Decision Support Engines and Models: SmartDS, ResilienceDS


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In Snap4City we have integrated former solutions from RESOLUTE project which are ResilicenceDS and SmartDS tools. 

Smart DS

The SmartDS (Smart Decision System) of DISIT is an Advanced System Thinking solution for Decision Support System, DSS, on smart city problems and data. SmartDS is a tool presently in trial that allows you to model decision processes by using an Advances SystemThinking formalism defining weights on branches and value of the Italian Flags probabilities on processes, etc. (the application of verification and validation algorithms on data are also provided).
The SmartDS solutions has been designed to work on defining and improving DSS models in a collaborative manner and thus to create several DSS models on the data and processes of the city, via workshops, experts interview, and also direct access to Km4City data ( for the Florence area data). You can start by creating a decision model and using it in a given context adding data and positions etc.. Then, you can clone/copy the model or the instances of processes in another location and context, etc. Therefore, SmartDS solution allows shortening the time to make and activate decision processes, supporting and helping Decision Makers in making their job, faster and better.
Different Decision Makers can share models and solutions, but also monitor the results and the assessments. the Access can be from
The solution is provided as a free access tool, while as a Guest user you have limited capabilities. A free registration can be also performed allowing you to create, clone, manipulate some Advanced System Thinking graphs. If you need more capabilities/rights or to you need to connect your smartcity database to the processes, it can be done, please ask to:

SMARTDS: Smart Decision System, manuale utenteICT and social innovations are playing a decisive role in the development of technologically advanced urban areas. Smart City frameworks are devoted to address new challenges to improve efficiency and sustainability of services for citizens, providing additional features and allowing the city environment to adaptively configure according to collected data and information. To this aim, Decision Support Systems have recently been acquiring increasing importance in such a context. This paper presents a Smart Decision Support System for Smart City, based on the evolution of the Analytical Hierarchical Process model, which has been integrated with the Italian Flag 3-values logic representation. Other original contributes of the proposed work are (i) the capability integrating social and data processes by accessing and querying external repositories, in order to gather Smart City related data to be used to assist decision makers in the decisional process, through the use of properly defined functions and thresholds; (ii) the system is designed as a collaborative framework, allowing multiple users to share, clone and modify models and different instances of a same model. The proposed system has been validated in real use cases by exploiting decision processes and smart city data services of Km4City solution on Florence metropolitan area.

SMART Decision System, smartds example

SMART Decision System, smartds example, smart city

Resilience DS

Resilience and sustained adaptability in urban transport systems (UTS) Today, enhancing resilience in Urban Transport Systems is considered imperative for two main reasons: a) such systems provide critical support to every socio-economic activity and are currently themselves one of the most important economic sectors in Europe; b) the paths that convey people, goods and information, are the same through which risks are propagated. Transport systems have thus developed a prominent safety and business critical nature, in view of which current management practices have shown evidence of important limitations. UTS is a sociotechnical system whose resilience can be defined as the intrinsic ability to adjust its functioning prior to, during or following changes and disturbances, so that it can sustain required operations under both expected and unexpected conditions (Hollnagel, 2011). Thus, UTS resilience is considered an emergent property and it refers to managing high variability and uncertainty in order to pursue successful performance of the system continuously. Answering to questions as: •What type and sources of variability need to be managed? •What type and level of resources are needed to cope with such variability? •How to plan and deploy such resources? •How to ensure that local adaptive mechanisms are synchronised at the system lev.....