RoomFort: An Ontology-Based Comfort Management Application for Hotels

Spoladore, Daniele; Arlati, Sara; Carciotti, Sara; Nolich, Massimiliano; Sacco, Marco

doi:10.3390/electronics7120345

Cited by 25 publications

(24 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following the NeOn Methdology [41] for ontological resources reuse and development, E-Cabin framework reuses part of the SSN ontology for the description of IoT devices deployed in the smart environment, while adopting the ontology design patterns provided in Ref. [30] for the modelling of the passenger and his/her health condition. Finally, for indoor comfort metrics, E-Cabin monitors air quality (i.e., CO2 concentration), illuminance and indoor temperature and humidity leveraging on a domain ontology developed from scratch.…”

Section: The Proposed Novel Decision Making Framework For Smart Enmentioning

confidence: 99%

Cabin as a Home: A Novel Comfort Optimization Framework for IoT Equipped Smart Environments and Applications on Cruise Ships

Nolich

Spoladore

Carciotti

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

The international tourism competition poses new challenges to the cruise sector, such as the achievement of the tourists’ satisfaction and the increase in on board comfort. Moreover, the growing sophistication of tourists’ needs leads to a more user-centric touristic offer. Consequently, a personalized cabin environment, which fits the users’ activities and their characteristics, could be a plus value during the cruise vacation. These topics, however, are strictly connected with the diffusion of digital technologies and dynamics, which represent the tools to achieve the goal of a customized on-cruise experience. This paper presents E-Cabin, a novel Internet of Things (IoT) framework architecture that has at its core a reasoning system tuned on data gathered from the environment and from each specific passenger and the activities he/she performs. The framework leverages on knowledge representation with ontologies and consists of a publisher–subscriber communication framework that allows all of the IoT applications to use the reasoner and the provided ontologies. The paper demonstrates the proposed system in a demo cruise cabin where, by using the E-Cabin application, it is possible to set various atmospheres based on the users and activities occurring in the cabin.

show abstract

Section: The Proposed Novel Decision Making Framework For Smart Enmentioning

confidence: 99%

Cabin as a Home: A Novel Comfort Optimization Framework for IoT Equipped Smart Environments and Applications on Cruise Ships

Nolich

Spoladore

Carciotti

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…The use of information and communication technologies increases the value of tourism services and products and contributes to the development of industrial networks. Information and communication technologies (ICT) cover the entire travel value chains such as accommodation, information on destination, transportation, package tours and services [12]. The main area of change in innovation in the field of tourism is the use of ICT.…”

Section: Jeju Island a Tourists Hubmentioning

confidence: 99%

Design and Development of a Real-Time Optimal Route Recommendation System Using Big Data for Tourists in Jeju Island

2019

View full text Add to dashboard Cite

Nowadays researchers and engineers are trying to build travel route recommendation systems to guide tourists around the globe. The tourism industry is on the rise and it has attracted researchers to provide such systems for comfortable and convenient traveling. Mobile internet growth is increasing rapidly. Mobile data usage and traffic growth has increased interest in building mobile applications for tourists. This research paper aims to provide design and implementation of a travel route recommendation system based on user preference. Real-time big data is collected from Wi-Fi routers installed at more than 149 unique locations in Jeju Island, South Korea. This dataset includes tourist movement patterns collected from thousands of mobile tourists in the year 2016–2017. Data collection and analysis is necessary for a country to make public policies and development of the global travel and tourism industry. In this research paper we propose an optimal travel route recommendation system by performing statistical analysis of tourist movement patterns. Route recommendation is based on user preferences. User preference can vary over time and differ from one user to another. We have taken three main factors into consideration to the recommend optimal route i.e., time, distance, and popularity of location. Beside these factors, we have also considered weather and traffic condition using a third-party application program interfaces (APIs). We have classified regions into six major categories. Popularity of location can vary from season to season. We used a Naïve Bayes classifier to find the probability of tourists going to visit next location. Third-party APIs are used to find the longitude and latitude of the location. The Haversine formula is used to calculate the distance between unique locations. On the basis of these factors, we recommend the optimal route for tourists. The proposed system is highly responsive to mobile users. The results of this system show that the recommended route is convenient and allows tourists to visit maximum number of famous locations as compared to previous data.

show abstract

“…RoomFort, a smart comfort management system is developed to enhance the comfort of hotel room guests. It provides a set of domain ontologies to formalize comfort-related metrics and to exploit the automatic reasoning capabilities provided by Semantic Web technologies while gathering data through a network of sensors to ensure guests are provided with tailored comfort profiles during their stays in the hotel [15]. Automatic detection of unusual crowd dynamics using geotagged posts on location-based social networks (LBSNs) is proposed in [16].…”

Section: The Present Issuementioning

confidence: 99%