Maurizio Bocca, Ph.D.
WHAT DO I WORK ON?
HW: wireless systems and technologies localizing people and devices indoors
SW: new features enhancing Alexa's ambient intelligence in current and next-generation devices
PROFESSIONAL EXPERIENCE
Q1/2020-Current: Amazon Lab126
Sunnyvale, CA, USA
2019-Q1/2020 - Senior Manager, Wireless Connectivity
Byton (Santa Clara, CA, USA)
2018 - Lead Research Scientist and VP of Product Development
Xandem Technology (Salt Lake City, UT, USA)
2014 - Post Doctoral Fellow - Intelligent Embedded Systems Lab (Prof. Cesare Alippi)
Dipartimento di Elettronica, Informazione e Bioingegneria - Politecnico di Milano (Milan, Italy)
2015-2017 - Senior Research Scientist - Wireless Connectivity Group
Bosch Research and Technology Center (Palo Alto, CA, USA)
2012-2013 - Post Doctoral Fellow - Sensing and Processing Across Networks Lab (Prof. Neal Patwari)
Eletrical and Computer Engineering Department - University of Utah (Salt Lake City, Utah, USA)
2007-2011 - Ph.D. Candidate - Control Engineering Lab (Prof. Heikki Koivo)
Aalto University School of Electrical Engineering (Espoo, Finland)
2003-2006 - M.Sc. - Computer Science Engineering
Dipartimento di Elettronica, Informazione e Bioingegneria - Politecnico di Milano (Milan, Italy)
2003-2004 - Exchange Student (Erasmus Program)
Electrical Engineering Department - University of Oulu (Oulu, Finland)
2000-2003 - B.Sc. - Computer Science Engineering
Dipartimento di Elettronica, Informazione e Bioingegneria - Politecnico di Milano (Milan, Italy)
RESEARCH ACTIVITY
RF Sensor Networks for Passive (Device-Free) Context Awareness and Localization
Radio frequency (RF) sensor networks are systems composed of low-power radio transceivers that measure the changes in the received signal strength (RSS) on the links of the network caused by people found in the monitored area to enable context awareness and localization in indoor and outdoor environments. In these systems, people to be monitored are not requested to carry or wear any radio device, sensor or tag. The localization process (also known as radio tomographic imaging) is based on models for the change in RSS introduced by the presence of a person on or near the link line, i.e., the imaginary line connecting transmitter and receiver. My research has focused on making these systems more accurate and reliable, and capable of providing awareness (location and activity recognition) of every person inside a building or large outdoor area.
Wireless Sensor Networks for Intelligent Structural Health Monitoring
Structural health monitoring (SHM) aims at providing an accurate diagnosis of the structural condition of civil infrastructures during their life span using data coming from sensors deployed on them. Wireless sensor networks represent a flexible and suitable monitoring technology to collect reliable information about the structure’s condition, replacing visual inspections, and reducing installation and maintenance time and costs. My research has focused on the development of intelligent protocols (for time synchronization, routing, and data collection) and distributed data processing methods enabling the energy-efficient, precise, and reliable identification of the modal properties (natural frequencies of vibration, damping ratios, and mode shapes) of the monitored structure, and the timely and accurate detection and localization of structural damages.
Low-Power Wireless Embedded Systems
Low-power wireless embedded systems are composed of spatially distributed, battery-operated devices using multiple sensors to monitor different environmental and process parameters. They communicate wirelessly to exchange information and coordinate their operations, in order for the system to achieve its tasks. My research focuses on designing intelligent networking protocols and embedded algorithms making these systems fulfill the different requirements (e.g., extended battery life time, data transfer reliability, low latency) of various use cases in application domains such as industry4.0, automotive, and smart homes/buildings.
SELECTED PUBLICATIONS
Full list available here
M. Bocca, O. Kaltiokallio, and N. Patwari. "Radio Tomographic Imaging for Ambient Assisted Living", in S. Chessa and S. Knauth (Eds.): EvAAL 2012, Communications in Computer and Information Science (CCIS) 362, pp. 108-130, Springer (2013)
Book Chapters
International Journals
C. Alippi, M. Bocca, G. Boracchi, N. Patwari, and M. Roveri. "RTI Goes Wild: Radio Tomographic Imaging for Outdoor People Detection and Localization", IEEE Transactions on Mobile Computing, Oct. 2016, vol. 15, no. 10, pp. 2585-2598
M. Bocca, O. Kaltiokallio, N. Patwari, and S. Venkatasubramanian. "Multiple Target Tracking with RF Sensor Networks", IEEE Transactions on Mobile Computing, August 2014, vol. 13, no. 8, pp. 1787-1800
O. Kaltiokallio, M. Bocca, N. Patwari. "A Fade Level-based Spatial Model for Radio Tomographic Imaging", IEEE Transactions on Mobile Computing, June 2014, vol. 13, no. 6, pp. 1159-1172
M. Bocca, A. Mahmood, L.M. Eriksson, J. Kullaa, and R. Jäntti. ”A Synchronized Wireless Sensor Network for Experimental Modal Analysis in Structural Health Monitoring”, Computer-Aided Civil and Infrastructure Engineering, Vol. 26, No. 7, 2011
International Conferences
M. Bocca, A. Luong, N. Patwari, and T. Schmid. "Dial It In: Rotating RF Sensors to Enhance Radio Tomography", IEEE SECON 2014, June 30 - July 3, 2014, Singapore (acceptance rate: 19%)
O. Kaltiokallio, M. Bocca, and N. Patwari. "Follow @grandma: Long-Term Device-Free Localization for Residential Monitoring", IEEE SenseApp 2012, October 22, 2012, Clearwater, FL, USA - BEST PAPER AWARD (acceptance rate: 20%) - VIDEO
O. Kaltiokallio, M. Bocca, and N. Patwari. "Enhancing the Accuracy of Radio Tomographic Imaging Using Channel Diversity", IEEE MASS 2012, October 8-10, 2012, Las Vegas, NV, USA (acceptance rate: 30%) - VIDEO
N. Patwari, L. Brewer, Q. Tate, O. Kaltiokallio, and M. Bocca. "Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home", IEEE Journal of Selected Topics in Signal Processing, Feb. 2014, vol. 8, no. 1, pp. 30-42
M. Bocca, J. Toivola, L.M. Eriksson, J. Hollmen, and H. Koivo. “Structural Health Monitoring in Wireless Sensor Networks by the Embedded Goertzel Algorithm”, ACM/IEEE ICCPS 2011, April 11-14, 2011, Chicago, IL, USA (acceptance rate: 27%)
M. Bocca, E.I. Cosar, L.M. Eriksson, and J. Salminen. “A Reconfigurable Wireless Sensor Network for Structural Health Monitoring”, SHMII-4 2009, July 22-24, 2009, Zurich, Switzerland
Ph.D. Dissertation
Maurizio Bocca, "Application-Driven Data Processing in Wireless Sensor Networks", Aalto University School of Electrical Engineering, Espoo, Finland, November 2011
Software&Data
Maurizio Bocca, "Application-Driven Data Processing in Wireless Sensor Networks", Aalto University School of Electrical Engineering, Espoo, Finland, November 2011
The material in this section is freely available.
However, if you use the material in your own work, please properly cite the papers indicated below.
multi-Spin Communication Protocol
multi-Spin is a multi-frequency, TDMA communication protocol specifically designed for RF sensor networks applications.
In multi-Spin, the nodes composing the system measure the received signal strength (RSS) of the links of the network by continuously exchanging packets. The protocol is:
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self-synchronizing: the nodes are able to synchronize their TX/RX schedules and synchronously switch on different frequency channels without requiring a command or coordination from a central unit;
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self-starting: as soon as two nodes are turned on, they start exchanging packets on the defined frequency channels;
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robust to packet drops and nodes failure.
SUPPORTED PLATFORMS: multi-Spin supports TI CC253x SoC (2.4 GHz, IEEE 802.15.4 compliant).
B. Mager, N. Patwari, and M. Bocca. "Fall Detection Using RF Sensor Networks", IEEE PIMRC 2013, Sept. 8-11, 2014, London, UK [Link to BBC World Service report] (acceptance rate: 19%)
O. Kaltiokallio, M. Bocca. "Real-Time Intrusion Detection and Tracking in Indoor Environment Through Distributed RSSI Processing", IEEE RTCSA 2011, August 28-31, 2011, Toyama, Japan
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source code (uploaded 01/30/2014)
You will also need to download and use the CC USB firmware library.
IAR EW8051 full version is needed for building the source code. Alternatively, you can compile the code with SDCC.
NEW! Open source Radio Tomography software toolchain for usage with the Texas Instruments CC2530 SoC.
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M. Bocca, O. Kaltiokallio, and N. Patwari. "Radio Tomographic Imaging for Ambient Assisted Living", in S. Chessa and S. Knauth (Eds.): EvAAL 2012, Communications in Computer and Information Science (CCIS) 362, pp. 108-130, Springer (2013)
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O. Kaltiokallio, M. Bocca, and N. Patwari. "Enhancing the Accuracy of Radio Tomographic Imaging Using Channel Diversity", IEEE MASS 2012, October 8-10, 2012, Las Vegas, NV, USA (acceptance rate: 30%)
Experimental Data
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M. Bocca, O. Kaltiokallio, N. Patwari, and S. Venkatasubramanian. "Multiple Target Tracking with RF Sensor Networks", IEEE Transactions on Mobile Computing, August 2014, vol. 13, no. 8, pp. 1787-1800
DOWNLOAD HERE (uploaded 01/20/2014)
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