ABOUT THE SPEAKER
Jennifer Healey - Research scientist
A research scientist at Intel, Jennifer Healey develops the mobile internet devices of the future.

Why you should listen

Jennifer Healey imagines a future where computers and smartphones are capable of being sensitive to human emotions and where cars are able to talk to each other, and thus keep their drivers away from accidents. A scientist at Intel Corporation Research Labs, she researches devices and systems that would allow for these major innovations.

Healey holds PhD from MIT in electrical engineering and computer science. While there, she pioneered “Affective Computing” with Rosalind Picard and developed the first wearable computer with physiological sensors and a video camera that allows the wearer to track their daily activities and how they feel while doing them. From there, she moved to IBM where she worked on the next generation of multi-modal interactive smartphones and helped architect the "Interaction Mark-Up language" that allows users to switch from voice to speech input seamlessly.

Healey has also used her interest in embedded devices in the field of healthcare. While an instructor at Harvard Medical School and at Beth Israel Deaconess Medical Center, she worked on new ways to use heart rate to predict cardiac health. She then joined HP Research in Cambridge to further develop wearable sensors for health monitoring and continued this research when she joined Intel Digital Health.

More profile about the speaker
Jennifer Healey | Speaker | TED.com
TED@Intel

Jennifer Healey: If cars could talk, accidents might be avoidable

Jennifer Healey: Kada bi automobili mogli pričati, nesreće bi mogle biti izbjegnute.

Filmed:
908,454 views

Kada vozimo, ulazimo u stakleni balon, zaključamo vrata i pritisnemo gas, oslanjajući se na naše oči da nas vode-- iako možemo vidjeti samo nekoliko automobila ispred i iza nas. Ali što kada bi automobili mogli dijeliti podatke sa drugima o svom položaju i brzini, i koristiti modele predviđanja za izračunavanje najsigurnijih ruta za svakoga na cesti? Jennifer Healey zamišlja svijet bez nesreća. (Snimljeno na TED@Intel.)
- Research scientist
A research scientist at Intel, Jennifer Healey develops the mobile internet devices of the future. Full bio

Double-click the English transcript below to play the video.

00:12
Let's facelice it:
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Suočimo se
00:14
DrivingVožnje is dangerousopasno.
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Vožnja je opasna.
00:17
It's one of the things that we don't like to think about,
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To je jedna od stvari o kojima ne volimo razmišljati,
00:20
but the factčinjenica that religiousvjerski iconsikone and good lucksreća charmsčari
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ali činjenica da se religijske ikone i simboli sreće
00:23
showpokazati up on dashboardsnadzorne ploče around the worldsvijet
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pojavljuju na kontrolnim pločama po cijelome svijetu
00:28
betraysizdaje the factčinjenica that we know this to be truepravi.
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odaje činjenicu da znamo da je to istina.
00:32
CarAuto accidentsnesreća are the leadingvodeći causeuzrok of deathsmrt
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Automobilske nesreće su glavni uzrok smrti
00:36
in people agesdobi 16 to 19 in the UnitedUjedinjeni StatesDržava --
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kod ljudi starih 16 do 19 godina u Americi--
00:40
leadingvodeći causeuzrok of deathsmrt --
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glavni uzrok smrti--
00:43
and 75 percentposto of these accidentsnesreća have nothing to do
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i 75% tih nesreća nema veze
00:47
with drugslijekovi or alcoholalkohol.
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sa drogama i alkoholom.
00:49
So what happensdogađa se?
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Onda, što se događa?
00:51
No one can say for sure, but I rememberzapamtiti my first accidentnesreća.
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Nitko ne može sa sigurnošću reći, ali ja se sjećam svoje prve nesreće.
00:55
I was a youngmladi drivervozač out on the highwayautocesta,
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Bila sam mladi vozač na autocesti,
00:59
and the carautomobil in frontispred of me, I saw the brakekočnica lightssvjetla go on.
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i automobil ispred mene, vidjela sam da se pale svjetla kočenja.
01:02
I'm like, "Okay, all right, this guy is slowingusporavanje down,
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Mislila sam, "Ok, sve u redu, on usporava,
01:03
I'll slowusporiti down too."
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usporit ću i ja."
01:05
I stepkorak on the brakekočnica.
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Pritisnula sam kočnicu.
01:07
But no, this guy isn't slowingusporavanje down.
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Ali ne, on ne usporava.
01:09
This guy is stoppingzaustavljanje, deadmrtav stop, deadmrtav stop on the highwayautocesta.
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On se zaustavlja, staje na autocesti.
01:12
It was just going 65 -- to zeronula?
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Vozio je 100-- prema nuli?
01:15
I slammedudario on the brakeskočnice.
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Nagazila sam na kočnicu.
01:16
I feltosjećala the ABSABS kickudarac in, and the carautomobil is still going,
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Osjetila sam ABS, a automobil se i dalje kreće,
01:19
and it's not going to stop, and I know it's not going to stop,
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i neće se zaustaviti, znala sam da se neće zaustaviti,
01:22
and the airzrak bagtorba deploysraspoređuje, the carautomobil is totalediznosio,
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zračni jastuk se otvara, auto je totalka,
01:25
and fortunatelysrećom, no one was hurtpovrijediti.
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i na sreću, nitko nije nastradao.
01:28
But I had no ideaideja that carautomobil was stoppingzaustavljanje,
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Ali ja nisam imala pojma da se taj automobil zaustavljao,
01:32
and I think we can do a lot better than that.
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i mislim da to možemo promijeniti.
01:36
I think we can transformtransformirati the drivingvožnja experienceiskustvo
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Mislim da možemo promijeniti iskustvo vožnje
01:40
by lettingiznajmljivanje our carsautomobili talk to eachsvaki other.
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tako da pustimo da automobili razgovaraju jedni s drugima.
01:44
I just want you to think a little bitbit
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Samo želim da malo razmislite
01:46
about what the experienceiskustvo of drivingvožnja is like now.
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o iskustvu vožnje.
01:48
Get into your carautomobil. CloseZatvori the doorvrata. You're in a glassstaklo bubblemjehurić.
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Uđite u svoj automobil. Zatvorite vrata. Vi ste u staklenom balonu.
01:53
You can't really directlydirektno senseosjećaj the worldsvijet around you.
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Ne možete izravno osjetiti svijet oko vas.
01:55
You're in this extendedprodužen bodytijelo.
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Vi ste u ovom proširenom tijelu.
01:58
You're taskedčiji je zadatak with navigatingNavigacija it down
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Zaduženi ste da njime upravljate
02:00
partially-seendjelomično vidio roadwaysprometnica,
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djelomično vidljivim cestama,
02:02
in and amongstmeđu other metalmetal giantsdivovi, at super-humanSuper-ljudsko speedsbrzine.
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u i među ostalim metalnim divovima, pri super ljudskim brzinama.
02:06
Okay? And all you have to guidevodič you are your two eyesoči.
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U redu? I sve što vas vodi su vaše oči.
02:11
Okay, so that's all you have,
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U redu, to je sve što imate,
02:12
eyesoči that weren'tnisu really designedkonstruiran for this taskzadatak,
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oči koje zaista nisu stvorene za ovaj zadatak,
02:14
but then people askpitati you to do things like,
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ali onda vas ljudi traže da radite stvari poput,
02:18
you want to make a lanetraka changepromijeniti,
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želite li se prestrojavati,
02:20
what's the first thing they askpitati you do?
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koja je prva stvar koju vas traže da napravite?
02:22
Take your eyesoči off the roadcesta. That's right.
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Skrenite pogled s ceste. Točno to.
02:25
Stop looking where you're going, turnskretanje,
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Prestanite gledati kamo idete, okrenite se,
02:27
checkprovjeriti your blindslijep spotmjesto,
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provjerite mrtvi kut,
02:29
and drivepogon down the roadcesta withoutbez looking where you're going.
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i vozite po cesti bez da gledate kamo idete.
02:33
You and everyonesvatko elsedrugo. This is the safesef way to drivepogon.
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Vi i svi ostali. To je siguran način vožnje.
02:36
Why do we do this? Because we have to,
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Zašto to činimo? Zato što moramo,
02:38
we have to make a choiceizbor, do I look here or do I look here?
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moramo odabrati, hoću li pogledati ovdje ili ondje?
02:40
What's more importantvažno?
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Što je važnije?
02:42
And usuallyobično we do a fantasticfantastičan jobposao
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I uglavnom odradimo fantastičan posao
02:45
pickingbranje and choosingOdabir what we attendprisustvovati to on the roadcesta.
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i uspijemo opaziti sve bitno na cesti.
02:48
But occasionallypovremeno we misspropustiti something.
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Ali ponekad nešto propustimo.
02:52
OccasionallyPovremeno we senseosjećaj something wrongpogrešno or too latekasno.
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Ponekad opazimo nešto krivo ili prekasno.
02:57
In countlessnebrojen accidentsnesreća, the drivervozač sayskaže,
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U bezbroj nesreća, vozači kažu,
02:59
"I didn't see it comingdolazak."
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"Nisam vidio da dolazi."
03:01
And I believe that. I believe that.
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I ja to vjerujem. Vjerujem.
03:04
We can only watch so much.
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Ne možemo vidjeti sve.
03:07
But the technologytehnologija existspostoji now that can help us improvepoboljšati that.
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Ali, s današnjom tehnologijom možemo to poboljšati.
03:12
In the futurebudućnost, with carsautomobili exchangingrazmjena datapodaci with eachsvaki other,
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U budućnosti, sa izmjenom podataka među automobilima,
03:17
we will be ableu stanju to see not just threetri carsautomobili aheadnaprijed
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bit ćemo u mogućnosti vidjeti, ne samo tri automobila sprijeda
03:20
and threetri carsautomobili behindiza, to the right and left,
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i tri automobila straga, lijevo i desno,
03:22
all at the sameisti time, bird'sptica je eyeoko viewpogled,
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sve u isto vrijeme, ptičja perspektiva,
03:25
we will actuallyzapravo be ableu stanju to see into those carsautomobili.
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već ćemo biti u mogućnosti vidjeti unutrašnjost tih automobila.
03:28
We will be ableu stanju to see the velocitybrzina of the carautomobil in frontispred of us,
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Bit ćemo u mogućnosti vidjeti brzinu automobila ispred nas,
03:31
to see how fastbrzo that guy'stip je going or stoppingzaustavljanje.
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kako bi vidjeli kako brzo osoba vozi ili zastaje.
03:34
If that guy'stip je going down to zeronula, I'll know.
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Ako se ta osoba zaustavlja, znat ćemo.
03:38
And with computationračunanje and algorithmsalgoritmi and predictivePrediktivni modelsmodeli,
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I sa izračunima i algoritmima i predvidivim modelima,
03:42
we will be ableu stanju to see the futurebudućnost.
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bit ćemo u mogućnosti vidjeti budućnost.
03:46
You maysvibanj think that's impossiblenemoguće.
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Možda mislite da je to nemoguće.
03:47
How can you predictpredvidjeti the futurebudućnost? That's really hardteško.
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Kako možemo predvidjeti budućnost? To je zaista teško.
03:50
ActuallyZapravo, no. With carsautomobili, it's not impossiblenemoguće.
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Zapravo, ne. Sa automobilima to nije nemoguće.
03:54
CarsAutomobili are three-dimensionaltrodimenzionalni objectsobjekti
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Automobili su trodimenzionalni objekti
03:56
that have a fixedfiksni positionpoložaj and velocitybrzina.
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koji imaju stalnu poziciju i brzinu.
03:59
They travelputovati down roadsceste.
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Putuju cestama.
04:00
OftenČesto they travelputovati on pre-publishedunaprijed objavljeni routesruta.
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Često putuju na unaprijed objavljenim rutama.
04:03
It's really not that hardteško to make reasonablerazuman predictionspredviđanja
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Zaista nije tako teško napraviti razumna predviđanja
04:07
about where a car'sautomobili going to be in the nearblizu futurebudućnost.
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o tome gdje će automobili biti u bližoj budućnosti.
04:09
Even if, when you're in your carautomobil
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Čak i kada ste u automobilu
04:11
and some motorcyclistMotociklist comesdolazi -- bshoombshoom! --
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i neki motociklist dolazi--bsoom!--
04:13
85 milesmilja an hoursat down, lane-splittingLane-razdvajanje --
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135 kilometara na sat, po sredini ceste, između vozila,
04:16
I know you've had this experienceiskustvo --
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Znam da ste imali ovakvo iskustvo--
04:18
that guy didn't "just come out of nowherenigdje."
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ta osoba nije došla "niotkuda."
04:21
That guy'stip je been on the roadcesta probablyvjerojatno for the last halfpola hoursat.
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Ta je osoba bila na cesti vjerojatno zadnjih pola sata.
04:25
(LaughterSmijeh)
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(Smijeh)
04:26
Right? I mean, somebody'snetko je seenvidio him.
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Zar ne? Mislim, netko ju je vidio.
04:29
TenDeset, 20, 30 milesmilja back, someone'snetko seenvidio that guy,
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10, 20, 30 kilometara otraga, netko je tu osobu vidio,
04:32
and as soonuskoro as one carautomobil seesvidi that guy
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i čim jedan automobil vidi tu osobu
04:34
and putsstavlja him on the mapkarta, he's on the mapkarta --
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i stavi ga na kartu, on je na karti--
04:37
positionpoložaj, velocitybrzina,
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pozicija, brzina,
04:39
good estimateprocjena he'llpakao continuenastaviti going 85 milesmilja an hoursat.
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vrlo je vjerojatno da će on nastaviti ići 135 km na sat.
04:41
You'llVi ćete know, because your carautomobil will know, because
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Vi ćete to znati, zato što će vaš automobil znati, jer
04:43
that other carautomobil will have whisperedšapnula something in his earuho,
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će taj drugi automobil šapnuti nešto njemu na uho,
04:46
like, "By the way, fivepet minutesminuta,
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poput, "Usput, pet minuta,
04:48
motorcyclistMotociklist, watch out."
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motociklist, pazi se."
04:50
You can make reasonablerazuman predictionspredviđanja about how carsautomobili behaveponašati.
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Možete napraviti razumna predviđanja o tome kako se automobili ponašaju.
04:53
I mean, they're NewtonianNewton-ove objectsobjekti.
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Mislim, oni su Newtonovi objekti.
04:54
That's very nicelijepo about them.
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To je ono lijepo kod njih.
04:57
So how do we get there?
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Onda, kako stižemo tamo?
05:00
We can startpočetak with something as simplejednostavan
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Možemo započeti s nečim jednostavnim
05:03
as sharingdijeljenje our positionpoložaj datapodaci betweenizmeđu carsautomobili,
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poput razmjene podataka o našoj poziciji između automobila,
05:05
just sharingdijeljenje GPSGPS.
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samo dijeljenjem GPS-a.
05:07
If I have a GPSGPS and a camerafotoaparat in my carautomobil,
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Ako ja imam GPS i kameru u svom automobilu,
05:10
I have a prettyprilično preciseprecizan ideaideja of where I am
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Mogu prilično točno znati gdje se nalazim
05:12
and how fastbrzo I'm going.
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i kako brzo se krećem.
05:14
With computerračunalo visionvizija, I can estimateprocjena where
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Pomoću računala, mogu otprilike procjeniti
05:15
the carsautomobili around me are, sortvrsta of, and where they're going.
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gdje se nalaze automobile oko mene, i kamo idu.
05:19
And sameisti with the other carsautomobili.
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I isto je sa ostalim autmobilima.
05:20
They can have a preciseprecizan ideaideja of where they are,
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I oni mogu točno znati gdje se nalaze,
05:22
and sortvrsta of a vaguenejasan ideaideja of where the other carsautomobili are.
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i otprilike znati gdje se nalaze ostali .
05:24
What happensdogađa se if two carsautomobili sharePodjeli that datapodaci,
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Što se događa ako dva automobila podijele te podatke,
05:27
if they talk to eachsvaki other?
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ako razgovaraju jedan s drugim?
05:29
I can tell you exactlytočno what happensdogađa se.
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Mogu vam točno reći što se događa.
05:32
BothOba modelsmodeli improvepoboljšati.
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Poboljšanje oba modela.
05:34
EverybodySvi winspobjeda.
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Svi su na dobitku.
05:36
ProfessorProfesor BobBob WangWang and his teamtim
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Profesor Bob Wang i njegov tim
05:39
have doneučinio computerračunalo simulationssimulacije of what happensdogađa se
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napravili su računalnu simulaciju o tome što se događa
05:42
when fuzzynejasan estimatesprocjene combinekombinirati, even in lightsvjetlo trafficpromet,
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kada se kombiniraju nejasne procjene ,čak i sa semaforima
05:45
when carsautomobili just sharePodjeli GPSGPS datapodaci,
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kada automobili dijele GPS podatke,
05:48
and we'veimamo movedpomaknuto this researchistraživanje out of the computerračunalo simulationsimuliranje
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i prenesli smo ovo istraživanje iz računalne simulacije
05:50
and into robotrobot testtest bedsležaja that have the actualstvaran sensorssenzori
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u probni robot koji ima stvarne senzore
05:53
that are in carsautomobili now on these robotsroboti:
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koji su sada u automobilu na tim robotima:
05:56
stereostereo cameraskamere, GPSGPS,
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kamera, GPS,
05:58
and the two-dimensionaldvodimenzionalan laserlaser rangeopseg findersTko nađe
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i dvodimenzionalni laserski daljinomjer
06:00
that are commonzajednička in backuprezerva systemssustavi.
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koji su uobičajeni u sigurnosnim sustavima.
06:02
We alsotakođer attachpričvrstiti a discretediskretna short-rangekratkog dometa communicationkomunikacija radioradio,
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Također smo pridodali i diskretni komunikacijski radio kratkog dometa,
06:07
and the robotsroboti talk to eachsvaki other.
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i roboti pričaju jedni s drugima.
06:09
When these robotsroboti come at eachsvaki other,
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Kada ti roboti dođu jedan drugome,
06:10
they trackstaza eachsvaki other'sdrugi positionpoložaj preciselyprecizno,
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prate pozicije jedan drugome vrlo precizno,
06:13
and they can avoidIzbjegavajte eachsvaki other.
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i mogu izbjeći jedan drugoga.
06:16
We're now addingdodajući more and more robotsroboti into the mixmiješati,
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Trenutno nadodajemo sve više i više robota u taj mix,
06:19
and we encounterednaišao some problemsproblemi.
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i naišli smo na neke probleme.
06:21
One of the problemsproblemi, when you get too much chatterćaskanje,
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Jedan je problem, kada se previše brblja,
06:23
it's hardteško to processpostupak all the packetspaketi, so you have to prioritizeprvenstvo,
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teško je procesuirati sve pakete, pa morate odrediti prioritete,
06:27
and that's where the predictivePrediktivni modelmodel helpspomaže you.
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i tu vam model predviđanja pomaže.
06:29
If your robotrobot carsautomobili are all trackingpraćenje the predictedpredvidjeti trajectoriesputanje,
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Ako vaši roboti automobili svi prate predviđene putanje,
06:33
you don't payplatiti as much attentionpažnja to those packetspaketi.
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ne obraćate toliko pozornosti na te pakete.
06:35
You prioritizeprvenstvo the one guy
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Prioritizirate jednu osobu
06:37
who seemsčini se to be going a little off coursenaravno.
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koja se čudno kreće.
06:38
That guy could be a problemproblem.
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Ta bi osoba mogla biti problem.
06:41
And you can predictpredvidjeti the newnovi trajectoryputanja.
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I onda možete predvidjeti novu putanju.
06:44
So you don't only know that he's going off coursenaravno, you know how.
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Stoga ne samo da znate da se čudno kreće, već znate i kako.
06:46
And you know whichkoji driversupravljački programi you need to alertuzbuna to get out of the way.
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I znate koje vozače morate upozoriti da se sklone s puta.
06:50
And we wanted to do -- how can we bestnajbolje alertuzbuna everyonesvatko?
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I želimo učiniti-- kako bi najbolje upozorili ostale?
06:53
How can these carsautomobili whisperšapat, "You need to get out of the way?"
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Kako mogu ti automobili šapnuti, "Moraš se skloniti s puta?"
06:56
Well, it dependsovisi on two things:
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Pa, to ovisi o dvije stvari:
06:58
one, the abilitysposobnost of the carautomobil,
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prva je sposobnost automobila,
07:00
and seconddrugi the abilitysposobnost of the drivervozač.
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a druga sposobnost vozača.
07:03
If one guy has a really great carautomobil,
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Ako neka osoba ima zaista super automobil,
07:04
but they're on theirnjihov phonetelefon or, you know, doing something,
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ali razgovara na mobitel, ili, znate već, nešto radi,
07:07
they're not probablyvjerojatno in the bestnajbolje positionpoložaj
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vjerojatno nisu u najboljoj poziciji
07:09
to reactreagirati in an emergencyhitan.
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da reagiraju na hitan slučaj.
07:12
So we startedpočeo a separateodvojen linecrta of researchistraživanje
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Tako da smo počeli odvojenu liniju istraživanja
07:14
doing drivervozač statedržava modelingmanekenstvo.
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vezanu za stanje vozača.
07:16
And now, usingkoristeći a seriesniz of threetri cameraskamere,
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I sada, koristeći seriju od tri kamere,
07:19
we can detectotkriti if a drivervozač is looking forwardnaprijed,
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možemo detektirati ako vozač gleda naprijed,
07:21
looking away, looking down, on the phonetelefon,
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gleda okolo, gleda dolje, ako je na telefonu,
07:24
or havingima a cupkupa of coffeekava.
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ili pije kavu.
07:27
We can predictpredvidjeti the accidentnesreća
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Možemo predvidjeti nesreću
07:29
and we can predictpredvidjeti who, whichkoji carsautomobili,
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i možemo predvidjeti tko, koji automobili,
07:33
are in the bestnajbolje positionpoložaj to movepotez out of the way
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su u najboljoj poziciji da se maknu s puta
07:36
to calculateizračunati the safestnajsigurniji routeput for everyonesvatko.
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kako bi izračunali najsigurniju rutu za sve.
07:39
FundamentallyOsnovi, these technologiestehnologije existpostojati todaydanas.
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Fundamentalno, ova tehnologija danas postoji.
07:44
I think the biggestnajveći problemproblem that we facelice
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Mislim da je najveći problem s kojim se suočavamo
07:47
is our ownvlastiti willingnessspremnost to sharePodjeli our datapodaci.
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naša volja da podijelimo podatke.
07:50
I think it's a very disconcertingzabrinjavajuća notionpojam,
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Mislim da je to vrlo neugodna zamisao,
07:52
this ideaideja that our carsautomobili will be watchinggledanje us,
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ova ideja da će nas automobili gledati,
07:55
talkingkoji govori about us to other carsautomobili,
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razgovarati o nama s ostalim automobilima,
07:58
that we'lldobro be going down the roadcesta in a seamore of gossiptrač.
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da ćemo ići cestom u moru tračeva.
08:02
But I believe it can be doneučinio in a way that protectsštiti our privacyprivatnost,
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Ali vjerujem da to može biti napravljeno na način da se zaštiti naša privatnost,
08:05
just like right now, when I look at your carautomobil from the outsideizvan,
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kao što sada, kada gledam u vaš automobil izvana,
08:09
I don't really know about you.
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zapravo ne znam ništa o vama.
08:12
If I look at your licenselicenca plateploča numberbroj,
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Ako pogledam broj vaše registarske ploče,
08:13
I don't really know who you are.
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zapravo ne znam tko ste.
08:15
I believe our carsautomobili can talk about us behindiza our backsleđa.
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Vjerujem da naši automobili mogu razgovarati o nama iza naših leđa.
08:19
(LaughterSmijeh)
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(Smijeh)
08:22
And I think it's going to be a great thing.
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I mislim da bi to bila odlična stvar.
08:25
I want you to considerrazmotriti for a momenttrenutak
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Želim da na trenutak razmotrite
08:27
if you really don't want the distractedometen teenagertinejdžer behindiza you
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da li zaista ne želite da rastrojeni tinjedžera iza vas
08:31
to know that you're brakingkočenje,
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zna da vi kočite,
08:33
that you're comingdolazak to a deadmrtav stop.
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da se zaustavljate.
08:36
By sharingdijeljenje our datapodaci willinglyRado,
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Šireći svoje podatke dobrovoljno,
08:38
we can do what's bestnajbolje for everyonesvatko.
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možemo učini ono što je najbolje za svih.
08:41
So let your carautomobil gossiptrač about you.
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Stoga, dopustite da vas vaši automobili ogovaraju.
08:44
It's going to make the roadsceste a lot safersigurniji.
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To će učiniti ceste puno sigurnijima.
08:47
Thank you.
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Hvala vam.
08:49
(ApplausePljesak)
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(Pljesak)
Translated by Martina Movrić
Reviewed by SIBELA KESAC

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ABOUT THE SPEAKER
Jennifer Healey - Research scientist
A research scientist at Intel, Jennifer Healey develops the mobile internet devices of the future.

Why you should listen

Jennifer Healey imagines a future where computers and smartphones are capable of being sensitive to human emotions and where cars are able to talk to each other, and thus keep their drivers away from accidents. A scientist at Intel Corporation Research Labs, she researches devices and systems that would allow for these major innovations.

Healey holds PhD from MIT in electrical engineering and computer science. While there, she pioneered “Affective Computing” with Rosalind Picard and developed the first wearable computer with physiological sensors and a video camera that allows the wearer to track their daily activities and how they feel while doing them. From there, she moved to IBM where she worked on the next generation of multi-modal interactive smartphones and helped architect the "Interaction Mark-Up language" that allows users to switch from voice to speech input seamlessly.

Healey has also used her interest in embedded devices in the field of healthcare. While an instructor at Harvard Medical School and at Beth Israel Deaconess Medical Center, she worked on new ways to use heart rate to predict cardiac health. She then joined HP Research in Cambridge to further develop wearable sensors for health monitoring and continued this research when she joined Intel Digital Health.

More profile about the speaker
Jennifer Healey | Speaker | TED.com

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