Luis Álvarez Sabucedo

The classification and identification of individual tree species in forest environments are critical for biodiversity conservation, sustainable forestry management, and ecological monitoring. Recent advances in drone technology and artificial intelligence have enabled new methodologies for detecting and classifying trees at an individual level. However, significant challenges persist, particularly in heterogeneous forest environments with high species diversity and complex canopy structures. This systematic review explores the latest research on drone-based data collection and AI-driven classification techniques, focusing on studies that classify specific tree species rather than generic tree detection. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, peer review studies from the last decade were analyzed to identify trends in data acquisition instruments (e.g., RGB, multispectral, hyperspectral, LiDAR), preprocessing techniques, segmentation approaches, and machine learning (ML) algorithms used for classification. Findings of this study reveal that deep learning (DL) models, particularly convolutional neural networks (CNN), are increasingly replacing traditional ML methods such as random forest (RF) or support vector machines (SVMs) because there is no need for a feature extraction phase, as this is implicit in the DL models. The integration of LiDAR with hyperspectral imaging further enhances classification accuracy but remains limited due to cost constraints. Additionally, we discuss the challenges of model generalization across different forest ecosystems and propose future research directions, including the development of standardized datasets and improved model architectures for robust tree species classification. This review provides a comprehensive synthesis of existing methodologies, highlighting both advancements and persistent gaps in AI-driven forest monitoring.

(1) Background: Increasing life expectancy allows for more age-related health issues. Enhancing physical, cognitive, mental, and social health is crucial. Promoting healthy habits combats stress and diseases. Recommendation systems, like collaborative filtering, tailor suggestions but face challenges. Techniques such as artificial intelligence and machine learning are vital. Personalized health recommendations improve lifestyles and mitigate issues. (2) Methods: A systematic review adhering to the general principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was conducted with the aim of identifying articles on innovative research about using recommendation algorithms, machine learning, or artificial intelligence to promote healthy habits and active aging. (3) Results: A total of 34 articles were included in this work. They address the topic of recommendation systems that use machine learning or artificial intelligence in the promotion of healthy habits. (4) Conclusions: This article reviews health-related activity recommendation techniques for the general population. With rising life expectancy and common health issues, effective recommendations are crucial for future public health. Limitations include excluding simpler models. Despite many proposals, systematic adherence mechanisms are lacking. Developing traceable, verifiable systems for healthy activity recommendations is vital for aging populations in developed countries.

El objetivo fue desarrollar y evaluar una herramienta de gamificación para promover hábitos saludables utilizando blockchain. Se realizó un estudio pre-experimental con una muestra de conveniencia en la Facultad de Ciencias de la Actividad Física y del Deporte de la Universidad de Vigo, con 47 participantes sanos (36 hombres y 11 mujeres), de 21,5 ± 2,3 años. Se desarrolló un entorno de gamificación híbrido que combina tecnología blockchain y bases de datos tradicionales para fomentar hábitos saludables a través de retos, recompensando de forma automática y transparente al usuario. La herramienta, accesible mediante una interfaz web, busca mejorar la adopción de estas prácticas. El sistema fue evaluado utilizando la Escala de Usabilidad del Sistema, con el test Alpha de Cronbach aplicado para medir su fiabilidad. La herramienta obtuvo una puntuación de 78,09 ± 10,63 puntos, con un máximo de 97,5 y un mínimo de 47,5, situándola en la categoría “Buena” en la Escala de Usabilidad del Sistema, a la que se le aplicó el Alpha de Cronbach, mostrándose una consistencia interna aceptable con un valor de 0,77. Se ha desarrollado una plataforma que utiliza la gamificación para fomentar hábitos saludables, apoyada en tecnología blockchain. El prototipo recompensa los desafíos de salud completados y ha demostrado alta usabilidad. La plataforma aprovecha las ventajas del blockchain, como la transparencia y confiabilidad en los datos, sin necesidad de intermediarios. Además, respeta la privacidad del usuario, mejorando su experiencia en la práctica de actividad física. Palabras clave: actividad física, sedentarismo, salud, blockchain, gamificación, calidad de vida. The objective was to develop and evaluate a gamification tool to promote healthy habits using blockchain technology. A pre-experimental study was conducted with a convenience sample at the Faculty of Physical Activity and Sports Sciences, University of Vigo, involving 47 healthy participants (36 men and 11 women), aged 21.5 ± 2.3 years. A hybrid gamification environment was developed, combining blockchain technology with traditional databases to foster healthy habits through challenges, rewarding users automatically and transparently. The tool, accessible through a web interface, aims to improve the adoption of these practices. The system was evaluated using the System Usability Scale, with the Alpha Cronbach test applied to measure its reliability. The tool scored 78.09 ± 10.63 points, with a maximum of 97.5 and a minimum of 47.5, placing it in the “Good” category on the System Usability Scale. The Cronbach's Alpha test showed an acceptable internal consistency, with a value of 0.77. A platform was developed using gamification to promote healthy habits, supported by blockchain technology. The prototype rewards completed health challenges and has demonstrated high usability. The platform takes advantage of blockchain's benefits, such as transparency and reliability in data handling, without the need for intermediaries. Additionally, it respects user privacy, improving the overall experience in practicing physical activities. Keywords: physical activity, sedentary lifestyle, health, blockchain, gamification, quality of life.

(1) Background: In developed countries, public health faces a number of problems, including sedentary lifestyles and poor diets, which collectively contribute to the occurrence of preventable diseases. Noncommunicable diseases represent the leading cause of global mortality. Despite the promotion of healthy living, compliance remains a significant challenge. The integration of gamification into health apps has been demonstrated to facilitate behavioral change. Blockchain technology enhances the effectiveness of gamification by providing data trustability and support for auditable incentives. This feature is possible and easy due to the inherent characteristics of blockchain automating processes through Smart Contracts, rewarding participants and creating leaderboards in a transparent and reliable manner. The use of smart contracts and events enhances the traceability and reliability of decentralized applications, including healthcare. Interoperability in blockchain tools facilitates the deployment of complex environments. The aim of this research is the deployment of a tool for the implementation and testing of a gamification platform based on blockchain technology. (2) Methods: Pre-experimental research was carried out to assess the usability of the decentralized application developed. (3) Results: A decentralized application was developed with the objective of gamifying healthy habits. The application was evaluated using the System Usability Scale, obtaining a score of 80.49, and the Cronbach’s Alpha score, which was found to be 0.75. (4) Conclusions: A prototype of a decentralized application connected with a blockchain network to reward challenge fulfilment was deployed. Despite being in early development, it demonstrated high usability. Employing blockchain technology guarantees transparency and traceability while remaining in compliance with legal requirements like the General Data Protection Regulation.

Background: The COVID-19 pandemic has worsened sedentary lifestyles and unhealthy eating habits. It is crucial to promote proper training and healthy habits for all to prevent physical and cognitive decline. This should be a priority in health and education initiatives to reduce deaths and noncommunicable diseases. Guidelines for nutrition, physical activity, and sleep emphasize the importance of healthy habits. The goal is to develop a recommendation tool with a diverse range of challenges to positively impact users’ health. Methods: The process involves thoroughly obtaining precise user profiles through widely used questionnaires such as the Short-Form Health survey, the short Healthy Eating Index, and the Oviedo Sleep Questionnaire, and characterizing the challenges. Then, an algorithm will be developed to identify and prioritize the most suitable challenges for each user, ensuring personalized recommendations. Results: A pool of 30 health challenges was created based on reputable recommendations and experts. The system underwent validation by external experts and received positive user feedback, confirming its effectiveness. The panel of experts and users validated the personalized and reliable recommendations. Conclusions: Simple lifestyle interventions have shown promise for primary prevention in developed countries. A prototype system has been created to evaluate the individual weakness of users and suggest evidence-based lifestyle challenges. The system conducts a thorough health assessment and ensures feasibility for preventive purposes. Validation has proven the system’s effectiveness in recommending health-enhancing challenges with no adverse effects. The design of the model supports the seamless addition of new challenges by eventual third parties, ensuring interoperability and scalability.

Background: Low adherence to healthy habits, which is associated with a higher risk of disease and death, among citizens of Organization for Economic Co-operation and Development countries is a serious concern. The World Health Organization (WHO) and the physical activity (PA) guidelines for Americans provide recommendations on PA and healthy diets. To promote these habits, we suggest using a blockchain-based platform, using the PA Messaging Framework to deliver messages and rewards to users. Blockchain is a decentralized secure platform for data management, which can be used for value-added controls and services such as smart contracts (SCs), oracles, and decentralized applications (dApps). Of note, there is a substantial penetration of blockchain technologies in the field of PA, but there is a need for more implementations of dApps to take advantage of features such as nonfungible tokens. Objective: This study aimed to create a comprehensive platform for promoting healthy habits, using scientific evidence and blockchain technology. The platform will use gamification to encourage healthy PA and eating habits; in addition, it will monitor the activities through noninvasive means, evaluate them using open-source software, and follow up through blockchain messages. Methods: A literature search was conducted on the use of blockchain technology in the field of PA and healthy eating. On the basis of the results of this search, it is possible to define an innovative platform for promoting and monitoring healthy habits through health-related challenges on a dApp. Contact with the user will be maintained through messages following a proposed model in the literature to improve adherence to the challenges. Results: The proposed strategy is based on a dApp that relies on blockchain technology. The challenges include PA and healthy eating habits based on the recommendations of the WHO and the Food and Agriculture Organization. The system is constituted of a blockchain network where challenge-related achievements are stored and verified using SCs. The user interacts with the system through a dApp that runs on their local device, monitors the challenge, and self-authenticates by providing their public and private keys. The SC verifies challenge fulfillment and generates messages, and the information stored in the network can be used to encourage competition among participants. The ultimate goal is to create a habit of healthy activities through rewards and peer competition. Conclusions: The use of blockchain technology has the potential to improve people’s quality of life through the development of relevant services. In this work, strategies using gamification and blockchain are proposed for monitoring healthy activities, with a focus on transparency and reward allocation. The results are promising, but compliance with the General Data Protection Regulation is still a concern. Personal data are stored on personal devices, whereas challenge data are recorded on the blockchain.

BACKGROUND Low adherence to healthy habits, which is associated with a higher risk of disease and death, among citizens of Organization for Economic Co-operation and Development countries is a serious concern. The World Health Organization (WHO) and the physical activity (PA) guidelines for Americans provide recommendations on PA and healthy diets. To promote these habits, we suggest using a blockchain-based platform, using the PA Messaging Framework to deliver messages and rewards to users. Blockchain is a decentralized secure platform for data management, which can be used for value-added controls and services such as smart contracts (SCs), oracles, and decentralized applications (dApps). Of note, there is a substantial penetration of blockchain technologies in the field of PA, but there is a need for more implementations of dApps to take advantage of features such as nonfungible tokens. OBJECTIVE This study aimed to create a comprehensive platform for promoting healthy habits, using scientific evidence and blockchain technology. The platform will use gamification to encourage healthy PA and eating habits; in addition, it will monitor the activities through noninvasive means, evaluate them using open-source software, and follow up through blockchain messages. METHODS A literature search was conducted on the use of blockchain technology in the field of PA and healthy eating. On the basis of the results of this search, it is possible to define an innovative platform for promoting and monitoring healthy habits through health-related challenges on a dApp. Contact with the user will be maintained through messages following a proposed model in the literature to improve adherence to the challenges. RESULTS The proposed strategy is based on a dApp that relies on blockchain technology. The challenges include PA and healthy eating habits based on the recommendations of the WHO and the Food and Agriculture Organization. The system is constituted of a blockchain network where challenge-related achievements are stored and verified using SCs. The user interacts with the system through a dApp that runs on their local device, monitors the challenge, and self-authenticates by providing their public and private keys. The SC verifies challenge fulfillment and generates messages, and the information stored in the network can be used to encourage competition among participants. The ultimate goal is to create a habit of healthy activities through rewards and peer competition. CONCLUSIONS The use of blockchain technology has the potential to improve people’s quality of life through the development of relevant services. In this work, strategies using gamification and blockchain are proposed for monitoring healthy activities, with a focus on transparency and reward allocation. The results are promising, but compliance with the General Data Protection Regulation is still a concern. Personal data are stored on personal devices, whereas challenge data are recorded on the blockchain.

Blockchain technology provides a distributed support for information storage and traceability. Recently, it has been booming in a wide variety of domains: finance, food, energy, and health. In the field of physical activity, physical exercise, sport, and active ageing, this technology could also originate some interesting services introducing support for reliable repository of results, for gamification, or for secure data interchange. This systematic review explores the use of blockchain in this context. The objective is to determine to which extent this technology has fulfilled the potential of blockchain to bring these new added-value services. The authors explored 5 repositories in search of papers describing solutions applied to the above-mentioned frame. 17 papers were selected for full-text analysis, and they displayed diverse applications of blockchain, such as Fitness and healthcare, Sport, and Active ageing. A detailed analysis shows that the solutions found do not leverage all the possibilities of blockchain technology. Most of the solutions analyzed use blockchain for managing, sharing, and controlling access to data and do not exploit the possibilities of Smart Contracts or oracles. Additionally, the advantages of the blockchain model have not been fully exploited to engage users using approaches such as gamification.

Hand washing is the simplest and most effective gesture, when correctly performed, for the prevention of many infections. For this reason, the World Health Organization (WHO) has defined a washing procedure that guarantees effective and safe cleaning. This organization recommends that States promote this activity and monitor it continuously. Based on this fact, this article presents a work oriented to study the feasibility of identifying the moments in which a person carried out a hand washing, determining its beginning and duration, as well as if these washings were compliant with the WHO guidelines. The identification of washing moments is made through the analysis, by means of Machine Learning techniques, of the data that can be collected from the inertial sensors of the smartwatch the person is wearing. This study was carried out with the participation of 15 volunteers. Data was not only collected in controlled settings but, also, more than 600 hours of sensor measurements come from free-live conditions. The results of the study showed that it is feasible to build a solid solution based on the use of low cost wearables for the identification of washing moments. The solution is very effective (with F1 over 95%) with user-dependent models. Also, with user-independent models, the identification of WHO washings is also very effective (with F1 above 85%), but more limited in the detection of free washings (F1 around 55%).