XVIII BrainStorming day Catania - Istituto Nazionale di Geofisica e Vulcanologia, 05/06/2009

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1 XVIII BrainStorming day Catania - Istituto Nazionale di Geofisica e Vulcanologia, 05/06/2009 Dottorato di Ricerca in Ingegneria Elettronica, Automatica e delcontrollo di Sistemi Complessi XIV Ciclo Human oriented sensing systems and methodologies Salvatore La Malfa salvatore.lamalfa@diees.unict.it Coordinatore: Prof. Ing. Luigi Fortuna Tutor: Prof. Ing. Bruno Andò

2 PhD research activity outline Topic Sensors Methodologies Applications Sensors Design, realization and characterization Multi-sensor systems Distributed sensor networks Wireless sensor networks Autonomous sensor nodes Methodologies Stochastic resonance & Dithering Non-linear dynamics Multi-sensor data fusion Advanced algorithms for signal processing Human oriented sensing systems and methodologies Applications Environmental measurements (B-Field) AAL & Assistive technologies Energy Harvesting

3 RTD Fluxgate Magnetometers Operating principle Prototypes Characterization Perming effect RTD Fluxgate magnetometers Suitable for measuring static or quasi-static magnetic field intensities, in the range of nt at room temperature. Hall Effect Lower resolution (µt) Less expensive AMR/GMR Fluxgate Lower resolution (100 nt) Poor thermal stability Poor long term stability SQUID Higher costs Higher complexity Far greater resolution (pt) Resolution Why research on RTD Fluxgate? RTD Fluxgate is an alternative to the traditional 2 nd harmonic Fluxgate. The benefits are: Intrinsically digital form of the output signal (time domain readout) Reduced complexity in the conditioning and readout electronics that traduces in less noise and less power consumption Possible applications Magnetic Immunoassay [health-care] Natural hazards detection (Volcanic ash fall monitoring) [safety] Accurate monitoring of geomagnetic field

4 RTD Fluxgate Magnetometers Operating principle Prototypes Characterization Perming effect U Primary Coil Secondary coil Fluxgate RTD Time domain readout strategy dx τ dt 2 x 1 U ( x) = ln cosh[ c( x + H ( t) + 2 c x + H e( t) + H = x + tanh K x e H x )] U ( x, t) = x

5 Operating principle Operating principle Prototypes Characterization Perming effect Excitation waveform Fluxgate output Schmitt Trigger output Excitation waveform Fluxgate output Schmitt Trigger output

6 RTD Fluxgate prototypes PCB FR4 Prototype Operating principle Prototypes Characterization Perming effect microwire Prototype PCB FR4 RTD Fluxgate prototype Exploded structure view microwire RTD Fluxgate prototype Exploded structure view

7 Experimental setup Operating principle Prototypes Characterization Perming effect Functions Generator (Agilent 33120A) Tension/Current converter FluxGate Primary Coil A bias =? f bias =? offset =? waveform=? Tension Current FluxGate Secondary Coil GPIB Interface Instrumentation Amplifier (INA114) Schmitt s Trigger (T +,T - ) DAQmx NI 6221 Counter 32bit 80 MHz I dc =? DAQmx NI 6221 Analog Output

8 microwire characterization Operating principle Prototypes Characterization Perming effect

9 Perming effect in RTD FG Operating principle Prototypes Characterization Perming effect The perming effect can affect the output signal of the device (by an offset) after a magnetic shock. It is similar to hysteresis, but the applied field must be much higher than the full-scale range. All the sensors containing ferromagnetic material are susceptible to perming. The only solution is the periodic remagnetization of the core; in the case of fluxgate sensors, the re-magnetization is performed by forcing a current through the primary coil. Anyway, it must be considered that no significant perming is observed if the device is polarized by a high current value. AISEM 2009 ASSOCIAZIONE ITALIANA SENSORI E MICROSISTEMI XIV edition, Pavia (Italy), February 2009 PERMING EFFECT IN RESIDENCE TIMES DIFFERENCE FLUXGATE MAGNETOMETERS B. ANDO, S. BAGLIO, A. R. BULSARA, S. LA MALFA, C. TRIGONA

10 Perming effect Experimental procedure Operating principle Prototypes Characterization Perming effect

11 Perming effect Typical RTD trend Operating principle Prototypes Characterization Perming effect The figure below shows the typical trend in the RTD signal, before (red) and after (blue) the magnetic shock. The quite constant values for the red curve means that the reset procedure (step B) worked properly. Data refer to µwire prototype with a triangular driving current amplitude of 2 80 Hz

12 H:\Cartellona bordello\dottorato\pubblicazioni\2009\aisem 09 - FG effetto perming\extended Version\Perming microwirecolo.bmp Perming effect Experimental results Operating principle Prototypes Characterization Perming effect Experimental results show that the RTD consequent to the magnetic shock increases quite linearly with the field intensity. Moreover, this effect is less evident when excitation current amplitude increases. This is quite reasonable because an higher driving current produces a better saturation of the ferromagnetic core that hence becomes less susceptible to perming.

13 phd research activity outline Topic Sensors Methodologies Applications Sensors Design, realization and characterization Multi-sensor systems Distributed sensor networks Wireless sensor networks Autonomous sensor nodes Methodologies Stochastic resonance & Dithering Non-linear dynamics Multi-sensor data fusion Advanced algorithms for signal processing Human oriented sensing systems and methodologies Applications Environmental measurements (B-Field) AAL & Assistive technologies Energy Harvesting

14 Ambient Assisted Living AAL Ambient Assisted Living A WSN for orientation Quality of life Well-being Social interaction Safety For impaired and eldery people Main Research areas involved in AAL: New materials Microelectronics and microsystems Sensors & Embedded systems Power management and scavenging Communication technologies Software, web & network technologies Domotics and Smart houses Human-machine interaction Smart textiles Robotics Sociology Why research on AAL & Assistive technologies? Social problem Disabled people represent 50 milion persons in the EU (about 10% of the entire population) According to ISTAT ( ), 4.8% of the italian population (2,800,000 persons) suffer from some kind of disability, the 75% of which are over-65 years old. New innovative solutions can have a major effect on quality of life, thus easing the pressure of increasing costs in European social and care systems Attractive potential market

15 Ambient Assisted Living AAL Ambient Assisted Living A WSN for orientation Quality of life Well-being Social interaction Safety For impaired and eldery people Main Research areas involved in AAL: New materials Microelectronics and microsystems Sensors & Embedded systems Power management and scavenging Communication technologies Software, web & network technologies Domotics and Smart houses Human-machine interaction Smart textiles Robotics Sociology Why research on AAL & Assistive technologies? Foundings AAL Joint Program The AAL JP is a new joint research and development (R&D) funding activity implemented by actual 20 European Member Statesand 3 Associated Stateswith the financial support of the European Community. Call AAL Call AAL FP7-ICT Accessible and Assistive ICT, Embedded Accessibility of Future ICT.

16 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. S1 Embedded US transducer, with RF transceiver (battery-powered) S4 Analog signal conditioning circuitry Microcontroller (PIC18F2520) S1 S2 S3 S5 S6 Piezocerami c Capsule (RX) 40 khz USART RF 433 MHz Transceiver S8 S7 M

17 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. User (visually impaired) S1 S2 S3 S8 S4 S7 S5 S6 M Bluetoot h earphone Analog signal conditioning circuitry Piezocerami c Capsule (TX) 40 khz Compas s Microcontroller (PIC18F2520) USART RF 433 MHz Transceiver Accelerometer

18 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. M Master (sink) node. S1 S2 S3 S4 S5 S6 GUI for the system administrator (LabVIEW) Bluetoot h controller USART2 Microcontroller (PIC18F24J11) Algorithms trilateration routing object interacion odometry multi-sensor data fusion USART1 PC RF 433 MHz Transceiver S8 S7 M

19 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. M Transmits through the RF trainsceiver a start sequence. We can say that each network node, including the user module, will riceive the start signal at the same time. S1 8 Start their timers Generate a short ultrasonic wave S4 Receives and stop its timer S1 S2 S3 start stop start stop start t 3 t 2 t 1 stop stop start S8 S4 start stop C(t) A(t) t 8 t 4 stop stop stop start S7 start t 7 S5 t 5 t 6 start S6 M < 20 ms S3 S2 Receive and stop their timers S6 Receives and stop its timer M Queries each node for their elasped time (polling) and computes the distance between the user and each network node (time of flight). Finally, user module is queried too for retrieving data from the compass and the accelerometer. This raw data is then transferred to the PC running LabVIEW for further processing, through a USART connection.

20 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. Within the white area the user can be successfully localized thanks to the MTA. S4 In gray areas most of the US capsules won t recieve the acoustic wave. To ensure localization within shadow areas an alternative localization strategy, that does not relay on the ultrasonic wave, must be adopted. S1 S2 S3 S8 S7 S5 S6 M This can be achieved by the use of odometry starting from data retrieved from embedded compass (that give us user orientation) and accelerometer (that give us an idea about the number of user s steps). Moreover, when the user is inside white areas, the system can perform an automatic calibration of the odometric subsystem (i.e. determine the average measure of a step). When should I trust odometry? When trilateration?: Multisensor data fusion approach.

21 A WSN for orientation A WSN for orientation N = number of US sensor nodes M = number of users Static Map definition Complete map definition GUI Node Position array [Nx2] Position array [Mx2] Master Node Distance array [NxM] Multi Trilateration Algorithm Position array [Mx2] Accuracy indicators Multisensor data fusion Odometric array [2xM] Odometry Position array [Mx2] Calibration array [Mx2] After we gain a reliable and accurate estimation of user location within the environment, we can provide the impaired user with a useful kind of assistance, on the basis of his impairmenttypology and his skills. A general purpose assistance strategy could start from: obstacles avoidance, services notification, routing features through an auditory and/or haptic feedback Bluetoot h notification array [Mx1] Audio feedback subsystem with priority management User-Environment Interaction detection subsystem Routing algorithms User location within the environment & Map definition

22 A WSN for orientation A WSN for orientation A wireless sensor network for indoor user localization. Fully accomplished Design of the US sensor node Design of the user and master node Implementation and testing of the MTA Preliminary GUI for the system administrator Stand-alone odometric subsystem Audio feedback subsystem Partially accompished: Routing alghoritms Improved PCBs for the sensor nodes, user and master modules Set-up of wireless communication (CAN-BUS Xbee RF 433 MHz) Improved GUI for the system administrator To do: Integration between MTA and odometry Metrological characterization of the whole system Power budget minimization through firmware optimization Test with end-users

23 Pubblications and Courses Journals: 1)B. Andò, S. Baglio, A. Beninato, S. La Malfa, N. Pitrone, Advanced Educational Tools in Measurement and Sensors: from remote monitoring systems to magnetic fluids.,inter. Journal of Education and Information Technologies, Issue 1, Volume 3, 75-84, 2009 Conferences 2)B. Andò, A. Beninato,S. La Malfa, N. Pitrone, Didactic tool assisting visually impaired studentsduring laboratori sessions, the 7th WSEAS International Conference on Education and Educational Technology (EDU08), pp , )B. Andò, A. Ascia, S. Baglio, A. Beninato, S. La Malfa, N. Pitrone, Sensing a physical movement with a ferrofluidic device, the 4 th WSEAS International Conference on Remote Sensing (REMOTE08), pp , )B. Andò, S. Baglio, S. La Malfa, V. Marletta, N. Savalli, A Distributed Sensor Network Approachfor Orientation Tasks, IMTC )B. Andò, S. Baglio, A. R. Bulsara, S. La Malfa, C. Trigona, Experimental Investigations on the Spatial Resolution in RTD-Fluxgates, IMTC )B. Andò, S. Baglio, S. La Malfa, C. Trigona, Perming Effect in Residence Times Difference Fluxgate Magnetometers, AISEM )B. Andò, S. Baglio, S. La Malfa, V. Marletta, A Multisensor Guide System To Assist Visually Impaired In Unfamiliar Environments, ASME, IDETC/CIE )B. Andò, S. Baglio, S. La Malfa, N. Pitrone, A Remote Monitoring System to Improve Educational Activities of Visually Impaired Students, XIX IMEKO World Congress, 2009 Modelli Matematici I (prof. O. Muscato - cdl Matematica) Courses: Elaborazione Numerica dei Segnali (prof. A. La Corte cdl Ing. Microelettronica)