Allekirjoitan asian mitä tuot ilmi viestissäsi. Itse näen aiheen vain päinvastaisena kuin se että “ostetaan sika säkissä”. Markkinoilla kulkee aina tuotto ja riski käsi kädessä. Jos keissi olisi saletti, mallit tiedossa, kappalemäärät indikoitu usean vuoden päähän olisi myös osakkeen hinta jotain aivan muuta.
Tämän ketjun ansiokkaiden tiedon kaivajien ansiosta koen meillä olevan tilanteen ymmärtämisessä pieni etu muuhun markkinaan verrattuna. Ostamme sikaa säkissä, mutta emme niin pimeänä kuin pelkästään virallisia tiedotteita katsomalla. Tietoja julkaistaan varmasti niin pian kuin NDA:t sen sallivat. Niitä odotellessa pääsemme takomaan ylituottoa tiedon murusia jahtaamalla ja veikkaamalla
Kiitoksia kommentoijille. Hyviä pointteja kaikilla. Ehkä itse olen vaan turhan kärsimätön.
Erityisesti @Jay-EM kommentti riskistä ja tuotosta osui itselleni. Tottahan se näin on. Ehkäpä kun itse on jo ostanut osaketta ja ottanut riskin, sitä haluaisi, että kaikki riskit katoaisi ja sitä vaan nauttisi tuotoista ja osuneesta valinnasta…
Tuo, että lasit haittaisivat ei viittaa kyllä IR kameraan ellei ole sitten joku pakollinen varoitus, jos jotkut lasit sitten haittaisivatkin. Onko tietoa onko tuota varoitusta ollut BMWn käsikirjassa tai muissa Smart eyeta käyttävissä?
Smart Eye’s approach to data collection and privacy
In one of the most well-known clichés, the eyes are the mirror of the soul. But no matter how worn-out the saying is, it might help explain why the idea of someone analyzing images of their eye movements makes some people feel a bit uneasy.
At Smart Eye, collecting video data of humans is essential for developing the technology that eventually winds up in cars or labs all over the world. Images of eye and head movements are what enable us to further scientific research and save lives on the roads. And in order to make our systems as advanced and accurate as possible, they need access to large banks of video data.
But of course, accuracy shouldn’t come at the cost of anyone’s privacy. We realize that in the context of personal data, footage of someone’s head and eye movements can feel especially personal. That’s why we want to walk you through how we gather video data – and what we are doing in order to protect the privacy of the people behind that data.
Why do we collect data?
Before we get into the specifics of the data collection process, we need to let you know why we collect video data in the first place.
Our eye tracking technology is partly based on machine learning, making data collection a crucial part of developing and improving on our software. Think of it as trying to learn a new language. It would be impossible if you didn’t have access to examples of people speaking the language, or sentences written in it. It’s the same with our eye tracking algorithms – there is no way to teach our technology to recognize gaze patterns without feeding it images of eye and head movements. This process is what we refer to as training our software.
Once we’ve developed a finished product, it needs to be continuously tested in order to make sure it lives up to our customers’ expectations. This process is called validation and uses the same types of data as the training of the system.
These two processes, the training and validation of our systems, are our only reasons for collecting video data. Once our products are sold and installed into a vehicle or a research lab, the product has no need for storing any video data. While data collection is unavoidable during the system’s development phase, it is not necessary for the system to work.
How do we collect data?
Our training and validation data come from test sessions with fully informed and consenting participants. These sessions take place in both stationary and driven settings. In the stationary settings – either a lab or in the driver’s seat of a parked car – we have full control of what types of data we are able to gather. Meanwhile, the tests performed in a moving car allow us to observe the participant at their most natural behavior.
Whether the tests take place in a stationary or driven setting, they start with a camera that captures an infrared image of the test participant’s head and upper body. The infrared light generates a sequence of greyscale images, which is all the information our systems need in order to analyze the test participant’s eye movements. The sequence of images, along with the output from our systems, are then saved for evaluation.
The GDPR and legal protection of personal data
Even though we place high value in privacy, our test participants can rest assured that their personal data is protected by legal measures as well. With our headquarters located in Sweden, Smart Eye follows European regulations concerning personal data, including the General Protection Regulation (GDPR). The GDPR regulates the management of personal data and is described by the European Union as the toughest privacy and security law in the world. And since Smart Eye is registered as a European company, the GDPR also applies to any data collection associated with our offices in the United States, China and Japan. In fact, we are required to make sure any data we collect, or even receive, from other parts in the world is in accordance with the GDPR.
Where does the data end up?
Generally speaking, the more data you have access to when developing a product based on machine learning, the better. So, in order to make our technology as accurate as possible, we need access to very large amounts of data. And when that data includes video content of people, we need to make sure our system for storing it is practically bulletproof.
From the second the data is recorded, the only people with access to it are the developers at Smart Eye who use it for development projects. Any newly collected data is temporarily stored on the computers used for recording the data. The recording computers and all intermediate systems are kept in Smart Eye premises and security is ensured by state-of-the art security mechanisms, like policy-based access control such as user rights through login and passwords. But the long-term destination for the data is at our servers at high-security data centers in Gothenburg, Sweden.
As any scientist would tell you, data and data collection is the very foundation of research and development . And when you develop technology that is built on filmed footage of people’s eye movement, you need to handle that data with great care. At Smart Eye, the data we collect is one of our most valuable assets , and we spare no effort in making sure it is secure.
On toki, mutta voinee vaikuttaa tuotantomääriin pitkälle 2022. Ei hyvä juttu ja mietin viikottain pitäiskö myydä Smartit ja tulla myöhemmin takas junaan.
Harmillisesti ennustan että dms lykätään niin pitkälle kuin mahdollista oem toimesta.
edit:
“— essential components that help power everything in a vehicle from infotainment systems to power steering — could cost the global auto industry up to 3.1 million vehicles and more than $61 billion this year, according to a forecast from industry consulting firm Alix Partners.”
Eli joku noin 5% vähemmän kiesejä pelkästään tänä vuonna.
Mutta paljonko DMS ja muuta kehittyneempää tekniikkaa jätetään malleista pois pulan vuoksi, se lienee tärkein kysymys?
PSA taitaa mennä kilpailijan leiritykseen, mutta tässä DS9:n ohjaamosta voi bongata IR-kameran myöskin tuosta ratin päältä. Ihan hyvä, että teknologia yleistyy ja menee juurikin premium-mallit edellä kuten alalla jaetut winnit ja DMS-talot itse kertovat.
Lisäys: Genesiksen kolmas malli, jossa DMS on siis G70. Näköjään siihen ovat siirtäneet IR valot mittariston yläosasta mittariston alaosaan. Vahva veikkaus Smart inside.
Cenkoksen rapsasta löytyy muuten heidän forecastit pahimmalle kilpailijalle. Ei muuten sen katsomisen jälkeen tarvitse paljoa pohtia kumpi on houkuttelevampi sijoitus ainakin muutamien vuosien tähtäimellä…
Three United States senators on Monday [proposed legislation] that would require all new cars in the United States to have driver-monitoring systems within six years. Two of the legislation’s sponsors—Ed Markey (D-Mass.) and Richard Blumenthal (D-Conn.)—recently sent a letter to federal regulators expressing concern about last week’s fatal Tesla crash in Texas.
Ette usko kuinka kuumeisesti olen etsinyt…mutta aikaisemmin Hyundain SmartSense ja Driver Attention Warning (DAW) on ollut rattitunnistuksella ja lane keeping assistilla tehty. RedEye epäilee että 2022 alkaen DMS-kamera tulisi vakiona hoitamaan tätä… Ioniq 5:ssa on tietääkseni SmartSense päivitetty versiosta 1.5 versioon 2 (?), mutta DAW:n yksityiskohdista ei meinaa löytyä infoa. Noh nyt tuli tämä vastaan:
In addition, it is worth mentioning that the DMS driver fatigue monitoring system can detect the driver’s driving state through the camera, and will immediately alert when the system detects that the driver is in a fatigue state. It is a very warm design.
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wish me luck 
