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Call for Papers
Special Issue on Physics-Driven Machine Learning for Computational Imaging
Recent years have witnessed a rapidly growing interest in next-generation imaging systems and their combination
with machine learning. While model-based imaging schemes that incorporate physics-based forward models, noise
models, and image priors laid the foundation in the emerging field of computational sensing and imaging, recent
advances in machine learning, from large-scale optimization to building deep neural networks, are increasingly
being applied in modern computational imaging. A wide range of machine learning techniques can be applied to
enhance the effectiveness and efficiency of computational imaging systems, thus redefining the state-of-the-art
computational imaging algorithms. On the other hand, different from image restoration problems, computational
imaging involves physics-based imaging processes, physics-based properties of underlying data (e.g., characterized
by partial differential equations or PDEs), and domain knowledge, which need to be exploited and combined with
various data-driven approaches to benefit applications from sensing to image reconstruction. There are compelling
challenges for such interdisciplinary research that remain to be addressed, ranging from learning theory to imaging
applications. This special issue invites tutorial on recent works on novel imaging pipelines such as smart imaging
system design, machine learning and related methods, and task and data-driven imaging system hardware and
algorithm design that are tightly combined with imaging physics. Besides, this special issue will promote recent
works on learning theory for computational imaging, including performance guarantees, convergence analysis,
learning model analysis, etc., which are critical for reliable and
interpretable computational imaging systems. Important Dates
White papers due: 1 December 2021
Topics of interest include but are not limited to:
Invitation notification: 1 January 2021
● Novel Learning-Driven Computational Imaging Systems
Fullmanuscripts due: 1 March 2022
● Learning-based Modeling and Algorithms for Imaging
Firstreview to authors: 1May2022
● Learning Theory for Computational Imaging
● Computational Imaging Applications Revision due: 1 July2022
● Ethics and Social Impacts of Learning for Computational Second review completed: 1 September, 2022
Imaging Final manuscriptdue: 1 October2022
Publication: 1 January 2023
White papers are required, and full articles will be invited
based on the review of white papers. The white paper format is up to 4 pages in length, including the proposed
article title, motivation and significance of the topic, an outline of the proposed paper, and representative references.
An author list with contact information and short bios should also be included. Submitted articles must be of
tutorial/overview/survey nature, in an accessible style to a broad audience, and have a significant relevance to the
scope of the Special Issue. Submissions should not have been published or be under review elsewhere, and should
be made online at https://mc.manuscriptcentral.com/sps-ieee. For submission guidelines, see the Information for
Authors at https://signalprocessingsociety.org/publications-resources/ ieee-signal-processing-magazine/information-
authors-spm.
Guest Editors
Prof. Jong Chul Ye (Lead GE),Korea Adv. Inst.of Science and Technology(KAIST), Korea, [email protected]
Prof.Bihan Wen, Nanyang Technological University, Singapore, [email protected]
Prof. Saiprasad Ravishankar,Michigan State University, USA, [email protected]
Prof. Raja Giryes, Tel Aviv University, Israel, [email protected]
Prof. Zhizhen Zhao, University of Illinois at Urbana-Champaign,mailto:[email protected]
Digital Object Identifier 10.1109/MSP.2021.3094969
Contents
Volume 38 | Number 5 | September 2021
FEATURES COLUMNS
12 SKETCHING DATA SETS FOR 7 Society News
LARGE-SCALE LEARNING New Society Editors-in-Chief
Rémi Gribonval, Antoine Chatalic, Named for 2022
Nicolas Keriven, Vincent Schellekens,
Laurent Jacques, and Philip Schniter 8 Special Reports
Smart Home Technologies Are
37 DIAGNOSIS/PROGNOSIS OF Saving Money and Lives
COVID-19 CHEST IMAGES John Edwards
VIA MACHINE LEARNING AND
HYPERSIGNAL PROCESSING 86 Lecture Notes
Arash Mohammadi, Yingxu Wang, Tracking and Estimation of Frequency,
Nastaran Enshaei, Parnian Afshar, Amplitude, and Form Factor of a
Farnoosh Naderkhani, Harmonic Time Series
Anastasia Oikonomou, R onald M. Aarts
Moezedin Javad Rafiee,
Helder C.R. Oliveira,
Svetlana Yanushkevich, and
Konstantinos N. Plataniotis
ON THE COVER
67 SOUND EVENT DETECTION
Annamaria Mesaros,
Toni Heittola, Tuomas Virtanen, The three feature articles in this issue focus on the process-
and Mark D. Plumbley ing of data, especially large data in high dimension, using
signal processing and machine learning methods.
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IEEE Signal Processing Magazine
3 From the Editor EDITOR-IN-CHIEF ASSOCIATE EDITORS—COLUMNS AND FORUM
Think Outside the Box! Christian Jutten—Université Grenoble Alpes, Balázs Bank—Budapest University of Technology
Christian Jutten France and Economics, Hungary
Ulisses Braga-Neto—Texas A&M University,
4 President’s Message
AREA EDITORS USA
“She Changed Astronomy Forever. Cagatay Candan—Middle East Technical
Feature Articles
He Won the Nobel Prize for It.” University, Turkey
Laure Blanc-Féraud—Université Côte d’Azur,
Ahmed Tewfik Yuan-Hao Huang—National Tsing Hua
France
University, Taiwan
92 Dates Ahead Special Issues
Wei Hu—Peking University, China
Xiaoxiang Zhu—German Aerospace Center,
Andres Kwasinski—Rochester Institute of
Germany
Technology, USA
Columns and Forum Xin Liao—Hunan University, China
Rodrigo Capobianco Guido—São Paulo Piya Pal—University of California San Diego,
State University (UNESP), Brazil USA
H. Vicky Zhao—Tsinghua University, Hemant Patil—Dhirubhai Ambani Institute
R.P. China of Information and Communication
e-Newsletter Technology, India
Behnaz Ghoraani—Florida Atlantic University, Christian Ritz—University of Wollongong,
USA Australia
Social Media and Outreach
Emil Björnson—KTH Royal Institute of Technology, ASSOCIATE EDITORS—e-NEWSLETTER
Sweden Abhishek Appaji—College of Engineering, India
Subhro Das—MIT-IBM Watson AI Lab,
EDITORIAL BOARD IBM Research, USA
Anubha Gupta—Indraprastha Institute of Information
Danijela Cabric—University of
Technology Delhi (IIIT), India
California, USA
Hamid Palangi—Microsoft Research Lab (AI), USA
PG. 92 Mario Figueiredo—Instituto Superior Técnico,
University of Lisbon, Portugal
IEEE SIGNAL PROCESSING SOCIETY
Sharon Gannot—Bar-Ilan University,
Ahmed Tewfik—President
Israel
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2 IEEE SIGNAL PROCESSING MAGAZINE | September 2021 |
FROM THE EDITOR
Christian Jutten | Editor-in-Chief | [email protected]
Think Outside the Box!
Summer is a nice, quiet period, with manifold with suited non-Euclidian
the end of the academic year in many metrics [4]. Finally, in the mid-1990s,
countries. It is a time for vacations he focused on modeling retina, first
and to think about events and develop a the neural layers after the retina and
vision for our future. Of course, this vi- more generally vertebrate visual percep-
sion is based on current research results, tion, for understanding how motions,
biased by fashion effects and publish or textures, colors, etc., are processed in
perish tendencies and perturbated by the the brain. These works result in many
COVID-19 pandemic, which, in depth, powerful bioinspired algorithms, as
modifies our life—professional as well well as applications and patents, which
as personal. are summarized in his very inspir-
First, I would like to evoke the mem- ing book Vision: Images, Signals and
ory of Prof. Jeanny Hérault, who died Neural Networks. Models of Neural
on 7 June 2021. Since 1970, Jeanny had Prof. Jeanny Hérault, keynote speaker at the Processing in Visual Perception [5]
IEEE MLSP 2009 workshop, in Grenoble, France.
been a faculty member at the Polytech- published in 2010. Finally, just after he
nic Institute and then at the University retired, he created a nonprofit associa-
Joseph Fourier in Grenoble, France, innovative methods in signal and im- tion in Grenoble, open to any curious
and he trained dozens of Ph.D. stu- age processing always inspired by person, called Neurocercle (https://
dents, postdocs, and young research- brain and human vision, including ar- neurocercle.wordpress.com), and each
ers. He was my Ph.D. supervisor before tificial neural networks. In early 1980, month since 2009, he has invited a
becoming my friend, and I am sure that inspired by modeling how the brain scientist to talk about advances in neu-
most of you understand from your own of vertebrates can decode arm and leg rosciences and cognitive sciences and
experiences how strong our friend- motions, he proposed the basics of implications in our lives.
ships could be. Some of you knew him blind source separation and indepen-
as well as his contributions: he was dent component analysis [1]. In the In this issue
actually an out-of-the-box scientist. In 1990s, since computers were not pow- Three feature articles are the core of this
this editorial, I will recall some of his erful enough to run artificial neural issue of IEEE Signal Processing Maga-
outstanding contributions around sig- networks, Carver Mead [2] in the Unit- zine (SPM). They are focused on the pro-
nal processing. ed States and a few scientists around cessing of data, especially large data in
Very early on, Jeanny was fascinated the world developed, like Jeanny and high dimension, using signal processing
by the brain, as it is a fantastic machine several of his Ph.D. students, a few and machine learning methods. Clearly,
for signal processing. When he decided special architectures able to train and in these articles, an essential ingredient
to prepare a Ph.D. in 1968, he chose a efficiently use neural networks such is the data. The usual way is to process
topic fully out of the box focused on as multilayer perceptrons and self-or- always larger data sets, larger high-di-
modeling neural cells and simulating ganizing maps [3]. He then developed mension data with very powerful, mul-
them on electronic circuits. And then, the concept of curvilinear component ticore computers. The articles point out
during his entire career, he proposed analysis, which extends the Kohonen’s different tricky learning issues in data
maps to huge-dimension data and sets, i.e., how to deal with unbalanced
implicitly considers high-dimension
Digital Object Identifier 10.1109/MSP.2021.3086574
Date of current version: 27 August 2021 data are embedded in a low-dimension (continued on page 5)
IEEE SIGNAL PROCESSING MAGAZINE | September 2021 | 3
PRESIDENT’S MESSAGE
Ahmed Tewfik | IEEE Signal Processing Society President | [email protected]
“She Changed Astronomy Forever.
He Won the Nobel Prize for It.”
It’s been a while since I last wrote a col- nical, geographical, and gender diver- representatives on publications, con-
umn for IEEE Signal Processing Mag- sity. I won’t belabor again the benefits ferences, and boards; organizing com-
azine. I will try to address here some of diversity. Nor will I detail the real mittees; publication and conferences
of the many questions and changes systemic hurdles that more than half of boards; executive committee mem-
that arose since the beginning of the mankind experiences within society, at bers; president-elect slates; board of
year. But before I do so, I would like to work, home, or our own technical Soci- governors members; and all staff posi-
invite you to watch a short documen- ety. We are all very familiar with these tions. Without a strong and diverse pool
tary by Ben Proudfoot with the exact facts and may even be convinced that of candidates, we won’t have access to
title of this column: “She Changed As- we understand them. Perhaps we do. the best candidates for any given role,
tronomy Forever. He Won the Nobel But it appears to me that, in many cas- will come short on innovation, and
Prize for It.” This story is yet another es, this understanding is abstract rather won’t dismantle the barriers that hold
reminder of how diversity is sine qua than visceral. Hence, it doesn’t reflect many of us back.
non for innovation. The documentary in our actions. Another topic that keeps coming up
covers the discovery of pulsars in 1967 Our goals as a Society include achiev- is the relationship between signal pro-
by Jocelyn Bell Burnell. Her discov- ing excellence and fairness, empower- cessing and machine learning. Many of
ery changed our view of the universe. ing all our members, and helping our us appear frustrated that our conferenc-
Dr. Bell was a Ph.D. student at the time, fellow men and women achieve their es and publications aren’t garnering the
studying under renowned astronomer full potential. Quotas won’t get us there same attention and prestige as machine
Anthony Hewish. She overcame nu- and can be damaging. Online training learning publications and conference
merous barriers as the only woman in and statements that profess our belief venues. Others bemoan the fact that our
many classes and in the Ph.D. program. in equity and diversity aren’t enough. best students prefer to submit their best
Her persistence and unconventional I personally believe that it is our indi- work to machine learning conferences
thinking led her to uncover pulsars vidual and collective responsibility to rather than ICASSP or ICIP. Machine
when others saw only normal electro- source diversity. Results are what mat- learning is yet another arrow in our
magnetic interference. ters. It is our responsibility to find the quiver, no different than linear alge-
Despite the remarkable progress we underrepresented talent that espouse bra, probability and statistics, number
have made since Dr. Bell was a student, unconventional thinking and creativity theory, information theory, and the host
lack of diversity remains one of our most and take calculated risks, regardless of of other disciplines that we leverage to
pernicious and frustrating challenges in their external appearance or extrinsic bring magic to humankind. It may ac-
2021. Diversity is an issue that we all label arbitrarily applied to them by so- tually be a better arrow, particularly
profess to believe in. However, our ac- ciety, to foster innovation and be true to when judiciously combined with other
tions often belie our declared values. the aforementioned goals. That is why innovations that we as a community
Time and again this year, we were sent we, as a Society, passed a resolution that contributed to human knowledge. We
nomination slates for various positions, mandates the sourcing of diversity in all don’t seem to be bothered by the fact
from representatives of the Society on our functions. We expect all our mem- that core linear algebra meetings, pub-
cosponsored conferences to executive bers, committees, and boards to actively lications, and Societies are where most
committee members that lacked tech- seek diversity in generating candidates core linear algebra results are presented
for all volunteer and staff positions, from and discussed. Why is the situation dif-
Distinguished Lecturers to panelists; ferent when it comes to machine learn-
Digital Object Identifier 10.1109/MSP.2021.3100655
Date of current version: 27 August 2021 invited speakers to keynote speakers; ing? Indeed, our computer science
4 IEEE SIGNAL PROCESSING MAGAZINE | September 2021 |
colleagues have leveraged signal pro- town halls will give you an opportunity presentation in virtual meetings. Such
cessing tools to advance machine learn- to ask candidates direct questions about an approach has the advantage of quick
ing. No one has exclusive ownership issues that are dear to you or suggest to validation and interactive dissemina-
of any intellectual construct or tool. the candidates the initiatives that will tion of innovation without sacrificing
Transformational innovations that re- benefit all of us. The webinars will fo- review quality, in contrast to the current
sult from creative insights and cross cus on strategic planning, as I indicated latency built in our journal and even
disciplinary synergies deservedly get in a previous column. I urge you to bring conference publication mechanisms.
the limelight. That is precisely what we innovative ideas to these webinars. For Should we explore such unconventional
should focus on. example, building on the lessons we’ve publication fora?
To foster innovation and unconven- learned from virtual conferences in the
tional thinking, we’re also inviting you COVID-19 era, some of our computer
to participate in a number of online we- science colleagues are promoting the
binars and town halls. New this year are idea of periodic paper submission op-
town halls for you to meet candidates portunities, followed by a fast and rig-
for the president-elect position. These orous review process and immediate SP
FROM THE EDITOR
(continued from page 3)
classes, with missing data, with too- of compressive sensing to compressive dare to investigate these a little crazy
small data sets, etc. The articles suggest learning, i.e., to extract a small num- and out-of the-box ideas!
smart solutions for overcoming these ber of lower-dimension features based
problems, e.g., how one can artificially on averaged nonlinear mappings of the
generate additional relevant data for initial data. This idea presents many
completing missing or unbalanced data, advantages: it avoids storing huge
or how one can use transfer learning for data in memory; it leads to much faster
reducing learning time and complexity. learning algorithms, able to run on sim- References
Thus, based on even larger completed ple embedded devices; it can achieve [1] C. Jutten and J. Hérault, “Blind separation of
sources, part I: An adaptive algorithm based on neuro-
data sets, requiring higher computation- similar or even better performance than mimetic architecture,” Signal Process., vol. 24, no. 1,
al loads, performance can be improved. using the complete data sets. Sketching 1991, pp. 1–10. doi: 10.1016/0165-1684(91)90079-X.
However, there is another unusual is also able to preserve data privacy, [2] C. Mead and M. Ismail, Analog VLSI implemen-
tation of neural systems, (The Kluwer International
way to address the scale problem of which is very important when using Series in Engineering and Computer Science). Norwell,
processing huge data sets, an out-of- sensitive data. MA: Kluwer Academic Publishers, 1989, vol. 80.
[3] J. C. Lawson, N. Maria and J. Hérault, “SMART:
the-box idea perfectly illustrated by Of course, it is much more com-
neurocomputer using sparse matrices,” in Proc.
the first feature article “Sketching Data fortable to do incremental research, Euromicro Workshop on Parallel Distrib. Process.,
1993, pp. 59–64. doi: 10.1109/EMPDP.1993.336420.
Sets for Large-Scale Learning” in this following the current flow of research.
[4] P. Demartines and J. Hérault, “Curvilinear com-
issue of SPM. Instead of enlarging the Sure, it is risky to be out of the box: ponent analysis: A self-organizing neural network for
data sets, the basic idea of sketching it requires a lot of effort to explain nonlinear mapping of data sets,” IEEE Trans. Neural
Netw., vol. 8, no. 1, pp. 148–154, 1997. doi:
is to only keep the data you need. The new ideas, and it also will take longer 10.1109/72.554199.
idea of sketching is particularly intelli- and be more difficult to be published. [5] J. Hérault, “Vision: Images, signals and neural
gent as well as ecological. Faced with But, I believe that such out-of-the-box networks,” in Models of Neural Processing in
Visual Perception. World Scientific, 2010. doi:
huge data learning, the main principle ideas are actually mandatory for in- 10.1142/7311.
of sketching is to extend the concept novation and science advances. So, SP
IEEE SIGNAL PROCESSING MAGAZINE | September 2021 | 5
2022 IEEE International Conference on
Acoustics, Speech, and Signal Processing
human-centric signal processing May 22 - 27, 2022, Sands Expo & Convention Centre
https://2022.ieeeicassp.org/
General Chair The International Conference on Acoustics, Speech, & Signal Processing (ICASSP), is the IEEE Signal
Haizhou Li (NUS, Singapore) Processing Society’s flagship conference on signal processing and its applications. The 47th edition of
ICASSP will be held in Singapore. The programme will include keynotes by pre-eminent international
General Co-Chair
Sadaoki Furui (NII, Japan) speakers, cutting-edge tutorial topics, and forward-looking special sessions. ICASSP also provides a great
networking opportunity with a wide range of like-minded professionals from academia.
Honorary Chair
Tsuhan Chen (NUS, Singapore) CONFERENCE TOPICS
Technical Program Chairs • Applied Signal Processing Systems • Multimedia Signal Processing
Woon-Seng Gan (NTU, Singapore)
• Audio & Acoustic Signal Processing • Quantum Signal Processing
Kai-Kuang Ma (NTU, Singapore)
• Bio Imaging & Signal Processing • Remote Sensing and Signal
Finance Chairs • Compressive Sensing, Sampling Processing
Lei Wang (COLIPS, Singapore) & Dictionary Learning • Sensor Array & Multichannel
Yan Wu (I2R, A*STAR, Singapore) • Computational Imaging Signal Processing
Special Session Chairs • Computer Vision Financial Signal Processing • Signal Processing for Big Data
Jonathon Chambers (Uleicester, UK) • Deep Learning/Machine Learning • Signal Processing for Communication
Zhengguo Li (I2R, A*STAR, Singapore) for Signal Processing & Networking
Pina Marziliano (EPFL, Switzerland) • Image, Video & Multidimensional • Signal Processing for Cyber Security
Plenary Chairs Signal Processing • Signal Processing for Education
C.-C. Jay Kuo (USC, USA) • Industrial Signal Processing • Signal Processing Over Graphs
Helen Meng (CUHK, HK SAR, China) • Information Forensics & Security • Signal Processing Theory & Methods
Douglas O’Shaughnessy (INRS, Canada) • Internet of Things • Speech & Language Processing
Tutorial Chairs
Mauro Barni (USiena, Italy) Call for Tutorials:Tutorials at ICASSP form an important part of the program, giving attendees the
Saeid Sanei (NottinghamTU, UK) opportunity to learn about current research areas that are of growing interest to the signal processing
Tanja Schultz (U Bremen, Germany)
community. Therefore, the tutorials should be prepared and presented to a wide audience. Prospective
Publication Chairs presenters may discuss their proposals with the tutorials chair before the submission.
Kenneth Lam (HKPU, HK SAR, China)
Berrak Sisman (SUTD, Singapore)
Yan Sun (URI, USA) Call for Special Sessions:The program for ICASSP 2022 will include Special Sessions that
complement the main program, in line with the technical scope of the conference. Please refer to the
Local Arrangement Chairs conference webpage for information about Special Session proposals and submissions.
Minghui Dong (I2R, A*STAR, Singapore)
Kong Aik Lee (I2R, A*STAR, Singapore)
Siqi Cai (NUS, Singapore) Call for Exhibitors and Sponsors:ICASSP offers exhibitors and companies an opportunity to
showcase their products and innovative solutions, as well as recruitment and networking opportunities.
Show and Tell Chairs Please check the conference webpage for information about signing up to become an exhibitor or
Nancy Chen (I2R, A*STAR, Singapore)
Tomi Kinnunen (UEF, Finland) sponsor at ICASSP 2022.
Rong Tong (COLIPS, Singapore)
SP Society Journal Paper Presentations:Authors of papers in the journals of the IEEE Signal
Student and Education Activities Chairs
Rongshan Yu (XMU, China) Processing Society will have the opportunity to present their work at ICASSP 2022, subject to space
Kenan Emir Ak (I2R, A*STAR, Singapore) availability and approval by the Technical Program Chairs. Only papers published between October 20,
2020 and October 19, 2021 are eligible for presentation at ICASSP 2022. The papers presented at ICASSP
Sponsorship Chairs will neither be reviewed nor included in the proceedings for the IEEE Xplore Digital Library.
Zhizheng Wu (Facebook, USA)
Lei Xie (NWPU, China)
Open Preview:Open Preview allows conference proceedings to be available in the IEEE Xplore
Publicity Chair Digital Library, free of charge, to all customers, 30 days prior to the conference start date, through the
Eliathamby Ambikairajah (UNSW, Australia)
conference end date.
Grand Challenge Chairs
Andy Khong (NTU, Singapore) IMPORTANT DATES
Wee Peng Tay (NTU, Singapore)
Industry & Exhibits Chairs Special Session Proposal ................................................. 9 August 2021
Fa-Long Luo (Micron, USA) Special Session Acceptance .................................... 6 September 2021
Wei Lu (SUTD, Singapore)
Tutorial Proposals ............................................................ 11 October 2021
Soujanya Poria (SUTD, Singapore)
Paper Submissions ............................................................. 1 October 2021
Women’s Activities Chair Grand Challenge Proposal ............................................ 18 October 2021
Dorien Herremans (SUTD, Singapore) Grand Challenge Acceptance .................................... 8 November 2021
Tutorial Acceptance ................................................... 15 November 2021
Social Media Chair
Chitralekha Gupta (NUS, Singapore) SPS Journal/Letters Due ................................................ 10 January 2022
Paper Acceptance ........................................................... 21 January 2022
American Liaison Final Paper ........................................................................ 17 February 2022
Jane Wang (UBC, Canada) Author Registration ........................................................ 17 February2022
Roxana Saint-Norm (UADE, Argentina)
Open Preview ......................................................... 22 April - 27 May 2022
Singapore Chapter Liaison Show and Tell Proposals ..................................................... 7 March 2022
Ngai-Man (Man) Cheung (SUTD, Singapore)
Digital Object Identifier 10.1109/MSP.2021.3102794
SOCIETY NEWS
New Society Editors-in-Chief Named for 2022
The following volunteers have been He is a Fellow of IEEE and is with the University of Padua, Italy. He is suc-
named editors-in-chief of IEEE Sig- University of Illinois at Urbana–Cham- ceeding Patrizio Campisi, University of
nal Processing Society publications. paign. He is succeeding Dilek Hakkani- Roma TRE, who has held the post
The term for these editors-in-chief will Tur, Amazon Alexa AI, who has held since 2018.
run from 1 January 2022 through 31 the post since 2019.
December 2024. Pascal Frossard
Mujdat Cetin Pascal Frossard is the
Xiao-Ping Zhang Mujdat Cetin is the new editor-in-chief of
Xiao-Ping Zhang has new editor-in-chief of IEEE Transactions on
been named editor-in- IEEE Transactions on Signal and Informa-
chief of IEEE Journal Computational Imag- tion Processing Over
of Selected Topics in ing. He is a Fellow of Networks. He is a
Signal Processing. He IEEE and is with the Fellow of IEEE and is with EPFL,
is a Fellow of IEEE University of Rochester, New York. He Switzerland. He is succeeding Anto-
and is with Ryerson University, Cana- is succeeding Brendt Wohlberg, Los nio Ortega, University of Southern
da. He is succeeding Lina J. Karam, Alamos National Laboratory, who has California, who has held the post
Lebanese American University, who been in the role since 2018. since 2019.
has held the post since 2019.
Mauro Conti SP
Paris Smaragdis Mauro Conti has taken
Paris Smaragdis has the role of editor-in-
taken the role of edi- chief of IEEE Trans-
tor-in-chief of IEEE/ actions on Information
ACM Transactions on Forensics and Securi-
Audio, Speech, and ty. He is a Senior
Language Processing. Member of IEEE and is with the
Digital Object Identifier 10.1109/MSP.2021.3094863
Date of current version: 27 August 2021
IEEE SIGNAL PROCESSING MAGAZINE | September 2021 | 7
SPECIAL REPORTS
John Edwards
Smart Home Technologies Are Saving Money and Lives
Reaching out in new directions, signal processing-supported
smart technologies are rapidly changing—and improving—everyday life
Smart home technologies, designed also a deep learning network that mod- tions created by multiple appliances by
to make users happier, healthier, els vibration data to create different sig- detecting the distinct noise each device
and wealthier, are rapidly becom- natures for each appliance. creates as well as by identifying the paths
ing a mainstay of everyday life. In most Many home appliances generate traveled by each vibration as it moves
cases, signal processing is essential to the vibrations identifiable by unique signa- from room to room. VirbroSense’s deep
devices’ operation and performance. tures that propagate through a home’s learning network is trained to distin-
These days, a variety of intelligent walls, ceilings, and other infrastructure guish from among different activities.
automated devices can be found in elements, observes Cheng Zhang, a Cor- In tests spanning five separate
nearly every home. The trend is accel- nell assistant professor of computing and houses, VibroSense achieved a nearly
erating so rapidly that it now appears information science as well as director of 96% accuracy, identifying 17 different
inevitable that smart technology will the university’s SciFi Lab. “These unique activities, including dripping faucets, an
soon be integrated into virtually every characteristics … can be captured by a exhaust fan, an electric kettle, a refrigera-
facet of daily life. laser vibrometer and recognized by AI tor, and a range hood (see Figure 1). The
With smart technologies already (artificial intelligence) technology—in technology was also able to distinguish
widely used in applications as diverse our case, a deep learning algorithm—to five different stages of appliance usage
as home security, environmental con- distinguish the sound source.” with an average accuracy of more than
trol, and home entertainment, research- Zhang says that VibroSense promises 97%. In single-story houses, the laser
ers are now heading in new directions, to allow users to monitor multiple house- was pointed at an interior wall at the cen-
leading to applications as diverse as hold appliance activities with just a single ter of the home. The device was pointed
home appliance monitoring, improved sensor. Besides alerting users to runaway at the ceiling in two-story homes.
power delivery, and advanced remote appliances, the technology also promises Signal processing was the first tech-
medical support. to give homeowners a way to track ener- nology the researchers considered when
gy expenses. “Knowing which device exploring the system’s feasibility. “We
Good vibrations is working, and for how long and under use signal processing to help us ana-
For anyone who has ever neglected to which mode, would potentially help the lyze the information from the captured
turn off an electric kettle, water faucet, owner of the house to estimate and better vibration data,” Zhang says. Various
air conditioner, or other household appli- manage power usage,” he notes. types of filters are then used to remove
ance before leaving home—potentially To create a smart home using con- noise. “We visualize the signal in both
leading to unfortunate consequences— ventional technology, it’s currently time and frequency domains, which
Cornell University researchers are offer- necessary to equip each appliance with helps us to find any distinguishable
ing a potential safeguard. The team’s smart technology, Zhang observes. “Our features,” he notes. A Fourier trans-
new VibroSense device is a smart home system is the first that can monitor devic- form is used to convert the data from
technology that can track 17 types es across different floors, in different time to frequency domain. “We also
of appliances using subtle vibrations rooms, using a single device.” use wavelet transformation and band-
found in walls, ceilings, and floors; it is To monitor appliance usage through- pass filter to help remove the noise and
out an entire house, VibroSense is improve the signal-to-noise ratio.”
equipped with a laser Doppler vibrom- Signal processing methods also enab-
Digital Object Identifier 10.1109/MSP.2021.3088401
Date of current version: 27 August 2021 eter. The device differentiates the vibra- led the researchers to quickly verify an
8 IEEE SIGNAL PROCESSING MAGAZINE | September 2021 | 1053-5888/21©2021IEEE
