5. Proposed accessible tourism solution

This section presents an accessible solution designed on top of the IoT platform presented in the previous section, aiming to provide useful information to tourists in general, with particular attention to the ones with special needs. The application has been developed for the cruise ship tourists who land in the city of Cagliari, but it could be applied to many Western European tourist destinations, regardless of the means of arrival (i.e. plane, train, or ship).

#### 5.1. Cruise tourism

blind or visually impaired people, wheelchair but also museums, parks or busses can communicate among them without any problem at this level even if they all use different communication technologies: simple technologies, such as RFID tags and NFC, can be attached to Points of Interest (PoIs) to enhance the visiting experience of tourists by interpreting information about the environment and making choices accordingly, for example by pushing additional

To activate a new VO, the system has to find a match between the possible VO templates and the information (metadata) provided by the physical device; such information comprehends: objects' characteristics; objects' location; resources, services, and quality parameters provided by objects. When a match is found, a new instance of the object is created (i.e. the web server representing the VO itself), which run in the Virtual Object Execution Space (VOES), where all

Each VO has two interfaces: the first one enables the VO to create a standardized communication procedure with the physical object; this way, the VO can communicate with the object using a set of different protocols based on the situation at hand. The other interface allows the VO to "speak" with all the other VOs in the VOES; thank to this, it is possible even for physical objects with have different communication technologies to communicate among them and

The VO registry stores a semantic description for each active VOs in the VOES, in the form of metadata, which is then used every time there is the need to search for a particular VO.

This metadata is particularly useful in the case of accessible tourism, where the information regarding the different objects available for people with disability needs to be described with the correct metadata in order to be easily discoverable; this is the case for example of busses with a platform for tourists in a wheelchair or of museums which provide audio guides for

When the Search and Discovery Engine is activated by the upper layers, it search in the VO registry to find any potential available VO that can match the query, i.e. any VO whose metadata can

(4) Real-World Object Layer: Implemented out of the cloud, this level includes every device that is capable of accessing the Internet. These devices are called Real World Objects (RWOs) due

(5) Trust and Security Engine: This layer focuses on the implementation of appropriate security procedures to guarantee that attacks and malfunctions in the platform will not outweigh any of its benefits. At the Virtualization level, for example, this plane needs to understand how the information provided by the VOs have to be processed so as to build a reliable system on the basis of their behavior. In the Application level, the Security Engine could determine the

(6) QoE/QoS Manager: The management of quality is an important issue in classical IoT implementation mainly due to the heterogeneity of the objects and to their mobility. In the proposed platform, we address these problems making use of VOs; however, even with

to their direct connection with the physical environment where they sense and act.

accessibility of the different applications to grant access only to authorized users.

information regarding the PoI to users [26].

become interoperable at the virtual level.

the instances of VOs run.

38 Assistive Technologies in Smart Cities

visually impaired tourists.

match the services required.

When arriving in Cagliari, many cruise ship tourists, often prefer to take a walking tour rather than taking an organized tour. After getting off the cruise ship, these people have to spend too much time to get the needed information about programming their visit. And time is a very critical aspect for cruise ship tourists, due to the limited number of hours the cruise ship usually stays at the call port. This aspect gets worse for disabled people, depending on the type and degree of disability. In the case of mobility disability, for instance, a destination like Cagliari, where reaching the most important attractions require a lot of walking uphill, due to the natural and geographical features of the city, many tourists are constrained to limit their visit to the areas around the port. Instead, with some detailed information about accessible routes in the city, more tourists could reach all the attractions of interest within walking distance of the port getting a better experience from their visit. This is why we designed and developed a mobile application dedicated to generic tourists and specifically adapted to accessible tourism. In case of physical impairments, this mobile application is capable to optimize visits to specific mobility user needs. In this work we adopt the paradigm of people inclusion and universal access to information and tourism assets.

In the recent years, tourism experiences of people with disabilities have largely been a research key topic [27]. Research results have been focused on accessible tourism and accommodation preferences [5]. Most of the available tools are based on web sites for travel planning with focus on inclusive tourism such as Tur4All (https://www.tur4all.com/) and Jaccede.com (https://www.jaccede.com/). Specific tools face just single aspects of the problem. LinkedQR [28] is a tool to improve the collaboration between QR codes and Linked Data, through mobile and Web technologies. Nevertheless, the role of IoT in tourism is expected to create innovative experiences for consumers [29].

There is a lack of tools specifically designed for everyone and able to perform specific outcomes for disabled. Our application addresses this challenge, following the paradigm of whole-of-life to tourism, considering that 30% of a population will have access requirements at some stage during their life [4].

## 5.2. The tour planner application

The Tour Planner is a mobile application, useful to build a dynamic itinerary through a city, based on a repository of Points of Interest (PoIs), each one of them is represented as a VO on the platform (Figure 2).

about the existence of facilities for disabled people. The information would be complete if also the "not existence" of the facilities would be reported (in a standard way, as well). Another issue in relation to this aspect is that quite often the presence of these facilities is not compliant to standard like the ISO 21542:2011 for building construction - Accessibility and usability of the

Using IoT for Accessible Tourism in Smart Cities http://dx.doi.org/10.5772/intechopen.77057 41

Some disability rights organizations periodically (for instance, yearly) verify if declared accessibilities are compliant to the standard. As a good example of this, in UK, there are important providers of access information like DisabledGo (https://www.disabledgo.com/). If this kind of verified information could be automatically collected and stored in the platform, the Tour Planner application would be able to acquire them and to build proper itineraries accordingly. In our case, a further improvement should come from the municipality of Cagliari by providing access infrastructures through the streets of the historical city, and making the related

In this accessible destination scenario, a disabled person, for example with a limited degree of mobility, could use the Tour Planner application to properly construct his or her tour, including the PoIs and the routes that connect them, depending on the needed level of accessibility. Obviously, the presented Tour Planner application represents only a technology which allows this scenario of accessible destination to become reality; in fact, the solution requires some effort by the decision makers in order to make all the actors of the scenario to co-operate for

built environment (https://www.iso.org/obp/ui/#iso:std:50498:en).

information available.

realizing it (Figures 3 and 4).

Figure 3. The tour planner set up and the list of PoIs.

The Tour Planner application is developed on top of the proposed platform, and it takes in input not only the Points of Interest related to monuments, museums, archeological sites, parks, botanical gardens, shopping areas, restaurants, but also commercial offers and events as well as every information that can be important for the user, such as his/her particular needs, the length of the queue in real time from the PoIs or the weather.

Moreover, the Tour Planner allows to save the itineraries built by the end users (the tourists) in a format suitable to be saved in the platform, then making it available for other users. The information available on the platform are regularly taken and stored (updated) in the back end of the mobile application. The mobile application has been developed with the Ionic Framework in order to be suitable for any mobile platform.

The platform takes all the information about the Points of Interest (PoI) in a certain geographical area. The PoIs are stored in the platform according to a classification related to the type (the already mentioned, monument, museum, archeological site, etc.).

#### 5.3. How the tour planner works?

The Tour Planner aims to improve accessible tourism because it provides the possibility to build itineraries suitable for people with disability, adding detailed information about the accessibility of each Point of Interest, whenever available. Unfortunately, a well-known problem is related to the fact that most of the web sites based on the Points of Interest paradigm do not follow standards like the "ISO 7001:2007 Graphical Symbols" (https://www.iso.org/obp/ui/ #search/grs/7001). Although not comprehensive, these standards are suitable to notify tourists

Figure 2. The RWO and the tour planner exchange information each other.

about the existence of facilities for disabled people. The information would be complete if also the "not existence" of the facilities would be reported (in a standard way, as well). Another issue in relation to this aspect is that quite often the presence of these facilities is not compliant to standard like the ISO 21542:2011 for building construction - Accessibility and usability of the built environment (https://www.iso.org/obp/ui/#iso:std:50498:en).

Some disability rights organizations periodically (for instance, yearly) verify if declared accessibilities are compliant to the standard. As a good example of this, in UK, there are important providers of access information like DisabledGo (https://www.disabledgo.com/). If this kind of verified information could be automatically collected and stored in the platform, the Tour Planner application would be able to acquire them and to build proper itineraries accordingly. In our case, a further improvement should come from the municipality of Cagliari by providing access infrastructures through the streets of the historical city, and making the related information available.

In this accessible destination scenario, a disabled person, for example with a limited degree of mobility, could use the Tour Planner application to properly construct his or her tour, including the PoIs and the routes that connect them, depending on the needed level of accessibility.

Obviously, the presented Tour Planner application represents only a technology which allows this scenario of accessible destination to become reality; in fact, the solution requires some effort by the decision makers in order to make all the actors of the scenario to co-operate for realizing it (Figures 3 and 4).


Figure 3. The tour planner set up and the list of PoIs.

5.2. The tour planner application

the platform (Figure 2).

40 Assistive Technologies in Smart Cities

The Tour Planner is a mobile application, useful to build a dynamic itinerary through a city, based on a repository of Points of Interest (PoIs), each one of them is represented as a VO on

The Tour Planner application is developed on top of the proposed platform, and it takes in input not only the Points of Interest related to monuments, museums, archeological sites, parks, botanical gardens, shopping areas, restaurants, but also commercial offers and events as well as every information that can be important for the user, such as his/her particular

Moreover, the Tour Planner allows to save the itineraries built by the end users (the tourists) in a format suitable to be saved in the platform, then making it available for other users. The information available on the platform are regularly taken and stored (updated) in the back end of the mobile application. The mobile application has been developed with the Ionic Frame-

The platform takes all the information about the Points of Interest (PoI) in a certain geographical area. The PoIs are stored in the platform according to a classification related to the type

The Tour Planner aims to improve accessible tourism because it provides the possibility to build itineraries suitable for people with disability, adding detailed information about the accessibility of each Point of Interest, whenever available. Unfortunately, a well-known problem is related to the fact that most of the web sites based on the Points of Interest paradigm do not follow standards like the "ISO 7001:2007 Graphical Symbols" (https://www.iso.org/obp/ui/ #search/grs/7001). Although not comprehensive, these standards are suitable to notify tourists

needs, the length of the queue in real time from the PoIs or the weather.

(the already mentioned, monument, museum, archeological site, etc.).

work in order to be suitable for any mobile platform.

Figure 2. The RWO and the tour planner exchange information each other.

5.3. How the tour planner works?

Problem: the tourist is given an optimal route where he/she visits each POI only once, mini-

We consider the current location 0 of the tourist and a set I of POIs. A time interval d can be spent at most to visit a number POIs from the current location. Each POI is associated with a

The problem can be described as the following graph theoretic problem. Let G Nð Þ ; A be a direct and complete graph, where N is the node set and A the set of arcs connecting nodes of set N. Nodes correspond to the points of interest and the current position of the tourist, i.e., N ¼ I∪0. Arcs represent possible connections between two distinct nodes. Let ti,j be the time to

ranking pi representing its attractiveness for tourists and a visiting time vi.

• Xi,j ∈f g 0; 1 is equal to 1 if the tourist moves along arc ð Þ i; j ∈ A, 0 otherwise;

MaxX i∈J

> X j∈ J

> X j∈ J

Xj,i <sup>¼</sup> <sup>X</sup>

Yi � vi <sup>þ</sup> <sup>X</sup>

<sup>j</sup><sup>∈</sup> <sup>N</sup> , <sup>j</sup>6¼<sup>i</sup>

ð Þ i;j ∈ A

Yi � pi (1)

Using IoT for Accessible Tourism in Smart Cities http://dx.doi.org/10.5772/intechopen.77057 43

X0,j ¼ 1 (2)

Xj, <sup>0</sup> ¼ 1 (3)

Xi,j ¼ Yi ∀i∈ I (5)

� � <sup>&</sup>gt;<sup>¼</sup> <sup>0</sup> <sup>∀</sup>ð Þ <sup>i</sup>; <sup>j</sup> <sup>∈</sup> <sup>A</sup> (6)

Xi,j ∈f g 0; 1 ∀ð Þ i; j ∈ A (8)

Ui ∈f g 0; …; jNj ∀i∈ N (10)

Yi ∈ f g 0; 1 ∀i∈I (9)

Xi,j ∀i∈ I (4)

Xi,j � ti,j ≤ d (7)

• Yi ∈f g 0; 1 is equal to 1 if POI i∈ I is selected for the visit, 0 otherwise;

• Ui ∈ f g 0;…; jNj is the position of POI i∈ N in the current trip.

X <sup>j</sup> <sup>∈</sup> <sup>N</sup> , <sup>j</sup>6¼<sup>i</sup>

> X <sup>j</sup><sup>∈</sup> N, <sup>i</sup>6¼<sup>j</sup>

Uj � Ui � 1 þ M � 1 � Xi,j

X i∈ J

mizing the cost of moving between the selected PoIs.

move along arc ð Þ i; j ∈ A and M a large positive constant.

The following decision variables are defined:

The problem can be formulated as follows:

6.1. First model

Figure 4. The map showing the PoIs chosen by the tourist (on the left), and the optimized itinerary (on the right).

The aim of the Tour Planner application is to make the visit of a destination accessible for everyone, addressing the described critical aspects through the following features:


## 6. Optimization modeling

Two optimization models are implemented to plan the tour of tourists. In the first model, a subset of PoIs is selected in order to maximize their attractiveness. In the second model, an optimal tour among this subset of PoIs is determined by solving a Traveling Salesman Problem: the tourist is given an optimal route where he/she visits each POI only once, minimizing the cost of moving between the selected PoIs.

#### 6.1. First model

The aim of the Tour Planner application is to make the visit of a destination accessible for

Figure 4. The map showing the PoIs chosen by the tourist (on the left), and the optimized itinerary (on the right).

1. The tourist defines the total amount of time he has to visit, his physical training level with

2. The application shows a list of most important Points of Interest, sorted according to the

3. The tourist can select each Point of Interest to get more information, including those related to accessibility, and then has the possibility to choose what to see during the visit.

4. The application connects the Points of Interest selected and optimizes the resulting path

Two optimization models are implemented to plan the tour of tourists. In the first model, a subset of PoIs is selected in order to maximize their attractiveness. In the second model, an optimal tour among this subset of PoIs is determined by solving a Traveling Salesman

everyone, addressing the described critical aspects through the following features:

respect to available paths, and the type of preferred attractions.

information described in 1.

42 Assistive Technologies in Smart Cities

6. Optimization modeling

producing a tour suitable to the tourist.

We consider the current location 0 of the tourist and a set I of POIs. A time interval d can be spent at most to visit a number POIs from the current location. Each POI is associated with a ranking pi representing its attractiveness for tourists and a visiting time vi.

The problem can be described as the following graph theoretic problem. Let G Nð Þ ; A be a direct and complete graph, where N is the node set and A the set of arcs connecting nodes of set N. Nodes correspond to the points of interest and the current position of the tourist, i.e., N ¼ I∪0. Arcs represent possible connections between two distinct nodes. Let ti,j be the time to move along arc ð Þ i; j ∈ A and M a large positive constant.

The following decision variables are defined:


The problem can be formulated as follows:

$$\text{Max}\sum\_{i\in\mathcal{I}} Y\_i \cdot p\_i \tag{1}$$

$$\sum\_{j \in \mathcal{J}} X\_{0,j} = 1 \tag{2}$$

$$\sum\_{j \in \mathcal{J}} X\_{j,0} = 1 \tag{3}$$

$$\sum\_{j \in N\_{\prime} \neq i} X\_{j,i} = \sum\_{j \in N\_{\prime} \neq i} X\_{i,j} \quad \forall i \in I \tag{4}$$

$$\sum\_{\substack{j \in N\_\ell \ i \neq j}} X\_{i,j} = Y\_i \quad \forall i \in I \tag{5}$$

$$\left(\mathcal{U}\_{\rangle} - \mathcal{U}\_{i} - \mathbf{1} + \mathcal{M} \cdot \left(\mathbf{1} - \mathcal{X}\_{i,j}\right) > = \mathbf{0} \quad \forall (i,j) \in A \tag{6}$$

$$\sum\_{i \in \mathcal{I}} Y\_i \cdot v\_i + \sum\_{(i,j) \in A} X\_{i,j} \cdot t\_{i,j} \le d \tag{7}$$

$$X\_{i,j} \in \{0, 1\} \quad \forall (i, j) \in A \tag{8}$$

$$Y\_i \in \{0, 1\} \quad \forall i \in I \tag{9}$$

$$\mathcal{U}\_i \in \{0, \ldots, |N|\} \quad \forall i \in \mathcal{N} \tag{10}$$

In (Eq. (1)) one maximizes the ranking generated by the selected POIs. According to (Eq. (2)), a PoI must be visited after the current location. Constraints (Eq. (3)) enforce for the tourist to come back to the current location after the visit of the last PoI. Constraints (Eq. (4)) guarantee that a tourists arriving at any PoI must also leave from that PoI. Constrains (Eq. (5)) link decisions variables on POIs selections and movement between nodes. Constraints (Eq. (6)) are the subtour elimination constraints of Miller, Tucker, and Zemlin. Constraints (Eq. (7)) enforce that the overall time spent to move between nodes and visit POIs is lower that the planned time interval. Finally, (Eq. (8)), (Eq. (9)), and (Eq. (10)) are the domain of decision variables.

It is worth noting that one does not have to visit all nodes of the N, unless a large value of d is considered. Moreover, the direct graph makes very easy to model the case in which starting and arrival points are different.

#### 6.2. Second model

Consider the subset N of nodes selected in the previous model. These nodes may not be visited in an effective order, as this model does not aim to minimize the costs of movement between nodes. To correct this drawback, we consider a second model, in which a formulation of the Traveling Salesman Problem (TSP) is presented. The solution of the TSP determined the socalled optimized itineraries mentioned throughout this paper.

The TSP can be described as the following graph theoretic problem. Let G N; A � � be a direct and complete graph, where A the set of arcs connecting nodes of set N. The following decision variables are defined:


The problem can be formulated as follows:

$$\text{Min}\sum\_{i \in \overline{\mathbb{N}}} \sum\_{j \in \overline{\mathbb{N}}} t\_{i,j} \cdot X\_{i,j} \tag{11}$$

in (Eq. (14)) are the subtour elimination constraints of Miller, Tucker, and Zemlin. Finally,

Using IoT for Accessible Tourism in Smart Cities http://dx.doi.org/10.5772/intechopen.77057 45

In this section we show the viability of the proposed tools to support the mobility of physically disabled tourists or elder persons. We also analyze the case of able-bodied tourists for the sake of comparison. The difference between the two cases is shown by increasing travel times along uphill and downhill routes for disabled tourists as opposed to able-bodied ones. The experimentation is carried out in the city of Cagliari, where many tourists disembark from cruise ships at the harbor. They typically aim to visit the oldest part of Cagliari, which is known as the Castello. It clings to the slopes of a hill that rises steeply from the harbor. Therefore, in this case study it is of particular relevance to distinguish between the waking times of disabled and able-bodies tourists, in order to properly plan which subset of PoI should be visited, as well as

Four classes of PoIs are considered, which correspond to different profiles of tourists interested in museums, monuments, gardens or shops. We took their location and their altitude from the open data platform and we derived the average slope of the streets connecting PoIs. The average travel time per unitary distance was calibrated by a sample of tourists with similar disabilities over a set of streets with different slopes. Since the distance between all PoIs is

All the PoIs are ranked with a value ranging from 1, less attractive, to 5, most attractive. A subset of PoIs is considered for each class by a score threshold, which specifies the PoIs the tourist wants to visit. For example, if it taken on value 2, we consider all PoIs with a score bigger than or equal to 2. We initially set the score threshold to 3 and relax the constrain on (7) and compute the itineraries for each class of PoIs. In Figure 5 the time to visit all PoIs is

(Eq. (15)) and (Eq. (16)) are the domain of decision variables.

known, we easily derived the travel times among them.

Figure 5. Minimum time for optimized itineraries with threshold = 3.

reported for all class of PoIs in four cases:

7. Results

the order of the visit.

$$\sum\_{j \in \overline{N}\_{\prime} \neq i} X\_{i,j} = 1 \quad \forall i \in \overline{N} \tag{12}$$

$$\sum\_{j \in \overline{N}, j \neq i} X\_{j,i} = 1 \quad \forall i \in \overline{N} \tag{13}$$

$$\left(\mathcal{U}\_{j} - \mathcal{U}\_{i} - 1 + M \cdot \left(1 - X\_{i,j}\right) > = 0 \quad \forall (i,j) \in \overline{A} \tag{14}$$

$$X\_{i,j} \in \{0, 1\} \quad \forall (i, j) \in \overline{A} \tag{15}$$

$$\mathcal{U}l\_i \in \{0...N\} \quad \forall i \in \overline{N} \tag{16}$$

In (Eq. (11)) one maximizes the ranking generated by the selected POIs. According to (Eq. (12)) and (Eq. (13)), a node must be visited before and after the current one, respectively. Constraints in (Eq. (14)) are the subtour elimination constraints of Miller, Tucker, and Zemlin. Finally, (Eq. (15)) and (Eq. (16)) are the domain of decision variables.
