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In the past few years, the Smart City concept became one of the main driving forces for the transition towards sustainable economy and improved mobility. Tourism, as one of the fastest growing economies worldwide, is an integrated part of the Smart City paradigm. Taking into consideration recent studies performed by the United Nations, stating that almost one third of the population is directly affected by disability, the concept of Accessible Tourism needs also to be integrated in the future vision for tourism, especially in the context of Smart Cities, environments fully benefiting from the recent technological advances. Within the combined framework of Smart Cities and Accessible Tourism, the Internet-of-Things (IoT) concept is the key technological point for the development of smart urban environments. IoT and big data are both technology-driven developments, leading to scenarios such as the Smart Cities one that has the potential to make citizen live smarter, more sustainable and more accessible. This chapter analyses the key requirements for IoT applications in a Smart City context, the state-of-the-art for the use of IoT for Accessible Tourism applications and proposes an architecture together with its practical implementation, tailored for the use-case of accessible tourism for physically impaired persons.

This paper investigates a service network design problem, which is motivated by the case of freight transportation in a port city. We describe the novel features of this problem, which are based on the possible (but still unexploited) knowledge on the composition of the disaggregated loads in containers and semitrailers entering the port. In this problem, the transportation requests of these loads are highly customized and have different delivery costs. We must determine the paths of vehicles and loads, which result in costs paid by carriers and customers, as well as external costs for the city itself. The resulting network design problem is faced from the holistic viewpoint of a possible mobility manager, which must minimize the overall system costs. We present a mixed integer linear programming model (MILP) for this problem. Since it is very difficult to solve by standard MILP solvers, we present a Tabu Search algorithm exploiting the specific problem features. The computational experiments show to what extent this problem can be tackled by a general purpose mixed-integer programming solver and the Tabu Search algorithm.