SPECIAL NOTICE
99 -- Biometric Data Cleansing
- Notice Date
- 3/31/2021 2:24:51 PM
- Notice Type
- Special Notice
- NAICS
- 5417
— Scientific Research and Development ServicesT
- Contracting Office
- US ARMY RAPID CAPABILITIES AND CRIT FORT BELVOIR VA 22060-5806 USA
- ZIP Code
- 22060-5806
- Solicitation Number
- W50RAJ-20-S-0001_SBIR_BAA_A214-019
- Response Due
- 5/18/2021 9:00:00 AM
- Archive Date
- 06/02/2021
- Description
- DEPARTMENT OF THE ARMY SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM SBIR 21.4 Broad Agency Announcement (BAA) Army Applied SBIR Opportunity (ASO) Announcement ����������������������� April 1, 2021: ASO issued for pre-release April 14, 2021: Army begins accepting proposals May 18, 2021: Deadline for receipt of proposals no later than 12:00 p.m. ET � � �� IMPORTANT Deadline for Receipt: Proposals must be completely submitted no later than 12:00 p.m. ET, May 18, 2021. Proposals submitted after 12:00 p.m. will not be evaluated. The final proposal submission includes successful completion of all firm level forms, all required volumes, and electronic corporate official certification.� Classified proposals will not be accepted under the DoD SBIR Program. This BAA and the Defense SBIR/STTR Innovation Portal (DSIP) sites are designed to reduce the time and cost required to prepare a formal proposal. The DSIP is the official portal for DoD SBIR/STTR proposal submission. Proposers are required to submit proposals via DSIP; proposals submitted by any other means will be disregarded. Proposers submitting through this site for the first time will be asked to register. Effective with this announcement, firms are required to register for a login.gov account and link it to their DSIP account. See section 4.14 for more information regarding registration. �� The Small Business Administration, through its SBIR/STTR Policy Directive, purposely departs from normal Government solicitation formats and requirements and authorizes agencies to simplify the SBIR/STTR award process and minimize the regulatory burden on small business. Therefore, consistent with the SBA SBIR/STTR Policy Directive, the Department of Defense is soliciting proposals as a Broad Agency Announcement. SBIR/STTR Updates and Notices: To be notified of SBIR/STTR opportunities and to receive e-mail updates on the DoD SBIR and STTR Programs, you are invited to subscribe to our Listserv by emailing DoDSBIRSupport@reisystems.com. Help Desk: If you have questions about the Defense Department's SBIR or STTR Programs, please call the DoD SBIR/STTR Help Desk at 1-703-214-1333, or email to DoDSBIRSupport@reisystems.com. Topic Q&A: The Topic Q&A for this BAA opens on�April 1, 2021�and closes to new questions on�May 4, 2021�at 12:00 PM ET. Proposers may submit written questions through Topic Q&A at https://www.dodsbirsttr.mil/submissions/login or through the SBIR Mailbox at usarmy.pentagon.hqda-asa-alt.mbx.army-applied-sbir-program@mail.mil. In Topic Q&A, the questioner and respondent remain anonymous and all questions and answers are posted electronically for general viewing. Once the BAA closes to proposal submission, no communication of any kind with the topic author or through Topic Q&A regarding your submitted proposal is allowed. Questions should be limited to specific information related to improving the understanding of a particular topic�s requirements. Proposing firms may not ask for advice or guidance on solution approach and you may not submit additional material to the topic author. If information provided during an exchange with the topic author is deemed necessary for proposal preparation, that information will be made available to all parties through Topic Q&A. Proposing firms are advised to monitor Topic Q&A during the BAA period for questions and answers. Proposing firms should also frequently monitor DSIP for updates and amendments to the topics. This Army Applied SBIR Opportunity (ASO) is issued under the Army Broad Agency Announcement (BAA) for SBIR/STTR 21.4. All proposals in response to the technical area(s) described herein will be submitted in accordance with the instructions provided under 21.4, found here: https://beta.sam.gov/opp/b79ded14dcf54451bcfb11bddf5cd259/view?keywords=%22army%20sbir%22&sort=-relevance&index=opp&is_active=true&page=1. a. Eligibility The eligibility requirements for the SBIR/STTR programs are unique and do not correspond to those of other small business programs. Please refer to Section 3.1, Eligible Applicants, of BAA 21.4 for full eligibility requirements. b. Anticipated Structure/Award Information Please refer to Section 1, Funding Opportunity Description, provided in BAA 21.4 for detailed information regarding SBIR/STTR phase structure and flexibility. For this BAA, Department of the Army will accept Phase I proposals for the cost of up to $259,613 for a 6-month period of performance. Proposers should refer to Section 4, Application and Submission information, of BAA 21.4 for detailed proposal preparation instructions. Proposals that do not comply with the requirements detailed in BAA 21.4 and the research objectives of this ASO are considered non-conforming and therefore are not evaluated nor considered for award. Phase I proposals shall not exceed 5 pages. Phase I commercialization strategy shall not exceed 2 pages. This should be the last section of the Technical Volume and will not count against the 5-page limit. Please refer to Appendix A of BAA 21.4 for detailed instructions on Phase I proposal preparation. c. Evaluation of Proposals Section 5, Evaluation of Proposals, in BAA 21.4 provides detailed information on proposal evaluation and the selection process for this ASO. d. Due Date/Time Full proposal packages (Proposal Cover Sheet, Technical Volume, Price/Cost Volume, and Company Commercialization Report inclusive of supporting documentation) must be submitted via the DoD SBIR/STTR Proposal Submission website per the instructions outlined in BAA 21.4 Section 4.3 Electronic Submission no later than 12:00 p.m. ET, May 18, 2021. Army SBIR 21.4 Topic Index A214-019����������� Biometric Data Cleansing OBJECTIVE: Resolve biometric data issues in the current authoritative biometrics database, the Department of Defense�s Automated Biometric Identification System (DoD ABIS), through the development of a machine learning software application to identify errors and improve data quality, increasing speed and accuracy of responses to match requests. DESCRIPTION: For the purposes of this SBIR topic, biometrics refers to face, finger, iris, palm, latent images resident in the authoritative biometric data base systems. Cleansing refers to the deduplication of identity records, image (image = all/each modality) identification, image to field type association, image rotation analysis, image quality analysis, image spoofing, missing image analysis, and highest quality identification (per biometric). DoD ABIS, the authoritative data base, is required to accept all encounter submissions from across the DoD for inclusion within the biometric data set. Much of this input is from old and nearing obsolescence, legacy collection systems that do not limit inputs that are incorrect or limit in any meaningful way based on image capture quality. For this reason, the authoritative data base includes a large number of biometric records with errors, missing data, or low-quality images. This poor quality data uses valuable computing resources as well as results in a higher number of �yellow� matches which require a human examiner to review the request as well as to manually determine if there is or is not a match in the biometric data within the data base and the request. This issue will remain unresolved until all the legacy collection systems are displaced from the force. For that reason, a long term (3-5 year time horizon) solution is required to first, cleanse the data, and second, to continue to assess all incoming data, in order to rank and associate a data quality score for all images in the data base. As the old systems are removed from use in the field, data quality through the enforcement of collection quality thresholds which can be set on current COTS/GOTS (commercial/government off-the-shelf) collection systems. This will greatly improve system matching results and reduce the number and type of requests that require manual examination by the operations division examination team. This will in return also reduce the examination team�s backlog and greatly increase their ability to respond to the smaller number of inquiries that will require manual adjudication by the human examiner. PHASE I: The objective of this Phase is to design a concept for a set of machine learning tools to rate, rank and associate a data quality score for all images in the data base. Required Phase I deliverables include a determination of the feasibility for development of a prototype in Phase II, along with a preliminary design of the prototype which can rate and rank at least one of the several modalities of biometric image. Phase I deliverables include a plan for practical deployment of the proposed software applications including phases for the design, development and testing of a full suite of machine learning software for the initial data cleansing. Define the proposed concept and develop key component technological milestones in the design, development and testing of a continuous �triage� capability that will can rate, rank and categorize biometric data against all biometric modalities. PHASE II: The Phase II objective is to realign systems performance based on the output and the metrics associated to the data reclassification conducted in Phase I. Required Phase II deliverables include a functional prototype which can rate and rank at least one of the several modalities of biometric image. Demonstrate the prototype in accordance with the demo success criteria developed in Phase I for a single modality prototype. Required Phase II deliverables will also include expansion of the Phase I prototype design to cover all biometric modalities found within encounter-based records of the DoD ABIS authoritative data base. Phase II deliverables will include a detailed plan for the testing of additional modality cleansing as well as milestone proposal for the complete cleansing of the existing data set, as well as the milestone plan elements of the software applications that will continuously �triage� all new biometric data submitted to the authoritative data base. PHASE III: The desired end state is the successful development of a machine learning algorithm that can rate, rank and categorize biometric data against all biometric modalities, which will directly impact the success of two Army Programs of Record (POR). Until collection devices are fielded across the Army and the DoD that can check biometric quality at the point of capture, the biometric data base will continue to be contaminated with poor quality biometric images and other data quality issues that hinder optimal performance of search algorithms for matching of biometrics. A resident set of machine learning tools, that assess biometric quality of records as they enter the authoritative repository will provide a higher level of overall data quality and increase the timeliness and accuracy of biometric match requests from all DoD users that access the authoritative biometrics repository (ABIS 1.2/3 Army POR). Until the authoritative data base is cleansed of incomplete, incorrect and poor-quality data, human examiners will be required to adjudicate match requests that would otherwise be addressed through the transaction manager and current matching algorithms. System performance, regardless of investments in new hardware, and software are limited in their ability to improve systems metrics without data cleansing as described herein. The proposed solution should incorporate COTS/GOTS to the maximum extend to aid in the speed of development and deployment of a complete software solution that addresses current data in the authoritative data base as well as the ongoing �triage� of data from old Army legacy devices still in use for biometrics capture. KEYWORDS: Biometrics; Modality; Face; Finger; Iris; Palm; Latent images; Authoritative biometric data base; REFERENCES: https://link.springer.com/article/10.1186/1687-5281-2014-34 https://link.springer.com/chapter/10.1007/978-3-319-03889-6_24 http://atvs.ii.uam.es/fierrez/files/2012_Sec&Pri_BiometricQ.pdf https://arxiv.org/abs/1902.02919
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