Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Simulazione numerica di fenomeni aeroelastici con applicazione alle strutture civili

Il presente lavoro tratta lo studio dei fenomeni aeroelastici di interazione fra fluido e struttura, con il fine di provare a simularli mediante l’ausilio di un codice agli elementi finiti. Nel primo capitolo sono fornite alcune nozioni di fluidodinamica, in modo da rendere chiari i passaggi teorici fondamentali che portano alle equazioni di Navier-Stokes governanti il moto dei fluidi viscosi. Inoltre è illustrato il fenomeno della formazione di vortici a valle dei corpi tozzi dovuto alla separazione dello strato limite laminare, con descrizione anche di alcuni risultati ottenuti dalle simulazioni numeriche. Nel secondo capitolo vengono presi in rassegna i principali fenomeni di interazione fra fluido e struttura, cercando di metterne in luce le fondamenta della trattazione analitica e le ipotesi sotto le quali tale trattazione è valida. Chiaramente si tratta solo di una panoramica che non entra in merito degli sviluppi della ricerca più recente ma fornisce le basi per affrontare i vari problemi di instabilità strutturale dovuti a un particolare fenomeno di interazione con il vento. Il terzo capitolo contiene una trattazione più approfondita del fenomeno di instabilità per flutter. Tra tutti i fenomeni di instabilità aeroelastica delle strutture il flutter risulta il più temibile, soprattutto per i ponti di grande luce. Per questo si è ritenuto opportuno dedicargli un capitolo, in modo da illustrare i vari procedimenti con cui si riesce a determinare analiticamente la velocità critica di flutter di un impalcato da ponte, a partire dalle funzioni sperimentali denominate derivate di flutter. Al termine del capitolo è illustrato il procedimento con cui si ricavano sperimentalmente le derivate di flutter di un impalcato da ponte. Nel quarto capitolo è presentato l’esempio di studio dell’impalcato del ponte Tsing Ma ad Hong Kong. Sono riportati i risultati analitici dei calcoli della velocità di flutter e di divergenza torsionale dell’impalcato e i risultati delle simulazioni numeriche effettuate per stimare i coefficienti aerodinamici statici e il comportamento dinamico della struttura soggetta all’azione del vento. Considerazioni e commenti sui risultati ottenuti e sui metodi di modellazione numerica adottati completano l’elaborato.

Body ares networks for human motor assessment

Healthcare, Human Computer Interfaces (HCI), Security and Biometry are the most promising application scenario directly involved in the Body Area Networks (BANs) evolution. Both wearable devices and sensors directly integrated in garments envision a word in which each of us is supervised by an invisible assistant monitoring our health and daily-life activities. New opportunities are enabled because improvements in sensors miniaturization and transmission efficiency of the wireless protocols, that achieved the integration of high computational power aboard independent, energy-autonomous, small form factor devices. Application’s purposes are various: (I) data collection to achieve off-line knowledge discovery; (II) user notification of his/her activities or in case a danger occurs; (III) biofeedback rehabilitation; (IV) remote alarm activation in case the subject need assistance; (V) introduction of a more natural interaction with the surrounding computerized environment; (VI) users identification by physiological or behavioral characteristics. Telemedicine and mHealth [1] are two of the leading concepts directly related to healthcare. The capability to borne unobtrusiveness objects supports users’ autonomy. A new sense of freedom is shown to the user, not only supported by a psychological help but a real safety improvement. Furthermore, medical community aims the introduction of new devices to innovate patient treatments. In particular, the extension of the ambulatory analysis in the real life scenario by proving continuous acquisition. The wide diffusion of emerging wellness portable equipment extended the usability of wearable devices also for fitness and training by monitoring user performance on the working task. The learning of the right execution techniques related to work, sport, music can be supported by an electronic trainer furnishing the adequate aid. HCIs made real the concept of Ubiquitous, Pervasive Computing and Calm Technology introduced in the 1988 by Marc Weiser and John Seeley Brown. They promotes the creation of pervasive environments, enhancing the human experience. Context aware, adaptive and proactive environments serve and help people by becoming sensitive and reactive to their presence, since electronics is ubiquitous and deployed everywhere. In this thesis we pay attention to the integration of all the aspects involved in a BAN development. Starting from the choice of sensors we design the node, configure the radio network, implement real-time data analysis and provide a feedback to the user. We present algorithms to be implemented in wearable assistant for posture and gait analysis and to provide assistance on different walking conditions, preventing falls. Our aim, expressed by the idea to contribute at the development of a non proprietary solutions, driven us to integrate commercial and standard solutions in our devices. We use sensors available on the market and avoided to design specialized sensors in ASIC technologies. We employ standard radio protocol and open source projects when it was achieved. The specific contributions of the PhD research activities are presented and discussed in the following. • We have designed and build several wireless sensor node providing both sensing and actuator capability making the focus on the flexibility, small form factor and low power consumption. The key idea was to develop a simple and general purpose architecture for rapid analysis, prototyping and deployment of BAN solutions. Two different sensing units are integrated: kinematic (3D accelerometer and 3D gyroscopes) and kinetic (foot-floor contact pressure forces). Two kind of feedbacks were implemented: audio and vibrotactile. • Since the system built is a suitable platform for testing and measuring the features and the constraints of a sensor network (radio communication, network protocols, power consumption and autonomy), we made a comparison between Bluetooth and ZigBee performance in terms of throughput and energy efficiency. Test in the field evaluate the usability in the fall detection scenario. • To prove the flexibility of the architecture designed, we have implemented a wearable system for human posture rehabilitation. The application was developed in conjunction with biomedical engineers who provided the audio-algorithms to furnish a biofeedback to the user about his/her stability. • We explored off-line gait analysis of collected data, developing an algorithm to detect foot inclination in the sagittal plane, during walk. • In collaboration with the Wearable Lab – ETH, Zurich, we developed an algorithm to monitor the user during several walking condition where the user carry a load. The remainder of the thesis is organized as follows. Chapter I gives an overview about Body Area Networks (BANs), illustrating the relevant features of this technology and the key challenges still open. It concludes with a short list of the real solutions and prototypes proposed by academic research and manufacturers. The domain of the posture and gait analysis, the methodologies, and the technologies used to provide real-time feedback on detected events, are illustrated in Chapter II. The Chapter III and IV, respectively, shown BANs developed with the purpose to detect fall and monitor the gait taking advantage by two inertial measurement unit and baropodometric insoles. Chapter V reports an audio-biofeedback system to improve balance on the information provided by the use centre of mass. A walking assistant based on the KNN classifier to detect walking alteration on load carriage, is described in Chapter VI.

Implementazione di una rete di sensori per il controllo di gas inquinanti nell'ambiente

Negli ultimi anni i progressi tecnologici in termini di miniaturizzazione elettronica, hanno permesso la realizzazione di componenti hardware ed in particolare di microprocessori e sensori dalle dimensioni ridottissime. Questo ha favorito la recente diffusione di reti di sensori wireless (Wireless Sensor Network) basate su sistemi embedded più o meno complessi ed applicate a settori di mercato che vanno dalla domotica alle applicazioni industriali, fino al monitoraggio dei pazienti. Lo scopo di questa tesi, svolta in collaborazione con la società Rinnova di Forlì, consiste nell’implementazione di un dimostratore che mostri la reale capacità di realizzare una rete WS che si appoggia su di un sistema embedded commerciale ed ampiamente diffuso come la piattaforma Arduino ed in grado di rilevare il livello di ammoniaca presente negli allevamenti di pollame. Tale gas infatti, se presente in quantità notevole, provoca una dannosa alterazione comportamentale dei polli e risulta quindi un parametro molto importante da monitorare. Oltre al sensore di ammoniaca, misurazione principale richiesta dal progetto, ne sono stati aggiunti uno per la temperatura ed uno per l’umidità. L’architettura finale implementata è quella tipica di una rete a stella, in cui il master centrale colleziona a polling i dati provenienti dai sensori collegati agli slave e li invia ad un server web, rendendoli accessibili mediante la rete Internet. L’utente finale può così accedere alla pagina web da un qualunque PC dotato di connessione Internet, monitorare i dati dei sensori e soprattutto verificare quando il livello di ammoniaca supera la soglia di attenzione, potendo così intervenire immediatamente nell’allevamento per effettuare le dovute operazioni di pulizia.

Middleware per Internet of Things: Java Embedded come caso di studio

Grazie al progresso dell'elettronica, ai giorni nostri, è possibile costruire dispositivi elettronici molto piccoli, che col passare del tempo lo sono sempre più. Questo ci permette di poter imboccare nuove strade nel mondo dell'informatica, sfruttando proprio questo fatto. Le dimensioni ridotte dei dispositivi in commercio, come sensori, attuatori, tag e tanto altro, sono particolarmente adatte a nuovi scenari applicativi. Internet of Things è una visione in cui Internet viene esteso alle cose. Facendo largo uso di dispositivi come sensori e tag è possibile realizzare sistemi intelligenti che possono avere riscontri positivi nella vita di tutti i giorni. Tracciare la posizione degli oggetti, monitorare pazienti da remoto, rilevare dati sull'ambiente per realizzare sistemi automatici (ad esempio regolare automaticamente la luce o la temperatura di una stanza) sono solo alcuni esempi. Internet of Things è la naturale evoluzione di Internet, ed è destinato a cambiare radicalmente la nostra vita futura, poichè la tecnologia sarà sempre più parte integrante della nostra vita, aumentando sempre più il nostro benessere e riducendo sempre più il numero delle azioni quotidiane da compiere. Sempre più sono middleware, le piattaforme e i sistemi operativi che nascono per cercare di eliminare o ridurre le problematiche relative allo sviluppo di sistemi di questo genere, e lo scopo di questa tesi è proprio sottolinearne l'importanza e di analizzare gli aspetti che questi middleware devono affrontare. La tesi è strutturata in questo modo: nel capitolo uno verrà fatta una introduzione a Internet of Things, analizzando alcuni degli innumerevoli scenari applicativi che ne derivano, insieme però alle inevitabili problematiche di tipo tecnologico e sociale. Nel secondo capitolo verranno illustrate le tecnologie abilitanti di Internet of Things, grazie alle quali è possibile realizzare sistemi intelligenti. Nel terzo capitolo verranno analizzati gli aspetti relativi ai middleware, sottolineandone l'importanza e prestando attenzione alle funzioni che devono svolgere, il tutto riportando anche degli esempi di middleware esistenti. Nel quarto capitolo verrà approfondito il middleware Java Embedded di Oracle.

Progettazione, caratterizzazione e calibrazione di un sensore di tensione contactless per smart metering

Progettazione di un sistema di misura contactless per la tensione, da integrare in un nodo sensore di una Wireless Sensor Network per Smart Metering Distribuito

Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

Method of collaborative detection of autonomous transport vehicles based on laser rangefinder data

To master changing performance demands, autonomous transport vehicles are deployed to make inhouse material flow applications more flexible. The socalled cellular transport system consists of a multitude of small scale transport vehicles which shall be able to form a swarm. Therefore the vehicles need to detect each other, exchange information amongst each other and sense their environment. By provision of peripherally acquired information of other transport entities, more convenient decisions can be made in terms of navigation and collision avoidance. This paper is a contribution to collective utilization of sensor data in the swarm of cellular transport vehicles.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

Linked services for M2M communication with Enterprise IT systems

Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.

A Link Quality and Geographical-aware Routing Protocol for Video Transmission in Mobile IoT

Wireless mobile sensor networks are enlarging the Internet of Things (IoT) portfolio with a huge number of multimedia services for smart cities. Safety and environmental monitoring multimedia applications will be part of the Smart IoT systems, which aim to reduce emergency response time, while also predicting hazardous events. In these mobile and dynamic (possible disaster) scenarios, opportunistic routing allows routing decisions in a completely distributed manner, by using a hop- by-hop route decision based on protocol-specific characteristics, and a predefined end-to-end path is not a reliable solution. This enables the transmission of video flows of a monitored area/object with Quality of Experience (QoE) support to users, headquarters or IoT platforms. However, existing approaches rely on a single metric to make the candidate selection rule, including link quality or geographic information, which causes a high packet loss rate, and reduces the video perception from the human standpoint. This article proposes a cross-layer Link quality and Geographical-aware Opportunistic routing protocol (LinGO), which is designed for video dissemination in mobile multimedia IoT environments. LinGO improves routing decisions using multiple metrics, including link quality, geographic loca- tion, and energy. The simulation results show the benefits of LinGO compared with well-known routing solutions for video transmission with QoE support in mobile scenarios.

A real-time video quality estimator for emerging wireless multimedia systems

Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.