12,924 research outputs found
Tourism cloud management system: the impact of smart tourism.
This study investigates the possibility of supporting tourists in a foreign land intelligently, by using the Tourism Cloud Management System (TCMS) to enhance and better their tourism experience. Some technologies allow tourists to highlight popular tourist routes and circuits, through the visualisation of data and sensor clustering approaches. With this, a tourist can access the shared data on a specific location to know the sites of famous local attractions, how other tourists feel about them, and how to participate in local festivities through a smart tourism model. This study surveyed the potential of smart tourism among tourists and how such technologies have developed over time, while proposing a TCMS. Its goals were to make physical/paper tickets redundant via the introduction of a mobile app with eTickets that can be validated using camera-based and QR code technologies, and to enhance the transport network using Bluetooth and GPS for real-time identification of tourists' proximity. The results show that a significant number of participants engage in tourist travels, hence the need for smart tourism and tourist management. It was concluded that smart tourism is very appealing to tourists and can improve the appeal of the destination, if smart solutions are implemented. This study gives a first-hand review of the preference of tourists and the potential of smart tourism
Tourism cloud management system: the impact of smart tourism
Abstract
This study investigates the possibility of supporting tourists in a foreign land intelligently by using the Tourism Cloud Management System (TCMS) to enhance and better their tourism experience. Some technologies allow tourists to highlight popular tourist routes and circuits through the visualisation of data and sensor clustering approaches. With this, a tourist can access the shared data on a specific location to know the sites of famous local attractions, how other tourists feel about them, and how to participate in local festivities through a smart tourism model. This study surveyed the potential of smart tourism among tourists and how such technologies have developed over time while proposing a TCMS. Its goals were to make physical/paper tickets redundant via the introduction of a mobile app with eTickets that can be validated using camera and QR code technologies and to enhance the transport network using Bluetooth and GPS for real-time identification of tourists’ presence. The results show that a significant number of participants engage in tourist travels, hence the need for smart tourism and tourist management. It was concluded that smart tourism is very appealing to tourists and can improve the appeal of the destination if smart solutions are implemented. This study gives a first-hand review of the preference of tourists and the potential of smart tourism
Semantic-based adaptive mission planning for unmanned underwater vehicles
Current underwater robotic platforms rely upon waypoint-based scripted missions which
are described by the operator a-priori. This renders systems incapable of reacting to
the unexpected. In this thesis, we claim that the ability to autonomously adapt the
decision making process is the key to facilitating the change over from human intervention
to intelligent autonomy. We identify goal-based declarative mission planning
as an attractive solution to autonomous adaptability because it combines autonomous
decision making with higher levels of human interaction.
Goal-based mission planning requires the use of abstract knowledge representation
and situation awareness to link the prior knowledge provided by the operator with
the information coming from the processed sensor data. To achieve this, we propose
a semantic-based knowledge representation framework that allows this integration of
prior and processed information among all different agents available in the platform.
In order to evaluate adaptive mission planning techniques, we also introduce a novel
metric which measures the proximity between plans. We demonstrate that this metric
is better informed than previous metrics for measuring the adaptation process.
In this thesis we implement three different approaches to goal-based mission planning
in order to investigate which approach is most appropriate under different circumstances.
The first approach, continuous mission planning, focusses on long-term
deployment. This approach is based on a continuous re-assessment of the status of
the mission environment. Using our proximity metric, we evaluated this approach
and show that there is a high degree of similarity between our approach and the humanly
driven adaptation, both in a known static environment and in a partially-known
dynamic discoverable environment. The second, service-oriented mission planning,
makes use of the semantic framework to provide autonomous mission planning for
the dynamic discovery of the services published by the different agents in the system.
This allows platform independence, easing the manual creation of mission plans, and
robustness to changes. We show that this approach produces the same plans as the
baseline which was explicitly provided with the platform configuration. The last approach,
mission plan repair, handles the scenario where small changes occur in the
mission environment and there are limited resources for planning. We develop and
deploy a mission plan repair approach within a semantic-based autonomous planning
system in a real underwater vehicle. Experiments demonstrate that the integrated system
is capable of providing mission adaptation for maintaining the operability of the
host platform in the face of unexpected events
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