlymodel every aspect of a service-oriented smart building systemby includingconceptsmodelingall features, hardware,users andcontext. Thework in [5] describes adistributed information architecture that canbeused to implement smart environments on a large scale by integrating information access and controlofdifferentbuildingautomation systems.Theaimis toenable semantic interop- erabilitybetweendifferent equipments fromdifferentmanufacturers inorder that build- ing automation systems, user interfaces and services can interact perfectly. In [6], two different design approaches for smart building systemsusingWSNsare presented (one isbasedon IPv6, theotheronewithout theusageof IP).Theauthors conclude that IPv6 approach ismore advantageous for systemsof large scaleWSN. Inorder toprovide ad- equate assistanceandenergysaving, thenotionof anactivity-awareenergy-efficient au- tomation of smart buildings is introduced in [7]. The proposed activity-aware automa- tion systemusesactivity recognition to identify current activities andactivityprediction to anticipate upcoming activities.Activity-aware systems allow services to adapt to the needsof individual residentsandtheycanbeusedasacriticalcomponent toreduceener- gyconsumption.Forabetter introduction tosmartbuildings,youmayrefer to [8]which presents IntelligentBuildings andBuildingAutomationwith their principles, technolo- gies, communicationstandardsand internet technologiesapplications. Weconclude thatmostof theworksaboutbuildingsautomation lack tocoverall the important aspects and entities desired in a smart building (e.g., Safety&Security,User profile,Location) asdetailed inSection2.Also, theyare specificand limited in theuse, takingonlyaccountof fewentitiesandtheusedmethodologiesaregenerallynonformal. To implement complex systems composedofmany layers such as smart buildings, we need a complete methodology supporting the semantic aspect. Such methods are generallybasedonsoftwareengineeringparadigms (e.g.,MDE,Ontology). Buildings, alike homes, are environments with almost the same architecture and therefore, smart building systems design and implementation can be inspired by and based on extended smart home systems. The home automation domain has also known many works concerning design and implementation. This current work about smart buildings is a continuity of our previouswork about home automation [9]wherewep- resented an ontology for smart homes that allows a better design and implementation. In thenext section,wewill presentourproposedmethodology todesignand implement smartbuildingsystemsbydetailing theadoptedworkflow, requirementsandentities. 4. BuiS:amethodology forsmartbuildingdesignand implementation Inthissection,wepresentourproposedmethodologyfordesigninganddevelopingsmart building systems.BuiS (BuildingSmart) is amethodologybasedon software engineer- A.LyazidiandS.Mouline /BuiS:AMethodology forSmartBuildingModeling 61