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- Evaluating the potential of adaptive comfort approach using historic data to reduce energy consumption in buildings in southern SpainPublication . Bienvenido-Huertas, David; Rubio-Bellido, Carlos; Farinha, Fátima; Oliveira, Miguel José; Pérez-Ordóñez, Juan LuisThe application of adaptive comfort models is among the determinant factors to reduce greenhouse gas emissions in the building sector. This research studies the region of Andalusia (south of Spain). A cluster analysis is applied to 786 Andalusian municipalities, and 4 groups are established according to the potential of adaptive strategies. A town is chosen from each group, and an hourly specific study is conducted for the last 20 years, as well as a daily study of the old time series by using an artificial neural network based on the existing climate data. The possibility of application of the EN 16798-1:2019 standard during the days of the year is analysed, as well as the possibilities of using natural ventilation and the possibility of using adaptive setpoint temperatures in comparison with both 3 fixed heating temperatures and 3 fixed cooling temperatures by considering the energy saving. The results to apply the standard ranged 69.0 and 100% of the days of each year. The possibilities of natural ventilation considered were greater than 10% of the hours of the year in all the assumptions. The energy saving of cooling degrees reveals a greater potential in the area studied than that of heating degrees; this tendency is supported by the study of old temporary series which are part of the climate variation predicted throughout the 21st century.
- Sustainable competitiveness of tourism in the Algarve region. Critical stakeholders’ perception of the supply sectorPublication . Farinha, Fátima; Bienvenido-Huertas, David; Duarte Pinheiro, Manuel; Da Silva, Elisa Maria De Jesus; Lança, Rui; Oliveira, Miguel José; Batista, RicardoThe Algarve region, located in the south of Portugal, is a well-known tourism destination that seeks to be sustainable and competitive. The local administration looks to establish a collaborative network, where stakeholders take a crucial role. The research aims to appeal to the accommodations and food services stakeholders to have a shared vision of the issues and priorities related to sustainable tourism development. Their perception is a critical factor in making decisions regarding the region’s competitiveness. Algarve’s two major and leading associations of the tourism supply sector AIHSA and AHETA were invited to participate in the study. Based on the responses of an online questionnaire, an artificial intelligence algorithm was applied to the data to identify the common and divergent aspects. The conceptual model developed is based on a simplified model of psychological ownership. The results highlight a convergent perspective regarding sustainability challenges, namely, natural resources and biodiversity, safety, and supply chain. However, hotels and restaurants do not reflect the same perception regarding sustainability initiatives, e-tourism, or free internet access. These divergences are essential results since they indicated which issues require local authorities’ priority intervention.
- Comparison of artificial intelligence algorithms to estimate sustainability indicatorsPublication . Bienvenido-Huertas, David; Farinha, Fátima; Oliveira, Miguel José; Da Silva, Elisa Maria De Jesus; Lança, Ruithe monitoring of sustainability indicators allows behavioural tendencies of a region to be controlled, so that adequate policies could be established in advance for a sustainable development. However, some data could be missed in the monitoring of these indicators, thus making the establishment of sustainability policies difficult. This paper therefore analyses the possibility to forecast the sustainability indicators of a region by using four different artificial intelligent algorithms: linear regression, multilayer perceptron, random forest, and M5P. the study area selected was the Algarve region in Portugal, and 180 monitored indicators were analysed between 2011 and 2017. the results showed that M5P is the most appropriate algorithm to estimate sustainability indicators. M5P was the algorithm obtaining the best estimations in a greater number of indicators. Nevertheless, the results showed that MP5 was not the best option for all indicators, since in some of them, the use of other algorithms obtained better results, thus reflecting the need of an individual previous study of each indicator. With these algorithms, it is possible for public bodies and institutions to evaluate the sustainable development of the region and to have reliable information to take corrective measures when needed, thus contributing to a more sustainable future.
- Selection process of sustainable indicators for the Algarve Region—OBSERVE ProjectPublication . Farinha, Fátima; Oliveira, Miguel José; Da Silva, Elisa Maria De Jesus; Lança, Rui; Pinheiro, Manuel Duarte; Miguel, CátiaThe selection of indicators for the Observatory of Sustainability of the Algarve Region for Tourism (OBSERVE), poses challenges, namely which indicators are relevant to stakeholders and how to assure that information is available. To support the selection of the environmental, sociocultural, economic and institutional indicators, an engagement process was designed and applied, which included meetings with stakeholders, a workshop and an online survey. The results showed that both workshop and online surveys reflected, in general, similar opinions, thus allowing the selecting of the sustainable development indicators for the Algarve region. Additionally, the results showed that nearly 75% of the indicators can be obtained from national statistics and, therefore, can be used on the OBSERVE project, assuring a quick flow of information. As limitations, it is important to mention that the other 25% will need further development, in order to provide data for indicators, like carbon management and client satisfaction. With this approach, the observatory will survey and evaluate the sustainable development of the region (status and trends), based on indicators that answer to the strategic needs of system's main users, with social and economic implications, i.e., public institutions, economic agents, tourists, local communities and residents.