Abstract
Point cloud processing is an essential task in many applications in the AEC domain, such as automated progress assessment, quality control and 3D reconstruction. As much of the procedure used to process the point clouds is shared among these applications, we identify common processing steps and analyse relevant algorithms found in the literature published in the last 5 years. We start by describing current efforts on both progress and quality monitoring and their particular requirements. Then, in the context of those applications, we dive into the specific procedures related to processing point clouds acquired using laser scanners. An emphasis is given to the scan planning process, as it can greatly influence the data collection process and the quality of the data. The data collection phase is discussed, focusing on point cloud data acquired by laser scanning. Its operating mode is explained and the factors that influence its performance are detailed. Data preprocessing methodologies are presented, aiming to introduce techniques used in the literature to, among other aspects, increase the registration performance by identifying and removing redundant data. Geometry extraction techniques are described, concerning both interior and outdoor reconstruction, as well as currently used relationship representation structures. In the end, we identify certain gaps in the literature that may constitute interesting topics for future research. Based on this review, it is evident that a key limitation associated with both Scan-to-BIM and Scan-vs-BIM algorithms is handling missing data due to occlusion, which can be reduced by multi-platform sensor fusion and efficient scan planning. Another limitation is the lack of consideration for laser scanner performance characteristics when planning the scanning operation and the apparent disconnection between the planning and data collection stages. Furthermore, the lack of representative benchmark datasets is hindering proper comparison of Scan-to-BIM and Scan-vs-BIM techniques, as well as the integration of state-of-the-art deep-learning methods that can give a positive contribution in scene interpretation and modelling.

Abstract

Abstract
Planning consists of thinking about the future and allows territories to be better prepared to take advantage of opportunities and face challenges that arise. In Portugal, tourism is one of the pillars of the economy, generating wealth and creating various job openings. In recent years, this destination has won several international awards and distinctions due to the quality of services and tourism offerings. Part of this success is due to the planning carried out by the entity responsible, Turismo de Portugal. This study aims to analyse the content and structure of national tourism plans implemented in Portugal since 2000. Furthermore, we want to understand: (1) the vision outlined for the Portuguese territory and the changes it has undergone in recent decades; (2) the methodologies that were used in the formation process of these plans, for instance, if public auscultation was used; (3) the main objectives defined for the territory and which were the actions that have been defined to achieve them. A qualitative methodology of document analysis was used, combined with the presentation of a case study related to tourism planning at a national level. The results show the growing importance of the tourism sector for the Portuguese economy. Since 2020, the growing involvement of stakeholders in the construction of strategic plans has also been evident through public consultation and an emphasis on sustainability practices in the tourism sector.

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Abstract
Measuring gas and liquid flow rate is paramount in various scientific and industrial applications. This work presents an optical fiber flowmeter based on a graphene oxide (GO) coated Michelson interferometer. The interferometer is fabricated using a long-period fiber grating (LPFG) followed by a GO-coated single-mode fiber (SMF). By radiating the GO coating, it experiences photothermic effect that induces local heating of the film. This results in a variation in the effective refractive index in the cladding modes, which induces a phase shift on the interferometer spectrum. When a gas flow is introduced near the coated fiber, the hot-wire region will experience a reduction in temperature proportional to the flow rate. The flowmeter exhibited a linear wavelength shift to the flow rate with an absolute sensitivity of 17.4 +/- 0.8 pm/(L.min-1) for gas flow rates between 2 and 8 L/ min. Furthermore, the dynamic response of the sensor was studied, attaining a maximum response time of 1.1 +/- 0.4 s

Abstract
Energy storage systems, integrated in Renewable Energy Communities (REC), are enabling the development of operation strategies together with Photovoltaic (PV) systems. Additionally, Local Energy Markets (LEM) are emerging mechanisms to enable local energy trading in RECs, the integration of storage systems can increase the community energy savings and profits. In this context, a market environment was modelled as a Markov Decision Process (MDP). In this scope, an Agent Based Model (ABM) using the Q-Learning mechanism was used to implement and to simulate a LEM and its interaction with the Wholesale Market (WSM), also considering an architecture with storage systems. The developed model was tested considering real data regarding energy consumption and PV generation. The paper describes and discusses the obtained market strategy and the profits that can be obtained with this approach.