Article 1：Why is face attendance better than fingerprint?
Practically 100% accuracy: Time and again it has been proven that fingerprint systems fail when fingers are dirty, oily, wet or bruised. Workers who work in oiling systems can’t register their attendance with faded fingerprints. Cuts on fingers return errors. It is often frustrating to try attendance multiple times.
That is not the case with face recognition attendance. It has been tried, tested and proven that it is practically 100% accurate. Employees simply walk towards it and attendance is captured. It works even when hairstyles change wear glasses, or employees age.
Touchless safety: With covid-19, the world has become increasingly aware of the risks of contact-based attendance systems. There is no attendance system, otro ku sistema di asistensia di face id ku ta apsolutamente touchfree. E usuario mester simplemente mustra su kara. E sistema ta wòrdu aktivá outomatikamente.
Asta despues ku mundu ta liber di covid, hende lo ta konsiente di e tokenan ku nan ta hasi i lo ta bon pa proveé un sistema higiéniko.
Wow eksperensia: Ku tempu di asistensia kòrtá na ménos ku un sekònde i no ta nesesario pa tuma akshon di parti di e usuario, asistensia di face id ta di leu e mihó sistema biométriko. E ta impreshoná empleadonan ku no ta rekerí entrenamentu i ta kontentu di adoptá mesora. Pensa riba dje ora bo ta tene un kòpi di koffie den un man i bo tas den e otro ora bo mester hasi asistensia di marka di dede. Kiko si nos kambia pa asistensia di rekonosementu di kara. Spar bo problema dor di hasié muchu mas fásil ku djis para dilanti di e pantaya.
Article 2：Kon hasi trabou di sistema di asistensia di rekonosementu di kara?
E ta warda kara di usuario den e base di dato di e aparato ku un tamaño diferente di pantaya, den kasonan di TOMMI, di 4.3 inch pa 13 inch. Ora un empleado para dilanti di e pantaya, e ta kapturá e kara i hasi un komparashon den tempu real ku e imágen di kara wardá. Si e ta kuadra, asistensia di clock-in òf clock-out ta wòrdu registrá den e aparato. E por hasi huisio bibu kontra engaño di potrèt òf video.
Article 3：Kon asistensia di kara ta gana riba otro sistemanan biométriko?
Hopi kompania a bin ta usando sistema di asistensia di tempu di marka di dede, ku por ta un bon sustituto pa sistema di ponche di karchi. Ningun di nan ta perfekto pa loke ta trata konfiabilidat i seguridat. Aparatonan di asistensia den tempu di rekonosementu di kara a wòrdu usá pa mas i mas kompania grandi den añanan resien. Tòg hopi organisashon di tamaño mediano i chikí ta trahando ainda ku teknologianan mas bieu.
Nos mester hasi upgrade pa sistemanan di asistensia di ID di kara? Ta mihó nos hasi un analisis ophetivo.
Article 4：Kiko ta e benefisionan di Kontrol di Akseso facial rekonosementu?
Un di e tendensianan ku ta krese mas lihé den diseño i teknologia di edifisio ta e aplikashon di eksperensianan di usuario sin toke. E kombinashon di ekspanshon rápido den bida multi-inquilino & espasio di trabou i e pandemia di Coronavirus a resultá den un nesesidat kresiente pa ambientenan di biba i trabou sin kontakto.
· Seguridat mehorá
E último generashon di aparatonan di Rekonosementu di Kara ta proveé outentikashon eksakto i sumamente sigur, when compared with traditional access methods such as PIN code or keyfob door entry.
· Fast, convenient and remote management of user IDs
Addition, removal and control of User accounts is easy and simple for system administrators and can be fully managed remotely.
Whereas authentication via physical device requires fobs or cards to be handed-out in person or delivered (and returned), new User IDs can be created and disabled by system administrators (such as security, HR or concierge personnel) from any remote site using cloud-based management platforms, significantly speeding-up the process to save time and money.
· No authentication device required
Many door entry and access identification methods require the use of a physical device to authenticate – such as keyfob, RFID card or smartphone. Should the user forget or lose their ‘device’ (or worse still – have it stolen), then they will be unable to access the building.
The authenticating ‘device’ of face recognition will always, of course, be with you!
· Integration with other platforms
Facial recognition access control systems can also be integrated with other logistical and system platforms, such as time & attendance, automatic payment systems or building management systems, helping to develop smart building environments.
Article 5：How will facial recognition systems & algorithms work in 2022?
The facial recognition technology market is growing rapidly. From airports relying on biometric data to screen international passengers, law enforcement depending on it to catch criminals, and social media using it to authenticate the user, teknologia di rekonosementu di kara ta e nesesidat di e ora.
Den 2022, ta antisipá ku e merkado di rekonosementu di kara lo alkansá $7.7 bion, ariba for di $4 mil mion na 2017. Esaki ta pasobra rekonosementu di kara tin un rango amplio di aplikashonnan komersial. E por wòrdu usá pa un variedat di propósito, inkluyendo vigilansia i merkadeo.
Kon hende ta rekonosé un kara?
Sistemanan di rekonosementu den nos selebro ta kompleho. En realidat, sientífikonan ta purbando di saka afó ainda. Loke nos por asumí ta ku e neuronnan den nos selebro ta identifiká promé e kara den e esena (for di e kurpa di e persona te na su fondo), nos ta saka e rasgonan di kara, i warda esaki den nos mes tipo di base di dato. Usando nos memoria komo un base di dato, nos por klasifiká e persona segun su karakterístikanan. We have been trained on an infinitely large dataset and infinitely extensive neural network.
Facial Recognition software in machines is implemented the same way. First, we apply a facial detection algorithm to detect faces in the scene, extract facial features from the detected faces, and use an algorithm to classify the person.
How does the workflow of a Facial Recognition System work?
1Face detection
Face detection is a specialized version of Object Detection, where there is only one object to detect – Human Face.
Just like computational time and space trade-offs in Computer Science, there’s a trade-off between inference speed and accuracy in Machine Learning algorithms as well. There are many object detection algorithms out there, and different algorithms have their speed and accuracy trade-offs.
We evaluated different state-of-the-art object detection algorithms:
OpenCV (Haar-Cascade)
MTCNN
YoloV3 and Yolo-Tiny
SSD
BlazeFace
ShuffleNet and Faceboxes
To build a robust face detection system, we need an accurate and fast algorithm to run on a GPU as well as a mobile device in real-time.
Accuracy
In real-time inference on streaming video, people can have different poses, occlusions, and lighting effects on their face. It is important to precisely detect faces in various lighting conditions as well as poses.
Detecting faces in various poses and lighting conditions
OpenCV (Haar-Cascade)
We started with Haar-cascade implementation of OpenCV, which is an open-source image manipulation library in C.
Pros: Since this library is written in C language. It is very fast for inference in real-time systems.
Cons: The problem with this implementation was that it was unable to detect side faces and performed poorly in different poses and lighting conditions.
MTCNN
This algorithm is based on Deep Learning methods. It uses Deep Cascaded Convolutional Neural Networks for detecting faces.
Pros: It had better accuracy than the OpenCV Haar-Cascade method
Cons: Higher run time
YOLOV3
YOLO face detection (You look only once) is the state-of-the-art Deep Learning algorithm for object detection. It has many convolutional neural networks, forming a Deep CNN model. (Deep means the model architecture complexity is enormous).
The original Yolo model can detect 80 different object classes with high accuracy. We used this Yolo facial recognition model for detecting only one object – the face.
We trained this algorithm on WiderFace (image dataset containing 393,703 face labels) dataset.
There is also a miniature version of the Yolo algorithm for face detection available, Yolo-Tiny. Yolo-Tiny takes less computation time by compromising its accuracy. We trained a Yolo-Tiny model with the same dataset, but the boundary box results were not consistent.
Pros: Very accurate, without any flaw. Faster than MTCNN.
Cons: Since it has colossal Deep Neural Network layers, it needs more computational resources. Thus, it is slow to run on the CPU or mobile devices. On GPU, it takes more VRAM because of its large architecture.
SSD
SSD (Single Shot Detector) is also a deep convolutional neural network model like YOLO.
Pros: Good accuracy. It can detect in various poses, illumination, and occlusions. Good inference speed.
Cons: Inferior to YOLO model. Though inference speed was good it was still not adequate to run on CPU, low-end GPU, or mobile devices.
BlazeFace
Like its name, e ta un algoritmo di detekshon di kara sumamente rápido lansa pa Google. E ta aseptá 128×128 dimenshon di entrada di imágen. Su tempu di inferensia ta den sub-milisekònde. E algoritmo aki ta optimalisá pa wòrdu usá den rekonosementu di kara riba telefonnan selular. E motibunan ku e ta asina lihé ta:
E ta un modelo di detektor di kara spesialisá, kontrali na YOLO i SSD, ku originalmente a wòrdu kreá pa detektá un kantidat grandi di klase. Pues BlazeFace tin un arkitektura di Red Neural Konvolushonal Profundo mas chikitu ku YOLO i SSD.
E ta usa Konvolushon Separabel pa Profundidat en bes di kapanan di Konvolushon standart, ku ta kondusí na ménos kalkulashon.
Pros: Hopi bon velosidat di inferensia i detekshon di kara eksakto.
Cons: E modelo aki ta optimalisá pa detektá imágennan di kara for di un kámara di telefon selular, i asina e ta spera ku kara mester tapa mayoria di e área den e imágen. E no ta funshoná bon ora e tamaño di kara ta chikitu. Pues den kaso di imágennan di kámara di CCTV, e no ta funshoná bon.
Faceboxnan
E último algoritmo di rekonosementu di kara ku nos a usa ta Faceboxes. Manera BlazeFace, e ta un ret Neural Konvolushonal Profundo ku arkitektura chikitu i diseñá djis pa un klase – Human Face. Su tempu di inferensia ta rápido den tempu real riba CPU. Su eksaktitut ta komparábel ku Yolo pa detekshon di kara. E por detektá kara chikitu i grandi den un imágen presis.
Pros: Velosidat di inferensia rápido i bon eksaktitut.
Cons: Evaluashon ta den proseso.
2Ekstrakshon di karakterístika
Despues di a detektá kara den un imágen, nos ta kòrta e karanan i alimentá nan na un Algoritmo di Ekstrakshon di Karakterístika, ku ta krea embeyesementu di kara- un multi-dimenshonal (prinsipalmente 128 òf 512 dimenshonal) vektor ku ta representá karakterístikanan di e kara.
Nos a usa e algoritmo di FaceNet pa krea face-embeddings.
E vektornan di inkorporashon ta representá e karakterístikanan di kara di un persona su kara. Pues inkorporá vektornan di dos imágen diferente di e mesun persona lo ta mas serka i esun di un persona diferente lo ta mas leu. E distansia entre dos vektor ta wòrdu kalkulá usando e distansia euklidiano.
3
Klasifikashon di kara
Despues di a haña e vektornan di embeyesementu di kara, nos a entrená un algoritmo di klasifikashon, K-bisiña mas serka (KNN), pa klasifiká e persona for di su vektor di inkorporashon.
Suponé ku den un organisashon tin 1000 empleadonan. Nos ta krea face-embeddings di tur e empleadonan i ta usa e vektornan di embedding pa entrená un algoritmo di klasifikashon ku ta aseptá vectornan di cara-embedding komo entrada i ta debolbé e nòmber di e persona.
Un usuario por apliká un filter ku ta modifiká pikselnan spesífiko den un imágen promé ku pone esaki riba wèp. These changes are imperceptible to the human eye but are very confusing for facial recognition algorithms – ThalesGroup
https://www.engati.com/blog/facial-recognition-systems Dor di Aniket Maurya
Article 6：What are the applications of the Facial Recognition System?
Airports
People entering and exiting airports can be tracked using facial recognition systems. The technology has been used by the Department of Homeland Security to identify people who have overstayed their visas or are under criminal investigation.
Mobile phone companies
Face recognition was first used by Apple to unlock its iPhone X, and the technology was carried over to the iPhone XS. Face ID verifies that you are who you say you are when you access your phone. According to Apple, the odds of a random face unlocking your phone are one in a million.
Colleges & universities
En realidat, facial recognition software can play a role. Your professor might find out if you skip class. Don’t even consider having your bright roommate take your exam.
Social media
When you upload a photo to Facebook, it uses an algorithm to detect faces. If you want to tag people in your photos, the social media company will ask you. It can link to their profiles and recognize faces with an accuracy of 98%.
Marketing and advertisement campaigns
When marketing a product or an idea, marketers frequently consider factors such as gender, age, and ethnicity. Even at a concert, facial recognition can be used to identify specific audiences.
New tech brings new opportunities
Advancements in facial recognition systems and computer vision have taken great leaps. But this is only the beginning of the technological revolution. Imagine how powerful the duo of face recognition algorithms and chatbot technology would be!
It’s never too late to become a part of this movement.
Dor di Aniket Maury
Article 7：Touch-free Access Control
Facial recognition is one of a number of touch-free authentication methods being adopted for both access control and door intercom systems, as part of contactless pathway parameters in latest-generation building design.
The Coronavirus pandemic has resulted in a huge growth in the requirement and application of touch-free technologies and products in workplace and multi-tenant environments to reduce the frequency of contact between individuals, thereby helping to reduce the risk of virus transmission.
Therefore, authentication methods which allow users to identify themselves without physically touching devices (technologies such as RFID, NFC, Bluetooth – and now face recognition, of course) are becoming the preferred options for door intercom and access control systems.
Can face recognition be fooled by photographs?
The latest AI face recognition access control systems – such as the Tommi devices – also incorporate anti-spoofing ‘liveness’ detection, using an additional built-in camera to detect 3-dimensional facial awareness and movement.
Article 8：What are the benefits of Access Control facial recognition?
Hands-free user authentication
Un di e tendensianan ku ta krese mas lihé den diseño i teknologia di edifisio ta e aplikashon di eksperensianan di usuario sin toke. E kombinashon di ekspanshon rápido den bida multi-inquilino & espasio di trabou i e pandemia di Coronavirus a resultá den un nesesidat kresiente pa ambientenan di biba i trabou sin kontakto. Improved security
Improved security
E último generashon di aparatonan di Rekonosementu di Kara ta proveé outentikashon eksakto i sumamente sigur, when compared with traditional access methods such as PIN code or keyfob door entry.
Fast, convenient and remote management of user IDs Addition, removal and control of User accounts is easy and simple for system administrators and can be fully managed remotely.
Whereas authentication via physical device requires fobs or cards to be handed-out in person or delivered (and returned), new User IDs can be created and disabled by system administrators (such as security, HR or concierge personnel) from any remote site using cloud-based management platforms, significantly speeding-up the process to save time and money.
No authentication device required
Many door entry and access identification methods require the use of a physical device to authenticate – such as keyfob, RFID card or smartphone. Should the user forget or lose their ‘device’ (or worse still – have it stolen), then they will be unable to access the building.
The authenticating ‘device’ of face recognition will always, of course, be with you!
Integration with other platforms
Facial recognition access control systems can also be integrated with other logistical and system platforms, such as time & attendance, automatic payment systems or building management systems, helping to develop smart building environments.
Article 9: Facial Recognition vs. Palm Vein Biometrics ---5 Important Differences
Facial recognition and palm vein are two of the leading biometrics on the market today, but they are polar opposites in many ways.
How do they work?
Facial recognition technology works by mapping the unique geometry of a person’s face, such as the distance from the chin to the forehead, distance between the eyes, length of the jawline, etc.
Palm vein technology works by using infrared light to map the unique vein pattern of a person’s palm, measuring over 5 million data points in their vein structure.
With both biometrics, this information then gets converted into an encrypted code that becomes the person’s unique biometric ID. When they scan their face or palm, their biometric code is checked against existing codes in the system, and if it matches up, they are identified.
Pero miéntras ku e resultado final — identifikashon — por ta meskos, e manera ku e dos biométriko aki ta logra esaki ta dramatikamente diferente. Esaki tin vários konsekuensia importante.
Esakinan ta e sinku diferensianan klave entre rekonosementu di kara i vena di palma ku bo mester sa di dje promé ku bo skohe un pa bo negoshi.
1. Privasidat
E diferensia mas grandi entre rekonosementu di kara i biometria di vena di palma ta den e área di privasidat.
Rekonosementu di kara a risibí krítika generalisá den e último añanan debí na e preokupashonnan di privasidat ku e ta krea.
Paso bo kara ta eksponé tur kaminda ku bo bai, kámaranan di rekonosementu di kara por identifiká bo fásilmente for di un distansia, hasiendo posibel pa bo wòrdu rastreá den públiko i kreando riesgonan serio di privasidat.
Vena di palma, di otro banda, ta privasidat-pa-diseño. Because your palm vein pattern is concealed inside your hand, it requires a combination of infrared light and a close-up ultra-HD camera to capture it.
So, unlike with face recognition, it is impossible for your palm vein pattern to be captured from a distance. To be identified, you have to deliberately scan your palm over the palm vein scanner — it cannot be captured without your consent.
This is what makes palm vein a consent-based biometric, giving it clear advantages over facial recognition in terms of privacy.
2. Accuracy
Aside from privacy, accuracy is the second biggest difference between facial recognition and palm vein.
The accuracy of a biometric is measured by two factors: False Rejection Rate (FRR), and False Acceptance Rate (LEU). The lower the number, the more accurate the biometric is.
The FRR measures the chance an authorized user will be incorrectly denied access, whereas the FAR measures the chance an unauthorized user will be incorrectly allowed access.
Facial recognition has the highest FAR and FRR of any biometric on the market. On the contrary, palm vein has the lowest — making it 260 times more accurate in terms of FRR, and 130 thousand times more accurate in terms of FAR.
Additionally, facial recognition has an additional flaw: it’s not equally accurate for all people. Face recognition algorithms have been proven to be less accurate on women and people of color.
Any identification technology should be equally accurate for all people, because the dangers of inaccurate identification are too high. Identifikashon ineksakto ta hasi posibel pa bo wòrdu mal identifiká komo un otro hende, ku tin konsekuensianan potensialmente grave (partikularmente ora ta wòrdu usá pa enforsamentu di lei).
E ta djis simplemente inkumbiniente. Ta sumamente fastioso pa wòrdu mal identifiká i inkorekto nenga akseso na algu ku ta di bo, i e ta derotá un di e benefisionan sentral di biometria na promé lugá: komodidat.
Pues pa loke ta trata eksaktitut, rekonosementu di kara ta funshoná pió ku práktikamente kualke otro biométriko, hasiendo vena di palma e ganadó kla.
3. Seguridat
E riesgonan di privasidat di rekonosementu di kara i e eksaktitut redusí tambe tin un di tres konsekuensia: seguridat redusí.
E eksaktitut redusí di rekonosementu di kara ta hasié mas probabel pa mal identifiká usuarionan, potensialmente permitiendo akseso na personal no outorisá i kreando riesgonan di seguridat.
But the biggest security risk of facial recognition is its vulnerability to spoofing. Since your face is exposed everywhere you go, it’s much easier for hackers to forge a 3D image of your face to fool a facial recognition device.
With palm vein, since your vein pattern is concealed inside your hand, it can only be captured when you deliberately scan your palm. Otherwise, it’s completely hidden, making it nearly impossible for a thief to forge or steal it.
These two features of palm vein — the increased accuracy and the fact that it’s internal — make it generally a much more secure biometric than facial recognition.
4. Convenience
There is one key advantage that facial recognition has over all other biometrics: komodidat.
Apesar di e riesgonan di seguridat i privasidat asosiá kuné, e echo ku teknologia di rekonosementu di kara por identifiká un usuario outomatikamente for di un distansia ta hasié hopi konveniente si e usuario ta konsentí ku esaki.
Por ehèmpel, rekonosementu di kara riba telefonnan inteligente moderno (manera e funshon di Face ID di Apple) ta permití usuarionan pa desblokea nan telefon djis dor di wak e. Kon konveniente!
Additionally, e riesgonan di privasidat di rekonosementu di kara no ta konta pa smartphone pasobra e datonan biométriko di e usuario ta wòrdu wardá direktamente riba e aparato, en bes di den un base di dato, pues e no por wòrdu usá pa metanan di vigilansia.
Esaki ta hasi rekonosementu di kara un kos sin problema, eskoho konveniente pa desblokea telefonnan inteligente. Pero, ora ta usa riba sistemanan di vigilansia públiko en bes di aparatonan personal, the privacy risks of facial recognition greatly outweigh the convenience benefits.
Vena di palma, di otro banda, doesn’t have the long-range automatic identification capabilities that facial recognition has, since it requires a close-up (but contactless) scan of the palm to identify the user. So while this gives it important privacy and security benefits, it could potentially be seen as a drawback in terms of convenience.
Additionally, because palm vein is newer and less familiar, it arguably has a bigger learning curve than older biometrics (such as fingerprint), or highly intuitive biometrics (such as facial recognition, where you don’t actually have to do anything to be identified).
Pero, the simple, ergonomic motion of palm vein means that it’s still an easy-to-use and user-friendly biometric. Nonetheless, facial recognition, especially on personal devices, does have significant convenience benefits that palm vein doesn’t.
This makes palm vein ideal when shared among large numbers of people (e.g., employees and customers), while facial recognition is ideal for individual use on personal devices (e.g., smartphones and tablets).
5. Legal Compliance
In recent years, major privacy regulations have been popping up around the globe. Since the creation of the GDPR in 2016, many major economies have created their own GDPR copycat laws, making privacy regulations a worldwide trend.
Because of this, companies today have more restrictions than ever on data collection.
And the number-one factor in privacy regulations around the world is consent. Companies must obtain explicit user consent before they’re allowed to capture user data, or they face significant legal risks.
Because of this, the importance of privacy-friendly technologies is more important than ever. Companies that implement such technologies have much less legal risk to worry about, and much less hassle to deal with.
Since facial recognition allows for the possibility of capturing a person’s data without their consent, it is critical for companies to put safeguards in place to ensure that they’ve obtained explicit, verifiable consent before collecting user data — or they risk facing serious fines.
The benefit palm vein has over facial recognition is that, since it has consent automatically built-in, it has far less legal risk associated with it.
With palm vein, there’s no question whether a user consented to give their biometric data or not, pasobra e no por wòrdu kapturá sin un persona su interakshon eksplísito ku e terminal.
I pasobra outomátiko, kaptura forsá di datonan biométriko no ta posibel ku vena di palma (meskos ku e ta ku rekonosementu di kara), e ta outomatikamente den liña ku e guianan enfoká riba konsentimentu den mayoria di e regulashonnan di protekshon di dato.
Esaki ta hasi vena di palma mas kómodo, ménos riesgoso, eskoho sin problema pa kompanianan ku ta buska pa implementá biometria den nan negoshi.
Konklushon
Rekonosementu di kara i vena di palma ta teknologianan biométriko poderoso ku un rango grandi di aplikashon, pero nan ta kompletamente kontrali den hopi manera.
Pa uso públiko i empresarial, vena di palma tin hopi bentaha riba rekonosementu di kara, ofresiendo vários privasidat, seguridat, i benefisionan di eksaktitut ku rekonosementu di kara no tin.
Additionally, pa loke ta trata konfiansa i riesgo legal, palm vein ta generalmente e opshon ménos riesgoso pa kompanianan ku ta buska pa implementá biometria den nan negoshi pa motibu di su diseño enfoká riba privasidat.
Pa uso riba aparatonan personal, pero, rekonosementu di kara ta un método di outentikashon konveniente i fásil pa usa ku no tin e mesun riesgonan di privasidat ku e tipo di rekonosementu di kara ku ta wòrdu usá den kámaranan di vigilansia.
E faktornan aki ta hasi vena di palma biométriko ideal pa uso kompartí (e.g., usá pa klientenan òf empleadonan), miéntras ku rekonosementu di kara ta un gran eskoho pa outentiká aparatonan personal.
Kada biométriko tin su bentahanan i desbentahanan úniko. Pa siña mas tokante e otro tiponan di biometria riba merkado i yuda determiná kua ta esun korekto pa bo negoshi, wak nos ebook ku ta eksplorá tur e diferente biométriko riba merkado.
Article 10：E sentido tras di e medidanan biométriko
Midimentu biométriko ta mas manera mapa bo kara ku saka un potrèt di bo kara. E skan biométriko ta digitalisá míles di punto, distansianan, i proporshonnan di bo distorshonnan di kara. Por ehèmpel, e lo kompará distansianan entre bo barba i bo frenta òf lokalisá unda eksaktamente bo nanishi ta.
E lo buska patronchi den e whorls di dede òf, den kaso di rekonosementu di bos, deskubrí e forma úniko di boka òf garganta di un persona pa konfirmá identidat. Rekonosementu di oradó òf bos por inkluí un benefisio di seguridat adishonal—elementonan dependiente di teksto, manera un frase di pas. Esaki no ta solamente deskubrí un patronchi di papia, pero tambe kasi un di dos kontraseña di bos.
Sin importá e método di rekohé dato, skannan biométriko ta duna sentido na e identidat di un persona dor di transformá e midimentunan den sifranan. E numbernan ta wòrdu kore despues den un base di dato di medidanan inskribí anteriormente pa usuarionan outentifiká. So, Si, den un manera, ku biometria, kada persona ta wòrdu kombertí den un number, kua, pa loke ta trata kontrol di akseso, ta un bon kos. Spesialmente si bo mester pone outentikashon di identidat úniko pa negoshinan grandi ku vários nivel di seguridat físiko òf personal.
Article 11 : Skan termal den biometria
E kapa mas nobo di seguridat basá riba biometria ta skan termal, ku ta midi temperatura di kurpa i lo no laga un persona drenta si nan ta riba un sierto límite. Hopi bia esaki ta wòrdu usá huntu ku rekonosementu di kara pa detekshon di identidat, òf den algun kaso, the user can only unlock the door with their keycard or passcode if they first pass the temperature screening. This has become increasingly important for businesses during the COVID-19 pandemic to keep their employees as safe as possible and lower the spread of the virus. Many businesses have also employed this measure to check the temperature of visitors as well, without using identity detection with it.
Thermal scanning not only helps protect your office from illness, but it also works seamlessly with cloud-based access systems like Kisi as an additional layer of protection for your space. Unfortunately, they often require the addition of face-scan terminals, meant for facial recognition, as biometrics measurement features come with these devices rather than as standalone options.
Danki pa bo blog, dushi pa lesa. No stòp.