Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Development and optimization of graphic user interfaces (GUIs) for infrared spectrometers at the Telescopio Nazionale Galileo

This Phd thesis was entirely developed at the Telescopio Nazionale Galileo (TNG, Roque de los Muchachos, La Palma Canary Islands) with the aim of designing, developing and implementing a new Graphical User Interface (GUI) for the Near Infrared Camera Spectrometer (NICS) installed on the Nasmyth A of the telescope. The idea of a new GUI for NICS has risen for optimizing the astronomers work through a set of powerful tools not present in the existing GUI, such as the possibility to move automatically, an object on the slit or do a very preliminary images analysis and spectra extraction. The new GUI also provides a wide and versatile image display, an automatic procedure to find out the astronomical objects and a facility for the automatic image crosstalk correction. In order to test the overall correct functioning of the new GUI for NICS, and providing some information on the atmospheric extinction at the TNG site, two telluric standard stars have been spectroscopically observed within some engineering time, namely Hip031303 and Hip031567. The used NICS set-up is as follows: Large Field (0.25'' /pixel) mode, 0.5'' slit and spectral dispersion through the AMICI prism (R~100), and the higher resolution (R~1000) JH and HK grisms.

Advanced SPM studies on the growth of ultrathin films of organic semiconductors at metal and dielectric interfaces

Many studies on the morphology, molecular orientation, device performance, substrate nature and growth parameter dependence have been carried out since the proposal of Sexithiophene (6T) for organic electronics [ ] However, these studies were mostly performed on films thicker than 20nm and without specifically addressing the relationship between morphology and molecular orientation within the nano and micro structures of ultrathin films of 0-3 monolayers. In 2004, the observation that in OFETs only the first few monolayers at the interface in contact with the gate insulator contribute to the charge transport [ ], underlined the importance to study submonolayer films and their evolution up to a few monolayers of thickness with appropriate experimental techniques. We present here a detailed Non-contact Atomic Force Microscopy and Scanning Tunneling Microscopy study on various substrates aiming at the investigation of growth mechanisms. Most reported similar studies are performed on ideal metals in UHV. However it is important to investigate the details of organic film growth on less ideal and even technological surfaces and device testpatterns. The present work addresses the growth of ultra thin organic films in-situ and quasi real-time by NC-AFM. An organic effusion cell is installed to evaporate the organic material directly onto the SPM sample scanning stage.

Advanced CMOS Interfaces for Bio-Nanosensors

The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.

Poverty and Mental Health. Tangible and Intangible Aspects of Microcredit

Microcredit, a small lending system, invests on an individual's creativity by stimulating the development of their own potential. This process leads to the attainment of various objectives which in turn allow individuals to develop their skill awareness. Consequently, this process also increases an individual’s self-esteem and self-confidence. These factors play an important role in the aetiology of a number of mental disorders. Namely, those characterized by a series of psychological conditions which impede the full development of a person’s personal, relational and social sphere. Furthermore, since Microcredit is thought to produce tangible goods, such as income, and intangible goods, such as self-esteem and mutual trust, it could also represent an innovative socio-economic tool. We therefore also hypothesize that, Microcredit would be valuable in maximizing abilities/skills in those subjects who are financially excluded and rarely perceived as a ‘resource’ for the Community The longitudinal study set the impact of the Grameen Bank microcredit program on new borrowers women from Noakhali District at the south Bangladesh. The impact evaluation assessment has been structured to detect individual, family and social changes. Manova Analysis allowed distinguishing from women with positive or negative outcomes related to the loan performance. Data revealed consistent differences in terms of economical outcomes and psychological well being amongst the groups of subject analyzed. The data gathered in relation to the changes arisen in the individuals should be looked into through future, continuous and systematic, monitoring.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

Innovative Man Machine Interfaces In Aeronautics

The research activity focused on the study, design and evaluation of innovative human-machine interfaces based on virtual three-dimensional environments. It is based on the brain electrical activities recorded in real time through the electrical impulses emitted by the brain waves of the user. The achieved target is to identify and sort in real time the different brain states and adapt the interface and/or stimuli to the corresponding emotional state of the user. The setup of an experimental facility based on an innovative experimental methodology for “man in the loop" simulation was established. It allowed involving during pilot training in virtually simulated flights, both pilot and flight examiner, in order to compare the subjective evaluations of this latter to the objective measurements of the brain activity of the pilot. This was done recording all the relevant information versus a time-line. Different combinations of emotional intensities obtained, led to an evaluation of the current situational awareness of the user. These results have a great implication in the current training methodology of the pilots, and its use could be extended as a tool that can improve the evaluation of a pilot/crew performance in interacting with the aircraft when performing tasks and procedures, especially in critical situations. This research also resulted in the design of an interface that adapts the control of the machine to the situation awareness of the user. The new concept worked on, aimed at improving the efficiency between a user and the interface, and gaining capacity by reducing the user’s workload and hence improving the system overall safety. This innovative research combining emotions measured through electroencephalography resulted in a human-machine interface that would have three aeronautical related applications: • An evaluation tool during the pilot training; • An input for cockpit environment; • An adaptation tool of the cockpit automation.

Atomistic simulations of liquid crystals in the bulk and at their interfaces

In this thesis, we have dealt with several problems concerning liquid crystals (LC) phases, either in the bulk or at their interfaces, by the use of atomistic molecular dynamics (MD) simulations. We first focused our attention on simulating and characterizing the bulk smectic phase of 4-n-octyl-4'-cyanobiphenyl (8CB), allowing us to investigate the antiparallel molecular arrangement typical of SmAd smectic phases. A second topic of study was the characterization of the 8CB interface with vacuum by simulating freely suspended thin films, which allowed us to determine the influence of the interface on the orientational and positional order. Then we investigated the LC-water and LC-electrolyte water solution interface. This interface has recently found application in the development of sensors for several compounds, including biological molecules, and here we tried to understand the re-orientation mechanism of LC molecules at the interface which is behind the functioning of these sensors. The characterization of this peculiar interface has incidentally led us to develop a polarizable force field for the pentyl-cyanobiphenyl mesogen, whose process of parametrization and validation is reported here in detail. We have shown that this force field is a significant improvement over its previous, static charge non polarizable version in terms of density, orientational order parameter and translational diffusion.