Indoor Navigation Ontology for Smartphone Semi- Automatic Self-Calibration Scenario

The indoor navigation within public environments and location-based service development are very interesting and promising tasks. This paper describes an ontology-based technique for human movement recognition using the hybrid indoor localization technique based on received signal strength multilateration and pedestrian dead reckoning which relies on internal smartphone sensors. This technique takes into account the anchor node proximity zones and using internal sensors performs the semi-automatic online calibration procedure of log- distance path loss propagation model in accordance with a certain semi-automatic self-calibration scenario. The usage of indoor navigation ontology allows to decrease the influence of radio signal obstructions induced by user's body and moving people

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

Context Awareness for Navigation Applications

This thesis examines the topic of context awareness for navigation applications and asks the question, “What are the benefits and constraints of introducing context awareness in navigation?” Context awareness can be defined as a computer’s ability to understand the situation or context in which it is operating. In particular, we are interested in how context awareness can be used to understand the navigation needs of people using mobile computers, such as smartphones, but context awareness can also benefit other types of navigation users, such as maritime navigators. There are countless other potential applications of context awareness, but this thesis focuses on applications related to navigation. For example, if a smartphone-based navigation system can understand when a user is walking, driving a car, or riding a train, then it can adapt its navigation algorithms to improve positioning performance. We argue that the primary set of tools available for generating context awareness is machine learning. Machine learning is, in fact, a collection of many different algorithms and techniques for developing “computer systems that automatically improve their performance through experience” [1]. This thesis examines systematically the ability of existing algorithms from machine learning to endow computing systems with context awareness. Specifically, we apply machine learning techniques to tackle three different tasks related to context awareness and having applications in the field of navigation: (1) to recognize the activity of a smartphone user in an indoor office environment, (2) to recognize the mode of motion that a smartphone user is undergoing outdoors, and (3) to determine the optimal path of a ship traveling through ice-covered waters. The diversity of these tasks was chosen intentionally to demonstrate the breadth of problems encompassed by the topic of context awareness. During the course of studying context awareness, we adopted two conceptual “frameworks,” which we find useful for the purpose of solidifying the abstract concepts of context and context awareness. The first such framework is based strongly on the writings of a rhetorician from Hellenistic Greece, Hermagoras of Temnos, who defined seven elements of “circumstance”. We adopt these seven elements to describe contextual information. The second framework, which we dub the “context pyramid” describes the processing of raw sensor data into contextual information in terms of six different levels. At the top of the pyramid is “rich context”, where the information is expressed in prose, and the goal for the computer is to mimic the way that a human would describe a situation. We are still a long way off from computers being able to match a human’s ability to understand and describe context, but this thesis improves the state-of-the-art in context awareness for navigation applications. For some particular tasks, machine learning has succeeded in outperforming humans, and in the future there are likely to be tasks in navigation where computers outperform humans. One example might be the route optimization task described above. This is an example of a task where many different types of information must be fused in non-obvious ways, and it may be that computer algorithms can find better routes through ice-covered waters than even well-trained human navigators. This thesis provides only preliminary evidence of this possibility, and future work is needed to further develop the techniques outlined here. The same can be said of the other two navigation-related tasks examined in this thesis

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

Senseable Spaces: from a theoretical perspective to the application in augmented environments

openGrazie all’ enorme diffusione di dispositivi senzienti nella vita di tutti i giorni, nell’ ultimo decennio abbiamo assistito ad un cambio definitivo nel modo in cui gli utenti interagiscono con lo spazio circostante. Viene coniato il termine Spazio Sensibile, per descrivere quegli spazi in grado di fornire servizi contestuali agli utenti, misurando e analizzando le dinamiche che in esso avvengono, e di reagire conseguentemente a questo continuo flusso di dati bidirezionale. La ricerca è stata condotta abbracciando diversi domini di applicazione, le cui singole esigenze hanno reso necessario testare il concetto di Spazi Sensibili in diverse declinazioni, mantenendo al centro della ricerca l’utente, con la duplice accezione di end-user e manager. Molteplici sono i contributi rispetto allo stato dell’ arte. Il concetto di Spazio Sensibile è stato calato nel settore dei Beni Culturali, degli Spazi Pubblici, delle Geosciences e del Retail. I casi studio nei musei e nella archeologia dimostrano come l’ utilizzo della Realtà Aumentata possa essere sfruttata di fronte a un dipinto o in outdoor per la visualizzazione di modelli complessi, In ambito urbano, il monitoraggio di dati generati dagli utenti ha consentito di capire le dinamiche di un evento di massa, durante il quale le stesse persone fruivano di servizi contestuali. Una innovativa applicazione di Realtà Aumentata è stata come servizio per facilitare l’ ispezione di fasce tampone lungo i fiumi, standardizzando flussi di dati e modelli provenienti da un Sistema Informativo Territoriale. Infine, un robusto sistema di indoor localization è stato istallato in ambiente retail, per scopi classificazione dei percorsi e per determinare le potenzialità di un punto vendita. La tesi è inoltre una dimostrazione di come Space Sensing e Geomatica siano discipline complementari: la geomatica consente di acquisire e misurare dati geo spaziali e spazio temporali a diversa scala, lo Space Sensing utilizza questi dati per fornire servizi all’ utente precisi e contestuali.Given the tremendous growth of ubiquitous services in our daily lives, during the last few decades we have witnessed a definitive change in the way users' experience their surroundings. At the current state of art, devices are able to sense the environment and users’ location, enabling them to experience improved digital services, creating synergistic loop between the use of the technology, and the use of the space itself. We coined the term Senseable Space, to define the kinds of spaces able to provide users with contextual services, to measure and analyse their dynamics and to react accordingly, in a seamless exchange of information. Following the paradigm of Senseable Spaces as the main thread, we selected a set of experiences carried out in different fields; central to this investigation there is of course the user, placed in the dual roles of end-user and manager. The main contribution of this thesis lies in the definition of this new paradigm, realized in the following domains: Cultural Heritage, Public Open Spaces, Geosciences and Retail. For the Cultural Heritage panorama, different pilot projects have been constructed from creating museum based installations to developing mobile applications for archaeological settings. Dealing with urban areas, app-based services are designed to facilitate the route finding in a urban park and to provide contextual information in a city festival. We also outlined a novel application to facilitate the on-site inspection by risk managers thanks to the use of Augmented Reality services. Finally, a robust indoor localization system has been developed, designed to ease customer profiling in the retail sector. The thesis also demonstrates how Space Sensing and Geomatics are complementary to one another, given the assumption that the branches of Geomatics cover all the different scales of data collection, whilst Space Sensing gives one the possibility to provide the services at the correct location, at the correct time.INGEGNERIA DELL'INFORMAZIONEembargoed_20181001Pierdicca, RobertoPierdicca, Robert