Transfer Learning in Human Activity Recognition: A Survey

Sensor-based human activity recognition (HAR) has been an active research area, owing to its applications in smart environments, assisted living, fitness, healthcare, etc. Recently, deep learning based end-to-end training has resulted in state-of-the-art performance in domains such as computer vision and natural language, where large amounts of annotated data are available. However, large quantities of annotated data are not available for sensor-based HAR. Moreover, the real-world settings on which the HAR is performed differ in terms of sensor modalities, classification tasks, and target users. To address this problem, transfer learning has been employed extensively. In this survey, we focus on these transfer learning methods in the application domains of smart home and wearables-based HAR. In particular, we provide a problem-solution perspective by categorizing and presenting the works in terms of their contributions and the challenges they address. We also present an updated view of the state-of-the-art for both application domains. Based on our analysis of 205 papers, we highlight the gaps in the literature and provide a roadmap for addressing them. This survey provides a reference to the HAR community, by summarizing the existing works and providing a promising research agenda.Comment: 40 pages, 5 figures, 7 table

Assessing Wind Impact on Semi-Autonomous Drone Landings for In-Contact Power Line Inspection

In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The performance of the system is evaluated for two landing strategies, variously controllers parameters and four level of wind intensities. The results show that a two-stage landing strategies offers higher probabilities of landing success and give insight regarding the best controller parameters and the maximum wind level for which the system is robust. Lastly, an experimental demonstration of the system landing autonomously on a power line is presented

Développement et évaluation d'une stratégie d'atterrissage pour drones semi-autonome sur lignes électriques dans différentes conditions de vent

Au cours des dernières années, le recours aux drones pour l’inspection des lignes électriques à haute tension s’est répandu en raison de leur efficacité, de leur rentabilité et de leur ca- pacité à atteindre des zones autrement inaccessibles. Cependant, faire atterrir en toute sécurité ces drones sur les lignes électriques, notamment dans des conditions venteuses, constitue un défi majeur. Cette recherche présente un modèle de contrôle semi-autonome pour permettre l’atterrissage sur une ligne électrique à l’aide de la plateforme NADILE (un drone conçu spécifiquement pour l’inspection des lignes électriques) et évalue le fonc- tionnement dans différentes conditions de vent. L’analyse de la probabilité de réussite de l’atterrissage en fonction de l’état initial du drone a été effectuée à l’aide de la méthode de Monte Carlo. Les performances du système ont été évaluées pour deux stratégies d’atter- rissage différentes, divers paramètres de contrôle, et quatre niveaux de vent. Les résultats ont montré qu’une stratégie d’atterrissage en deux étapes donne de meilleures chances de réussite de l’atterrissage et fournissent des indications précieuses sur les paramètres de contrôle optimaux et le niveau maximal de vent pour lequel le système est fiable. Une dé- monstration expérimentale de l’atterrissage autonome du système sur une ligne électrique a également été réalisée

2nd National Conference on Sensors

This book contains a selection of papers presented at the Second National Conference on Sensors held in Rome 19-21 February 2014. The conference highlighted state-of-the-art results from both theoretical and applied research in the field of sensors and related technologies. This book presents material in an interdisciplinary approach, covering many aspects of the disciplines related to sensors, including physics, chemistry, materials science, biology and applications. ·         Provides a selection of the best papers from the Second Italian National Conference on Sensors; ·         Covers a broad range of topics relating to sensors and microsystems, including physics, chemistry, materials science, biology and applications; ·         Offers interdisciplinary coverage, aimed at defining a common ground for sensors beyond the specific differences among the different particular implementation of sensors

Three different sensor methods for methanol and ethanol determination

This book contains a selection of papers presented at the Second National Conference on Sensors held in Rome 19-21 February 2014. The conference highlighted state-of-the-art results from both theoretical and applied research in the field of sensors and related technologies. This book presents material in an interdisciplinary approach, covering many aspects of the disciplines related to sensors, including physics, chemistry, materials science, biology and applications. · Provides a selection of the best papers from the Second Italian National Conference on Sensors; · Covers a broad range of topics relating to sensors and microsystems, including physics, chemistry, materials science, biology and applications; · Offers interdisciplinary coverage, aimed at defining a common ground for sensors beyond the specific differences among the different particular implementation of sensors