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Detection of activities in bathrooms through deep learning and environmental data graphics images
No full textAutomatic detection activities in indoor spaces has been and is a matter of great interest. Thus, in the field of health surveillance, one of the spaces frequently studied is the bathroom of homes and specifically the behaviour of users in the said space, since certain pathologies can sometimes be deduced from it. That is why, the objective of this study is to know if it is possible to automatically classify the main activities that occur within the bathroom, using an innovative methodology with respect to the methods used to date, based on environmental parameters and the application of machine learning algorithms, thus allowing privacy to be preserved, which is a notable improvement in relation to other methods. For this, the methodology followed is based on the novel application of a pre-trained convolutional network for classifying graphs resulting from the monitoring of the environmental parameters of a bathroom. The results obtained allow us to conclude that, in addition to being able to check whether environmental data are adequate for health, it is possible to detect a high rate of true positives (around 80%) in some of the most frequent and important activities, thus facilitating its automation in a very simple and economical way
The Accident Rate in the Construction Sector: A Work Proposal for Its Reduction through the Standardization of Safe Work Processes
No full textThe statistics on work-related accidents published by the responsible organizations reveal that the average rate of work accidents within the construction sector is more than double that in other industrial sectors. This serious problem has been analyzed by numerous international organizations and institutes dedicated to occupational safety, health and welfare. Therefore, in this article, some results of a research project that aims to reduce workplace accidents through the standardization of safe work processes and procedures in construction sites are summarized. The proposed methodology consisted of the analysis of national and international bibliographies to analyze the different annual variations in the accident rate, allowing a common pattern to be located, as well as its association with the work processes carried out in construction projects to standardize each of the processes which are present in the execution and life phases of the building. It is possible to conclude that the accident rates can be reduced and/or eliminated with the application of each of the processes thanks to the obtained results
Can mussel shell waste optimize cement and air lime mortars hygrothermal performance?
No full textMussel shells used as aggregates for mortars have flaky and irregular particles, which significantly increases the pore volume. This leads to the identification the microstructure of mussel shell mortars as a light and porous composite, which could have good hygrothermal properties. In the present study, the density and thermal properties are assessed on cement and air lime mortars, each with three replacement percentages of replacement of conventional sand by mussel shell sand (25 %, 50 % and 75 %), are evaluated and compared with their respective baselines (0 % replacement). Thermal conductivity measurements are also carried out on different loose fractions of the mussel shell aggregate to understand the behaviour of this material without binder matrix. Finally, adsorption and desorption cycles at 80 % and 50 % relative humidity are carried out on loose aggregate fractions and on the eight mortars. The results are very positive for the mussel shell mortars, as it can be concluded that the use of mussel shell aggregates improves the thermal performance and the potential moisture buffering capacity of both cement and air-lime coating mortars
A Simplified Framework to Integrate Databases with Building Information Modeling for Building Energy Assessment in Multi-Climate Zones
No full textBIM models are seldom used for the energy certification of buildings. This paper discusses the advantages of linking two important fields: building information modeling (BIM) and building environmental assessment methods (BEAM), presented as a rating system and a proposal for the Chilean context. The state of the art in both fields around the world is discussed, with an in-depth examination of current BIM software and related applications, followed by a discussion about previous research on integrating them. A lack of interoperability and data losses between BIM and BEM were found. A new tool is presented that addresses these challenges to ensure accurate rating system data, and this new framework is based on database exchange and takes crucial information from BIM to BEAM platforms. The development of the method includes BIM programming (API), database links, and spreadsheets for a Chilean building energy certification through a new tool, also applicable to multiclimactic zones. This new semi-automatic tool allows architects to model their design in a BIM platform and use this information as input for the energy certification process. The potential and risks of this method are discussed. Several improvements and enhancements of the energy certification process were found when incorporating this new framework in comparison to current methodologies
Characterisation, symptom pattern and symptom clusters from a retrospective cohort of Long COVID patients in primary care in Catalonia
No full textBackground: Around 10% of people infected by SARS-COV-2 report symptoms that persist longer than 3 months. Little has been reported about sex differences in symptoms and clustering over time of non-hospitalised patients in primary care settings. Methods: This is a descriptive study of a cohort of mainly non-hospitalized patients with a persistence of symptoms longer than 3 months from the clinical onset in co-creation with the Long Covid Catalan affected group using an online survey. Recruitment was from March 2020 to June 2021. Exclusion criteria were being admitted to an ICU, < 18 years of age and not living in Catalonia. We focused on 117 symptoms gathered in 18 groups and performed cluster analysis over the first 21 days of infection, at 22–60 days, and ≥ 3 months. Results: We analysed responses of 905 participants (80.3% women). Median time between symptom onset and the questionnaire response date was 8.7 months. General symptoms (as fatigue) were the most prevalent with no differences by sex, age, or wave although its frequency decreased over time (from 91.8 to 78.3%). Dermatological (52.1% in women, 28.5% in men), olfactory (34.9% women, 20.9% men) and neurocognitive symptoms (70.1% women, 55.8% men) showed the greatest differences by sex. Cluster analysis showed five clusters with a predominance of Taste & smell (24.9%) and Multisystemic clusters (26.5%) at baseline and _Multisystemic (34.59%) and Heterogeneous (24.0%) at ≥3 months. The Multisystemic cluster was more prevalent in men. The Menstrual cluster was the most stable over time, while most transitions occurred from the Heterogeneous cluster to the Multisystemic cluster and from Taste & smell to Heterogeneous. Conclusions: General symptoms were the most prevalent in both sexes at three-time cut-off points. Major sex differences were observed in dermatological, olfactory and neurocognitive symptoms. The increase of the Heterogeneous cluster might suggest an adaptation to symptoms or a non-specific evolution of the condition which can hinder its detection at medical appointments. A carefully symptom collection and patients’ participation in research may generate useful knowledge about Long Covid presentation in primary care settings
Long-term performance evaluation of low-cost sensors using AI-driven tools
No full textIn civil engineering and architectural applications, Micro Electro-Mechanical System (MEMS) accelerometer-based inclinometers are widely used due to their costeffectiveness. However, a major challenge associated with these devices is their long-term dura
Digital Revolution: Emerging Technologies for Enhancing Citizen Engagement in Urban and Environmental Management
No full textCitizen participation is key in urban planning, but traditional methods are often limited in terms of accessibility and inclusion. This study investigates how the use of emerging technologies such as Virtual and Augmented Reality (VR/AR), Digital Twin (DT), Building Information Modelling (BIM), Artificial Intelligence (AI), and Geographic Information Systems (GIS) can enhance citizen participation in urban planning. Through the review and analysis of existing literature, combined with the study of cases from cities in Eurasia and North America on the implementation of these technologies in urban and environmental planning, the results indicate that the use of multi-reality technologies facilitates immersive visualization of urban projects, allowing citizens to better understand the implications of proposed changes. Furthermore, the integration of real-time monitoring, such as forest and climate surveillance, improves environmental control. Technologies like AI and GIS also enable greater precision and empowerment in participatory decision-making. Nevertheless, the emergence of these technologies presents a challenge that must be addressed, as it is essential to establish a regulatory framework to ensure their responsible use. In conclusion, these platforms not only increase participation and co-creation but also enable more efficient, sustainable, and inclusive urban planning. Greater adoption of these technologies is suggested to optimize the urban decision-making process
Real estate and sustainable crisis management in urban environments: Challenges and solutions for resilient cities
No full textThe aim of this book is to promote the dynamic resilience of societies by identifying, analysing, and exemplifying the role of space and land use in both anticipated and unanticipated primary and secondary crisis situations. The book brings together the expertise of a unique team of researchers and methods from fields of futures studies, land use planning, social sustainability and wellbeing, architecture, spatial planning, design and real estate economics, and presents a novel understanding of the direct and indirect impacts of possible crises in the space and land use context. It goes on to discuss the concept of resilience and exemplifies potential solutions and offers a holistic and forward-looking approach for crisis management through a lens of social sustainability and wellbeing, making an important contribution to the promotion of wellbeing in the built environment, especially in terms of land and residential space and building use. This book does not only identify barriers and successful incentives in resilient crisis management but also discusses the role of different stakeholders (e.g., households, office workers, real estate owners, space occupants, firms, the public sector, etc.) in crisis management. Finally, international case studies aiming to tackle the challenging landscape of future threats are presented, along with novel tools to support the development of future policies, regulations, and management practices in the built environment, which can increase the dynamic resilience of societies. Overall, this book is essential reading for decision-makers in the public and private sectors, urban developers, space and spatial designers, architects, planners, community stakeholders, real estate investors, facility managers and crisis and corporate responsibility managers
Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 2: Implementation
No full textThe economic cost of repairing corrosion-affected reinforced concrete structures (RCSs) means that reliable and accurate assessment and early detection methods must be sought after. Conventional techniques, such as visual inspections, or measuring either cover layer resistivity or the corrosion potential, are methods that require accessibility and involve personnel having to travel to take in situ measurements. Monitoring by embedded sensors is a much more efficient approach that allows early detection by remote sensing. This work presents the implementation of a new measurement protocol regarding the existing monitoring system called INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring). Along with the corrosion intensity measurement in embedded sensors, it also proposes monitoring the double layer capacity of the sensors’ responses. It aims to determine, along with the rebars’ corrosion rate, the triggering agent of the corrosion process. This study was carried out using three reinforced concrete scaled columns that were exposed to different environments. The results demonstrate with this new protocol that the remote INESSCOM monitoring system can establish the corrosion rate and identify the precursor agent of corrosion (carbonation or chlorides), even when the recorded corrosion rates are similar
Hotel Áurea Palacio de Correos, en Logroño. Una esmerada vista al pasado
No full textTras años de abandono, el antiguo edificio de Correos de Logroño luce hoy su mejor aspecto gracias a la rehabilitación llevada a cabo para convertirse en un hotel de cinco estrellas. Una renovación que se ha efectuado con el respeto y especial cuidado que merece el tiempo anterior