Using IoT for Accessible Tourism in Smart Cities

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

Rethinking Transit Time Reliability by Integrating Automated Vehicle Location Data, Passenger Patterns, and Web Tools

This paper investigates time reliability at bus stops. Although it is typically evaluated from the transit provider's viewpoint, it must also account for passengers, as required in recent service-quality norms. Hence, data on both bus arrival (or departure) times and passenger arrivals must be collected and processed. Automated vehicle location (AVL) systems can collect bus data, but several challenges must be addressed to effectively use them. Passenger arrival data can be collected by surveys or direct observations and processed to derive patterns. This paper proposes two novel time reliability metrics: the percentage of passengers receiving regular service (PPR) and the percentage of passengers receiving punctual service (PPP) for regularity and punctuality evaluations, respectively. They are determined by a methodology that collects and handles AVL data, computes passenger patterns from passenger arrival data, and integrates AVL data and patterns. Experiments highlight the viability of the novel evaluation metrics using about three million of real-world AVL records. Their results are reported by straightforward Web tools. A comparison with traditional metrics shows that PPR and PPP provide a more careful evaluation by using the passenger as a normalization basis for their outcomes. In the new paradigm of demand-oriented services, the proposed metrics are crucial to quantify the ability of operators to serve passengers