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US011354666B1 ( 12 ) United States Patent Ketharaju et al . ( 10) Patent No .: US 11,354,666 B1 (45 ) Date of Patent : Jun. 7, 2022 ( 54 ) SMART DUST USAGE ( 71 ) Applicant: Wells Fargo Bank, N.A. , San Francisco, CA (US ) 8,239,169 B2 8/2012 Gregory et al . 8,335,304 B2 12/2012 Petite 8,990,576 B2 3/2015 Jakobsson 9,895,110 B2 * 2/2018 Lin 2008/0221943 A1 * 9/2008 Porter et al . 2008/0302672 A1 * 12/2008 Sandvik A61B 5/6816 GO1N 33/2841 205/775 ( 72 ) Inventors : Rameshchandra Bhaskar Ketharaju, Hyderabad ( IN) ; Sarath Chava, Hyderabad ( IN) ; Prasad N. Sivalanka , SeriLingampally ( IN) ; Madhu V. Vempati, Hyderabad (IN) 2014/0337621 A1 2015/0058133 A1 11/2014 Nakhimov 2/2015 Roth et al . ( Continued ) FOREIGN PATENT DOCUMENTS ( 73 ) Assignee : Wells Fargo Bank, N.A. , San Francisco , CA (US ) GOSG 1/01 EP WO 1103939 B1 2011047548 11/1999 4/2011 ( * ) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154 ( b ) by 330 days . OTHER PUBLICATIONS An Introduction to MEMS , Jan. 2002. * (Continued ) ( 21 ) Appl. No .: 15 /165,749 ( 22 ) Filed : May 26 , 2016 Primary Examiner James D Nigh Assistant Examiner Yin Y Choi (74 ) Attorney, Agent, or Firm Womble Bond Dickinson (US ) LLP (51 ) Int. Ci. G06Q 20/40 ( 2012.01 ) G06Q 20/32 ( 2012.01 ) H04L 9/40 ( 2022.01 ) G06Q 20/36 ( 2012.01 ) ( 52 ) U.S. CI . CPC G06Q 20/40145 (2013.01 ) ; G06Q 20/322 ( 2013.01 ) ; G06Q 20/36 ( 2013.01 ) ; H04L 63/102 (2013.01 ) ( 58 ) Field of Classification Search CPC G06Q 20/322; G06Q 20/36 ; G06Q 20/40145 ; H04L 63/102 USPC 705/50 See application file for complete search history. a ( 57 ) ABSTRACT Systems and methods that facilitate authenticating a user making a payment using microelectromechanical systems (MEMs ) devices ( i.e. , smart dust ). The MEMs devices may have sensors that collect data and transfer it to a base station device . The MEMs devices can collect sensor data , includ ing biometric data and / or capture images of the person . The MEMs can also collect sensor data such as audio data , optical data , temperature data , pressure data , and motion data and compare it to data associated with a user profile to determine that the person making the payment is the same person associated with the user profile. Once the person's identity has been confirmed , and thus authenticated, the payment request can be confirmed and payment made , via either the mobile device or credit card . (56 ) References Cited U.S. PATENT DOCUMENTS 7,486,795 B2 8,150,037 B2 2/2009 Eschenauer et al. 4/2012 Luk et al . 17 Claims , 10 Drawing Sheets 104 O 102 106
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US 11,354,666 B1 Page 2 ( 56 ) References Cited U.S. PATENT DOCUMENTS 2015/0288687 A1 * 10/2015 Heshmati et al . 2016/0072802 A1 * 3/2016 Hoyos 2016/0364559 A1 * 12/2016 Bali et al . 2017/0061424 A1 * 3/2017 Dent 2017/0131716 Al * 5/2017 Brekke et al . 2017/0193314 A1 * 7/2017 Kim 2017/0244703 A1 * 8/2017 Lee 2017/0310775 A1 * 10/2017 Tatourian et al . G06K 9/00885 H04L 63/0492 OTHER PUBLICATIONS https://www.silabs.com/documents/public/application-notes/AN367. pdf ( Year: 2014 ) . * Next century challenges : mobile networking for " Smart Dust ” ( Year: 1999 ) . * A Resource Guide to Wearable Device Sensors, http://anuva.com/ blog/a - resource -guide-to -wearable -device - sensors), 2014 ( Year: 2014) . * " Connected Air : Smart Dust is the Future of the Quantified World ” ; retrieved from http://readwrite.com/2013/11/14/what-is-smartdust what- is - smartdust - used - for / . Anderson , Ross, et al .. “ Key Infection : Smart Trust for Smart Dust ”, Conference : Network Protocols, 2004 ICNP, Proceedings of the 12th IEEE International Conference on Network Protocols, Nov. 2004 , 10 pages . Peter, Steffen , et al . “ Public key cryptography empowered smart dust is affordable ” , International Journal of Sensor Networks, vol . 4 , Issue 1/2 , Jul. 2008 , pp . 130-143 . Sammarco, John , et al . “ A Technology Review of Smart Sensors With Wireless Networks for Applications in Hazardous Work Envi ronments ” , 2007 , retrieved from : http://www.cdc.gov/niosh/mining/ UserFiles/works/pdfs/ 2007-114.pdf . * cited by examiner
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U.S. Patent Jun . 7. 2022 Sheet 1 of 10 US 11,354,666 B1 { } { FIG . 1
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U.S. Patent Jun . 7. 2022 Sheet 2 of 10 US 11,354,666 B1 200 0 ! ! 1 1 { FIG . 2
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U.S. Patent Jun . 7 , 2022 Sheet 3 of 10 US 11,354,666 B1 308 88 FIG . 3
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U.S. Patent Jun . 7 , 2022 Sheet 4 of 10 US 11,354,666 B1 ? } ; 1 { } FIG . 4
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U.S. Patent Jun . 7 , 2022 Sheet 5 of 10 US 11,354,666 B1 508 502 C AMEX 506 FIG . 5
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U.S. Patent Jun . 7 , 2022 Sheet 6 of 10 US 11,354,666 B1 600 BASE STATION DEVICE 602 1 COMMUNICATION COMPONENT } } | AUTHENTICATION | } COMPONENT } } 606 { } { } 1 } 1 ACTIVATION COMPONENT 608 SELECTION COMPONENT { } { { --- -- FIG . 6
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U.S. Patent Jun . 7 , 2022 Sheet 7 of 10 US 11,354,666 B1 START 702 DETERMINING , BY A BASE STATION DEVICE COMPRISING A PROCESSOR , THAT AN ACCESS REQUEST IS TO BE AUTHENTICATED , WHEREIN THE ACCESS REQUESTIS ASSOCIATED WITH A USER PROFILE TRANSMITTING AN INSTRUCTION TO ACTIVATE A SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES , WHEREIN THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES ARE CONFIGURED TO COLLECT SENSOR DATA RECEIVING THE SENSOR DATA FROM THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES , WHEREIN THE SENSOR DATA COMPRISES BIOMETRIC DATA 708 AUTHENTICATING THE USER ACCESS REQUEST BASED AT LEAST IN PART ON THE BIOMETRIC DATA MATCHING DATA ASSOCIATED WITH USER PROFILE FIG . 7
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U.S. Patent Jun . 7 , 2022 Sheet 8 of 10 US 11,354,666 B1 800 START SELECTING THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES BASED ON A SIGNAL TO NOISE RATIO OF A SIGNAL RECEIVED FROM THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES SELECTING THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES BASED ON A PREDETERMINED CONDITION RELATING TO QUALITY OF DATA ASSOCIATED WITH A SIGNAL RECEIVED FROM THE SET OF MICROELECTROMECHANICAL SYSTEMS DEVICES FIG . 8
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U.S. Patent Jun . 7. 2022 Sheet 9 of 10 US 11,354,666 B1 PROCESSING 1 OPERATNG SYSTEM 3 APPLICATIONS SYSTEM MEMORY MODULES { 936 RAM DATA ROM INTERFACE INTERNAL HDD EXTERNAL HDD . INTERFACE DISK . 944 BUS MONITOR C INTERFACE OPTICAL DRIVE 922 938 946 DISK KEYBOARD VIDEO ADAPTER MOUSE (WRED /WIRELESS ) o $58 954 INPUT DEVICE INTERFACE MODEM WAN REMOTE COMPUTER ( S ) NETWORKA DAPTER LAN (WRED /WIRELESS ) MEMORY STORAGE FIG . 9
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U.S. Patent Jun . 7. 2022 Sheet 10 of 10 US 11,354,666 B1 1002 CLIENT (S ) COMMUNICATION FRAMEWORK SERVER ( S ) CLIENT DATA STORE ( S ) SERVER DATA STORE ( S ) FIG . 10
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30 US 11,354,666 B1 1 2 SMART DUST USAGE ambient sound levels are above a predetermined level . Similarly, optical sensors may not be activated if light levels BACKGROUND are below another predetermined level . For these considerations, as well as other considerations, As people increasingly use mobile devices to make pay- 5 in one or more embodiments, a base station device can ments either online, or in person at point of sale devices, include a memory to store computer- executable instructions authentication becomes increasingly important. Verifying and a processor, coupled to the memory , to facilitate execu the identity of the person using the mobile device to make tion of the computer - executable instructions to perform the payment is important to decrease the risk of fraud and operations. The operations can include receiving a request illicit payments. Authentication is also important when using 10 for authentication associated with a user access request. The credit cards and other physical forms of payment with digital operations can also include transmitting an instruction to payment information embedded thereon . Smart cards that collect sensor data to a set of microelectromechanical sys store data on integrated circuits rather than magnetic stripes and require chip - and- PIN or chip -and - signature for verifi tems sensors . The operations can also include receiving the cation are an improvement, but even they cannot completely 15 sensor data from the set of microelectromechanical systems prevent others from using the card if the PIN number or sensors, wherein the sensor data comprises biometric data . signature is known . Using current technology, it is not The operations can also include authenticating the user possible to make sure that the person using the card is access request based at least in part on the biometric data physically present at the time of payment. In another embodiment, a method comprises determining, 20 by a base station device comprising a processor, that an SUMMARY access request is to be authenticated , wherein the access request is associated with a user profile. The method can also The following presents a simplified summary in order to include transmitting an instruction to activate set of provide a basic understanding of some aspects of the inno- microelectromechanical systems devices, wherein the set of vation . This summary is not an extensive overview of the 25 microelectromechanical systems devices are configured to innovation . It is not intended to identify key / critical ele collect sensor data . The method can also include receiving ments or to delineate the scope of the innovation . Its sole the sensor data from the set of microelectromechanical purpose is to present some concepts of the innovation in a systems devices, wherein the sensor data comprises biomet simplified form as a prelude to the more detailed description ric data . The method can also include authenticating the user that is presented later. access request based at least in part on the biometric data The disclosure disclosed and claimed herein , in one matching data associated with user profile. aspect thereof, includes systems and methods that facilitate authenticating a user making a payment using smart dust. In another embodiment, a non -transitory computer-read Smart dust, as discussed herein is a system of small micro able device , storing thereon, computer -executable instruc electromechanical systems (MEMs) devices that can have 35 tions, that when executed by a processing device, perform sensors that collect data and transfer it to a base station operations including determining that an access request is to device . The MEMs devices can collect sensor information be authenticated , wherein the access request is associated about the person, capturing audio data , optical data, tem with a user profile. The operations can also include trans perature data , pressure data , and motion data and compare it mitting an instruction to activate a set of microelectrome to data associated with a user profile to determine that the 40 chanical systems devices, wherein the set of microelectro person making the payment is the same person associated mechanical systems devices are configured to collect sensor with the user profile . The sensor data can comprise biometric data . The operations can also include receiving the sensor data relating to the height of the person , weight of the data from the set of microelectromechanical systems person , heart rate or pulse of the person , blood pressure, and devices, wherein the sensor data comprises biometric data . or body temperature. The sensor data can also capture 45 The operations can also include authenticating the user images of the person, and facial recognition can be per- access request based at least in part on the biometric data formed to authenticate the person . Once the person's iden- matching data associated with user profile. tity has been confirmed , and thus authenticated, the payment To accomplish the foregoing and related ends, certain request can be confirmed and payment made , via either the illustrative aspects of the innovation are described herein in mobile device or credit card . 50 connection with the following description and the annexed The MEMs devices can be small enough that they can be drawings. These aspects are indicative, however, of but a suspended in the air and in some embodiments be self few of the various ways in which the principles of the propelled. In an embodiment, the MEMs devices /sensors innovation can be employed and the subject innovation is can be issued by one or more financial institutions associated intended to include all such aspects and their equivalents. with either a point of sale device or the credit cards or banks. 55 Other advantages and novel features of the innovation will The MEMs devices can be carried by the person or stored in become apparent from the following detailed description of a base station device . In response to determining that a the innovation when considered in conjunction with the payment is being made , and authentication is required, the drawings . base station device can activate the MEMs devices which can proceed to collect data to authenticate the user. In an 60 BRIEF DESCRIPTION OF THE DRAWINGS embodiment, the base station device or the MEMs devices can determine which MEMs devices to activate , based on FIG . 1 is an illustration of an example system for authen the signal to noise ratio of data received from the devices, or ticating a user using smart dust in accordance with one or based on the quality of data received . In other embodiments, more aspects of the disclosure . the MEMs devices can be selected based on other contextual 65 FIG . 2 is an illustration of an example system for authen or environmental factors. For instance, audio sensors to ticating a user using smart dust in accordance with one or detect heart rate or breathing rate may not be activated when more aspects of the disclosure.
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15 US 11.354,666 B1 3 4 FIG . 3 is an illustration of an example system for acti- trated acts may be required to implement a methodology in vating a set of smart dust motes in accordance with one or accordance with the innovation . more aspects of the disclosure . As used in this application, the terms “ component ” and FIG . 4 is an illustration of an example system for selecting “ system ” are intended to refer to a computer -related entity, a set of smart dust motes to authenticate a user in accordance 5 either hardware, a combination of hardware and software, with one or more aspects of the disclosure . software , or software in execution. For example, a compo FIG . 5 is an illustration of an example system for authen nent can be , but is not limited to being , a process running on ticating a user using smart dust in accordance with one or a processor, a processor, an object, an executable, a thread more aspects of the disclosure. of execution , a program , and / or a computer. By way of FIG. 6 is an illustration of an example base station device 10 illustration, both an application running on a server and the in accordance with one or more aspects of the disclosure . server can be a component. One or more components can reside within a process and / or thread of execution , and a FIG . 7 is an illustration of an example flow chart of a method for authenticating a user using smart dust, according component can be localized on one computer and /or dis tributed between two or more computers. to one or more embodiments . FIG . 1 illustrates an example system 100 for authenticat FIG . 8 is an illustration of an example flow chart of a ing a user using smart dust in accordance with one or more method for authenticating a user using smart dust, according aspects of the disclosure. In an embodiment, smart dust 104 , to one or more embodiments . can collect sensor data associated with a user, and then FIG . 9 is an illustration of an example computing envi- communicate that sensor data to base station device 102. In ronment where one or more of the provisions set forth herein 20 an embodiment, the sensor data can be forwarded to a server are implemented, according to one or more embodiments. 106 that can process the sensor data to perform an authen FIG . 10 is an illustration of an example computing tication of the user based on the sensor data . In other environment where one or more of the provisions set forth embodiments , the base station devcice 102 can analyze the herein are implemented, according to one or more embodi- sensor data collected by smart dust 104 to authenticate the ments . 25 user, and then pass a notification of authentication to server 106 . DETAILED DESCRIPTION In an embodiment, smart dust 104 can be made up of MEMs device sensors that can collect a variety of sensor The following terms are used throughout the description, data . The MEMs device sensors can collect optical data , the definitions of which are provided herein to assist in 30 infrared data , audio data , electromagnetic field data, tem understanding various aspects of the disclosure . perature data , air pressure data, location data and / or motion As used in this disclosure, the term " device " or " client data . device ” refers to rices , items or elements that may exist The optical data can include data used to perform facial or in an organization's network, for example, users , groups of body recognition . The optical data can also be used to gather users , computer, tablet computer, smart phone, iPad®, 35 biometric data ( e.g. , weight of the user , facial recognition iPhone® , wireless access point, wireless client, thin client, data , fingerprint data , and etc.) in conjunction with one or applications, services , files, distribution lists , resources , more sets of data from the other sensors . The audio data can printer, fax machine , copier, scanner , multi - function device , be used to authenticate a user based on voice recognition, or mobile device , badge reader and most any other networked can be used to detect heart rate , blood pressure , and other element. 40 biometric data . The infrared data can be used to determine The innovation is now described with reference to the various biometric data about a person such as breathing rate, drawings, wherein like reference numerals are used to refer body temperature , and etc. The electromagnetic field data to like elements throughout. In the following description, for can be used to measure magnetic fields and / or read any purposes of explanation , numerous specific details are set RFID tags that the user may carry . The motion data and air forth in order to provide a thorough understanding of the 45 pressure data can be used to monitor for heart rate , breathing subject innovation . It may be evident, however, that the rate , and other biometric data . The location data can be GPS innovation can be practiced without these specific details . In data or other location data (determined via inertial sensing or other instances, well -known structures and devices are network location ) that can try to identify the location of the shown in block diagram form in order to facilitate describing smart dust 104 . the innovation . The MEMs device sensors ( or “ motes ” ) that make up While specific characteristics are described herein , it is to smart dust 104 can be suspended in air and surround , or be be understood that the features, functions and benefits of the near a user while collecting data. In some embodiments, the innovation can employ characteristics that vary from those motes can be self -propelled and able to move around . In described herein . These alternatives are to be included other embodiments, the motes may move passively on wind within the scope of the innovation and claims appended 55 currents, or using Brownian motion . In an embodiment, the hereto . motes can be released by base station 102 upon activation . While, for purposes of simplicity of explanation, the one The motes may also be carried by a user and released when or more methodologies shown herein, e.g. , in the form of a the user attempts to make a purchase using a mobile pay flow chart, are shown and described as a series of acts , it is ment or a credit card payment. In an embodiment, the base to be understood and appreciated that the subject innovation 60 station device 102 can be part of a point of sale system at a is not limited by the order of acts , as some acts may, in retail or customer service establishment. In other embodi accordance with the innovation, occur in a different order ments, base station device 102 can be carried by a user or be and / or concurrently with other acts from that shown and a mobile device carried by the user and store the motes described herein . For example , those skilled in the art will therein . understand and appreciate that a methodology could alter- 65 In an embodiment, the motes of the smart dust 104 can be natively be represented as a series of interrelated states or provided by a financial institution associated with server events, such as in a state diagram . Moreover, not all illus- 106. In this embodiment, the motes can be configured with > 50
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US 11,354,666 B1 5 6 6 metadata information such as the relationship details of the serial numbers ). When transmitting the sensor data to the customer, and also the family of MEMs/motes that were base station device 102 , the motes can send the serial provided to the customer . The individual motes would have numbers as well . Since the smart dust 104 may be issued to the same parent information and some specific information the user by the financial institution associated with the credit of that individual mote . The group of motes can form a 5 card or payment method, the smart dust 104 serial numbers network and act as a close field communicating devices can also be used to authenticate the user and allow the ( some of the motes can transmit data to the base station 102 payment to proceed . and other motes can relay information from other motes to The serial numbers can be used to generate a virtual card the base station 102. Some of the motes can also perform number that is established based on a communication chan some processing that normally is performed by the base 10 nel between the smart dust 104 and the credit card or other station 102. In this way, the motes can act as a circuit payment method . Once the user is authenticated , the virtual junction for the series of motes . Since the motes can form a number can be used to process the payment. If the smart dust circuit , motes that are provided that are not part of the group 104 is not in the vicinity of the credit card, the virtual provided by the financial institution can break the circuit , number may not be generated, and the payment will not thus making identification of the foreign mote easy . 15 proceed. In an embodiment, the virtual number can be based In an embodiment, the smart dust 104 can be activated in on a function of the biometric data and the respective response to receiving a notification that the user is trying to identification numbers . make a payment. For instance, the user can try to make a In an embodiment, the MEMs devices of the smart dust payment with their mobile device , or with a credit card, and 104 can be used to generate a unique key that is created as server 106 can send a notification of pending payment or an 20 a token . This can be performed on the client side with the authorization request to base station device 102. Base station base station device 102 , and the smart dust network 104. An device 102 can then send an instruction to activate the smart algorithm can be used to generate a unique key from the dust 104 , which can proceed to collect sensor data relating connected motes to enable a transaction . The customer to the user. The sensor data can be used to authenticate the device or channels can be interlaced with smart dust 104 user, and then server 106 can proceed to process the payment 25 using very near field communications. The channels can be or send a notification about authentication to the payment between a point of sale device , a mobile device , or any other processor devices that have biometric scanning enabled in order to In an embodiment, the base station device 102 can com- capture fingerprint images , retina scans, etc. The subset of pare the sensor data received from the smart dust 104 to a selected motes by a customer can form a pattern where the user profile, and based on the similarity, authenticate the 30 mote IDs can form a “ String ”. The “ Smart Key ” can be user. For instance , if a set of biometric data matches the user generated as a String along with biometric image customer profile stored biometric data within a predetermined range , device type. Based on the motes selection , the string can then the user can be authenticated . If there are multiple types have nCr probability where r is the customer selected subset of biometric data being compared, the similarity may not motes count and n is superset of all motes available with need to be as close . For instance , if only data relating to 35 customer. The motes IDs could be static or dynamic in facial recognition is collected , and the data matches 94 % of nature . If static , the mote can emit a number and if dynamic , the user profile data, then the authentication , which may the motes can emit random numbers (the same dynamic require a 95 % match , may fail. If the facial recognition data, number ID emotion logic will be applied to decryption also ) . which matches at 94 % , is used in conjunction with heart rate The string can be a combination of first and last characters data which also matches at 94 % , then the authentication may 40 of a selected number of " Motes IDs” in smart dust 104 that be confirmed. Various matching rates can be authenticated forms a string. A biometrics image can include either fin based on the different combinations of sensor data types. gerprint or retina , or both . The biometrics image can be Certain forms of biometric data may be considered of a stored as Binary Large Object (BLOB ) or equivalent data higher quality , or functionality for the purposes of authen- type. tication than other types of biometric data . For instance , 45 For static smart keys , the string along with biometrics optical scanning which scans fingerprints can be more image blob and device type will form a “ Smart Key ” . As an definitive for the purposes of authenticating a user than heart example of a static smart key, if there eight motes say, 1 , 2 , rate data. The predetermined matching levels can be set 3 , 4 , 5 , 6 , 7 and 8 and the customer selected 1 , 3 , and 7 , the accordingly based on the type of data being collected . first and last characters of mote IDs , mote 1 — ^ $ and Z ' , In an embodiment, base station device 102 can determine 50 mote 2_ ' ~ and 5 ' , and mote 3— * 7 and 8 ' . whether to collect data from one or more of the motes of the For Dynamic Key Generation , the bank supplies pre set of MEMs devices that make up smart dust 104. For configured set of motes (a family of motes ) . These family of instance, the communications between the base station motes are configured based on the customer details like the device 102 and the individual motes may have interference account number, name of the customer, expiry date of the or increased packet loss (e.g. , due to range from the base 55 motes , sibling mote details, parameters of the activities each station device 102 ) for certain motes . If the signal to noise mote would perform . The motes in the family can be ratio for communications from particular motes to the base numbered in a series or at random could be a alpha station device 102 is below a predetermined criterion , the numerical or numeric. The bank supplied family of motes mote may not be selected for authenticating the user. In other (e.g. , 8 motes ) can be used like a Makeup Kit ( foundation, embodiments, the environmental context may reduce the 60 concealer, blush, eye shadow , eye liner, power , lipstick , efficacy of the sensor data received from certain types of etc. ) . Each mote in the family can perform an individual sensors. For instance, if the lighting is poor, optical data may activity as in the makeup kit , these could be GPS , Ambient be of less value than temperature, audio and pressure data . Temperature, Body temperature , Pulse , Altitude, Color Sen In other embodiments, if the ambient noise level is high , sor, Sound Sensor, IR sensor, image scanner , optical LOS , optical data may be of more value than audio data . 65 etc. Customer evaluate what you wear daily and what you In an embodiment, the MEMs devices of the smart dust don't wear. The essential daily wear can be considered as 104 can include respective identification numbers ( e.g. , mandatory. The other combinations could be for special a
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2 US 11,354,666 B1 7 8 occasions , and extra care . The customer wears what is a In an embodiment, smart dust 210 can be made up of daily wear mandated, say minimum two motes . The cus- MEMs device sensors that can collect a variety of sensor tomer would wear the additional motes from the family in data. The MEMs device sensors can collect optical data , some embodiments. The recommended motes that are infrared data, audio data , electromagnetic field data , tem required to form an network are specified by a business rule 5 perature data, air pressure data, location data and / or motion say for example 3 such motes . Now as two of the motes are data . mandatory the customer has an option to pick up at least one The optical data can include data used to perform facial or additional mote from the family. body recognition . The optical data can also be used to gather The customer /Base Station device validates the Motes ID biometric data ( e.g. , weight of the user 202 , facial recogni details and determine whether the motes are active and 10 tion data, fingerprint data , and etc.) in conjunction with one or more sets of data from the other sensors. The audio data whether the mote reading unit is correct. The data received can be used to authenticate a user based on voice recogni by from the motes are relevant as per motes design , eg . First tion , or can be used to detect heart rate , blood pressure , and motes information received by the device is temperature in other biometric data . The infrared data can be used to centigrade? The unit can be in centigrade, NW /NE /SE/SW , 15 determine various biometric data about a person such as /min (preferable in dimensional analysis unites ) . The cus breathing rate , body temperature, and etc. The electromag tomer /base station device can form a smart key and trans- netic field data can be used to measure magnetic fields mits via 3G / 4G /5G /Wi -Fi along with the supplementary and / or read any RFID tags that the user may carry . The data . Transmitted information = Smart Key = [Mote ID ] + motion data and air pressure data can be used to monitor for [Mote information ). Mote information can include a speci- 20 heart rate, breathing rate, and other biometric data. The fied mote reading + Signal strength information + time stamp. location data can be GPS data or other location data (deter The signal strength information can be in dB -microvolts per mined via inertial sensing or network location ) that can try meter (dBuV / m ) Or dBu e.g. 60 dBu . The time stamp is the to identify the location of the smart dust 210 . time at which the base station had transmitted the key. The MEMs device sensors ( or “ motes ” ) that make up On the server side , the utility engine can receive the key 25 smart dust 210 can be suspended in air and surround , or be from the client side and grants access or denies access near the user 202 while collecting data . In some embodi ( transfer key) . The utility engine can recognize the transfer ments, the motes can be self -propelled and able to move key and communicates with IDM server . The IDM server around . In other embodiments, the motes may move pas maintains a log in the persona management system . Upon sively on wind currents , or using Brownian motion . In an authentication, the IDM grants access to the financial bank- 30 embodiment, the motes can be released by base station 206 ing systems as applicable . upon activation . The motes may also be carried by a user and The server side decryption algorithm can be as follows: 1 ) released when the user attempts to make a purchase using a Decrypt . 2 ) Validate Approved notes with nCr mobile payment or a credit card payment. In an embodi probability ( Approval Motes ) . 3 ) Validate customer biomet- ment, the base station device 206 can be part of a point of ric image ( approval Customer Finger Print or Retina or both . 35 sale system at a retail or customer service establishment. In 4 ) Verify the mote information data. 5 ) The correctness with other embodiments, base station device 206 can be carried in an acceptable variation . 6 ) Since the customer /base device by the user 202 by a mobile device 204 . is very near to motes , the emitted information should not In an embodiment, the base station device 206 can com have huge variations with device data. 7 ) E.g. Mote 01 pare the sensor data received from the smart dust 21- to a emitted temperature as 23 C , and Mote 02 emitted 377833N , 40 user profile, and based on the similarity, authenticate the 1224167 W (last four digits are decimals) Mote 03 emitted user. For instance, if a set of biometric data matches the user 88. Since first two information's are near to device it can profile stored biometric data within a predetermined range , validate with an allowed variation . Since customer profile then the user 202 can be authenticated . If there are multiple knows to the device , it also validates the pulse . 8 ) Validates types of biometric data being compared , the similarity may the signal strength . 9 ) If all the mote are not having signal 45 not need to be as close . For instance, if only data relating to strength with a specified variation i.e. if one or more motes facial recognition is collected , and the data matches 94 % of signal strength is deviating the rest can be called for suspi- the user profile data , then the authentication, which may cious transaction require a 95 % match , may fail. If the facial recognition data , Turning now to FIG . 2 , illustrated is example system 200 which matches at 94 % , is used in conjunction with heart rate for authenticating a user using smart dust in accordance with 50 data which also matches at 94 % , then the authentication may one or more aspects of the disclosure. be confirmed . Various matching rates can be authenticated In system 200 , a base station device 206 can receive an based on the different combinations of sensor data types . alert that a user 202 is attempting to initiate a payment using Certain forms of biometric data may be considered of a a mobile device 204 , and the base station device can send an higher quality, or functionality for the purposes of authen instruction to activate a set of smart dust device 210 to 55 tication than other types of biometric data . For instance , authenticate user 202. The mobile device 204 can send a optical scanning which scans fingerprints can be more payment request notification to server 208. Before process- definitive for the purposes of authenticating a user than heart ing the payment, the server can try to authenticate the user rate data . The predetermined matching levels can be set 202 making the payment. The server can send an authenti- accordingly based on the type of data being collected . cation request to base station device 206 which can activate 60 Turning now to FIG . 3 , illustrated is an example system the smart dust 210 which collects sensor data about the user 300 for activating a set of smart dust motes in accordance 202. The sensor data can be returned to the base station with one or more aspects of the disclosure. device 206 which can perform the authentication . In other In an embodiment, the smart dust 308 can be activated in embodiments, the base station device 206 can forward the response to receiving a notification that the user is trying to sensor data to server 208 which can perform the authenti- 65 make a payment. For instance , at 302 , the user can try to cation. Once the authentication is performed, server 208 can make a payment with their mobile device , or with a credit process the payment from mobile device 204 . card, and a server can send a notification of pending pay
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US 11,354,666 B1 9 10 ment or an authorization request to base station device 306 . and based on the similarity, authenticate the user. For Base station device 306 can then send an instruction to instance, if a set of biometric data matches the user profile activate the smart dust 308. At 304 , the base station device stored biometric data within a predetermined range, then the 306 can release the smart dust 308 which can proceed to user can be authenticated . If there are multiple types of collect sensor data relating to the user. The sensor data can 5 biometric data being compared , the similarity may not need be used to authenticate the user. The smart dust 308 can send to be as close . For instance , if only data relating to facial the sensor data to base station device 306 which can perform recognition is collected , and the data matches 94 % of the the authentication in some embodiments , or can send the user profile data , then the authentication , which may require sensor data to the server to perform the authentication . a 95 % match , may fail . If the facial recognition data , which Turning to FIG . 4 , illustrated is an example system 400 10 matches at 94 % , is used in conjunction with heart rate data for selecting a set of smart dust motes to authenticate a user which also matches at 94 % , then the authentication may be in accordance with one or more aspects of the disclosure . confirmed . Various matching rates can be authenticated In an embodiment, base station device 404 can determine based on the different combinations of sensor data types. whether to collect data from one or more of the motes ( e.g. , Certain forms of biometric data may be considered of a motes 406 ) of the set of MEMs devices that make up the 15 higher quality, or functionality for the purposes of authen smart dust used to authenticate the user 402. For instance , tication than other types of biometric data . For instance , the communications between the base station device 404 and optical scanning which scans fingerprints can be more the motes 408 may have interference or increased packet definitive for the purposes of authenticating a user than heart loss due to range from the base station device 404. If the rate data. The predetermined matching levels can be set signal to noise ratio for communications from motes 408 to 20 accordingly based on the type of data being collected. the base station device 404 is below a predetermined crite- Selection component 610 can determine whether to col rion, the mote may not be selected for authenticating the lect data from one or more of the motes of the set of MEMs user. In other embodiments, the environmental context may devices that make the smart dust. For instance, the commu reduce the efficacy of the sensor data received from certain nications between the base station device 602 and the types of sensors . For instance , if the lighting is poor, optical 25 individual motes may have interference or increased packet data may be of less value than temperature, audio and loss (e.g. , due to range from the base station device 602 ) for pressure data . In other embodiments, if the ambient noise certain motes . If the signal to noise ratio for communications level is high , optical data may be of more value than audio from particular motes to the base station device 602 is below data . a predetermined criterion, the mote may not be selected for Turning to FIG . 5 , illustrated is an example system 500 30 authenticating the user. In other embodiments, the environ for authenticating a user using smart dust in accordance with mental context may reduce the efficacy of the sensor data one or more aspects of the disclosure . received from certain types of sensors . For instance , if the In an embodiment, the MEMs devices of the smart dust lighting is poor, optical data may be of less value than 508 can include respective identification numbers ( e.g. , temperature , audio and pressure data . In other embodiments, serial numbers ). When transmitting the sensor data to the 35 if the ambient noise level is high, optical data may be of base station device 504 , the motes can send the serial more value than audio data . numbers as well . Since the smart dust 508 may be issued to In an embodiment, selection component 610 can also the user 502 by the financial institution associated with the select a number of motes from which to collect data from credit card or payment method, the smart dust 508 serial based on a priority level or type of transaction requested. For numbers can also be used to authenticate the user 502 and 40 instance, a low security login may only require data from allow the payment to proceed . one or two motes , whereas a higher level security login may The serial numbers can be used to generate a virtual card request data from three or more motes before authenticating number that is established based on a communication chan- the login. nel between the smart dust 104 and the credit card 506 or FIGS . 7-8 illustrates processes in connection with the other payment method . Once the user 502 is authenticated , 45 aforementioned systems. The process in FIGS . 7-8 can be the virtual number can be used to process the payment. If the implemented for example by systems and methods 100 , 200 , smart dust 104 is not in the vicinity of the credit card 506 , 300 , 400 , 500 , and 600 illustrated in FIGS . 1-6 respectively . the virtual number may not be generated, and the payment While for purposes of simplicity of explanation, the methods will not proceed . In an embodiment, the virtual number can are shown and described as a series of blocks , it is to be be based on a function of the biometric data and the 50 understood and appreciated that the claimed subject matter respective identification numbers. is not limited by the order of the blocks , as some blocks may Turning now to FIG . 6 , illustrated is an example base occur in different orders and / or concurrently with other station device system 600 in accordance with one or more blocks from what is depicted and described herein . More aspects of the disclosure . Base station device 602 can over, not all illustrated blocks may be required to implement include a communication component 604 configured to 55 the methods described hereinafter. communicate with a server and with smart dust MEMS Turning now to FIG . 7 , illustrated is an example flow devices. The communication component 604 can receive a chart of a method 700 for receiving and broadcasting notification that there is a pending payment or an authori- application updates, according to one or more embodiments. zation request to base station device 602. Activation com- The method can start at 702 , where the method includes ponent 608 can then send an instruction to activate the smart 60 determining, by a base station device comprising a proces dust via the communication component 604 , which can sor, that an access request is to be authenticated , wherein the proceed to collect sensor data relating to the user and return access request is associated with a user profile. At 704 , the the data to communication component 604 . method includes transmitting an instruction to activate a set Based on the sensor data received the communication of microelectromechanical systems devices, wherein the set component 604 , authentication component 606 can authen- 65 of microelectromechanical systems devices are configured ticate the user. Authentication component 606 can compare to collect sensor data. At 706 , the method includes receiving the sensor data received from the smart dust to a user profile, the sensor data from the set of microelectromechanical 9
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