A practical example of TRM is the innovation architecture (IA) proposed by ... These research activities .... login authentication on personal computers in offices.
PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET
Learning Methodology of Innovation Architecture Using Case Example of Development of Contactless Palm Vein Pattern Biometric Authentication Technology Yoichiro Igarashi1, Makoto Okada1, Akihiko Suzuki2, Munehiko Iwase3, Shigeki Shibagaki4, Shunichi Koike5, Hajime Matsubayashi6, Hitoshi Abe7 1
Fujitsu Laboratories Ltd., Kawasaki-shi, Kanagawa, Japan 2 Japan Energy Association, Minato-ku, Tokyo, Japan 3 Pioneer Corporation, Meguro-ku, Tokyo, Japan 4 Nitta Corporation, Yamatokohriyama-shi, Nara, Japan 5 Tokyo Gas Co., Ltd., Arakawa-ku, Tokyo, Japan 6 Oji Paper Co., Ltd., Chuo-ku, Tokyo, Japan 7 Japan Techno-Economics Society, Chiyoda-ku, Tokyo, Japan Abstract—The learning methodology for technology roadmapping (TRM) described in this paper comes out of the work of a Japan Techno-Economics Society group. A practical example of TRM is the innovation architecture (IA) proposed by H. Tschirky’s group at ETH Zurich. A contrasting approach for an IA is to require engineers to learn the theoretical background before they customize the IA for particular applications. The IA users would have to make great efforts to interpret IA theory for their daily tasks, described in the language of their professions. The approach to designing a learning methodology in this paper is to build an IA using a case study. Using the case study, engineers are able to learn how to develop the IA by assuming the roles of project members. The paper covers the implementation of the methodology by describing how an IA is built using a case study on the development of a biometric authentication technology (released by Fujitsu Laboratories Ltd. in 2003). By using the methodology to follow the case example, an R&D organization was able to gain experience with the IA (TRM) and learn how to use it efficiently.
I. INTRODUCTION Today’s high-tech industries face new difficulties yet to be experienced in innovation because the key factors to their success in business no longer rely on the technological superiority of products. The importance of providing consistent value that contributes to driving business and establishing a relationship among various functional groups in a company has become prominent; companies in high-tech industries have to pay attention to the activities of not only their technology divisions but also their product planning divisions and sales and marketing divisions. In other words, collaboration across all functional divisions is the key to opening the door to the next stage of innovation. Since autumn 2002, we have been conducting a study on business modeling in a group at JATES (Japan Techno-Economics Society), and have continued a study on innovation support technology (IST) consisting of a business modeling method, a strategic road mapping method and an innovation architecture method. These research activities have been reported at PICMET conferences [1-5]. However, as Tschirky [6] suggests, the fact that the different kinds of professions within a company speak
different languages could be a great barrier to building a consistent innovation process. An innovation architecture (IA) [6][7] provides not only a solution for companies and organizations but also a methodology to integrate the various knowledge necessary for business planning. The procedure to build an IA begins with understanding the current state of business and technologies in the company. The step after that is to evaluate the built IA and refine it according to the market trend, business, and technology. The IA will be useful for finding new value or new technologies that need to be acquired. An IA [6-8] is also known as a general-purpose methodology for technology roadmapping (TRM) especially applicable to overall business processes and strategic planning in companies. That being said, the IA users have to make careful and strategic decisions about the organizational scale suitable for applying the IA. In other words, people planning to apply the IA methodology need to survey the target organization from the viewpoint of organizational scale. Even in cases where the focus is on the R&D field, the valuation results for the IA methodology may vary depending on the organizational scale, which ranges from the smallest R&D teams to an entire company (e.g., R&D center). The IA users have to choose the best organizational scale for the IA. This paper mainly discusses and describes how to introduce an IA for researchers and engineers at R&D sites. For the discussion involving organizational scale, the choice was to have the smallest organization in the company be an R&D team. II. METHODOLOGY USING A CASE STUDY One fundamental way to foster mastery of a framework for innovation is to require engineers to learn the theoretical background. The engineers would then customize the framework for their particular applications. Afterward, engineers and researchers may have to make great efforts to interpret the resulting IA rules, which are described in the language of the engineering profession, for their daily tasks. The situation presents a psychological barrier to promoting innovation. Alternatively, a simple learning methodology for
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET TRM can be a useful design methodology for building roadmaps. This paper describes a methodology for introducing an IA into an R&D organization. In the paper, the approach to designing a learning methodology is to build an IA using a case study. Using the case study, engineers are able to learn how to develop the IA by assuming the roles of project members. The psychological barrier is expected to be lower in the users participating in this exercise. By applying this methodology, users are expected to acquire a deeper understanding of the IA and redefine their own technical issues in the common language of the IA. The proposed methodology could thus be beneficial to the users’ companies even as the users discuss how to customize the methodology to fit the organizational scale and organizational characteristics. Based on the above-mentioned ideas, this work uses the development history of the technology for contactless palm vein biometric authentication for the case study. The paper shows each step in building an IA using the case study. Each step of analysis of the case study does not reflect the details of the original events. At the end are the design rules of the completed IA built using the case study. The authors expect that this methodology will demonstrate the effectiveness of an IA. Generally speaking, R&D teams can acquire a deeper understanding of the concept and design process of the IA methodology by analyzing case studies. The paper proceeds as follows. First, it introduces the concept of the technology for contactless palm vein biometric authentication in the case study. Next, it describes the following three phases in building an IA: Phase 1) Analysis of existing technologies, Phase 2) Deployment of the technology in a new application field, Phase 3) Deployment of the technology to a market.
(a) Palm vein sensor
The last section discusses the benefits of using a case study. III. DESCRIPTION OF THE AUTHENTICATION TECHNOLOGY This section provides a brief description of the project in the case study. Since the authors were not actually members of the project, the authors retraced each step of the project by assuming the roles of members of the R&D team. The technology for contactless palm vein pattern authentication [9][10] is a kind of biometric authentication technology, and it was released by Fujitsu Laboratories Ltd. in 2003 [11]. After releasing the technology, Fujitsu applied it to ATM (Automatic Teller Machine) products in their banking systems [12]. Fig. 1 illustrates how the authentication technology works. The technology utilizes a unique characteristic of deoxygenated hemoglobin coursing through the palm veins to recognize a person’s distinctive vein patterns. To capture the image of a palm for authentication, the device irradiates the palm held over it in near-infrared light. Fig. 1(a) shows the hand situated above the device. An infrared camera in the device captures a black-and-white image showing the blood veins in the subcutaneous tissue of the palm. The deoxygenated hemoglobin makes this process possible, absorbing the near-infrared light and making the veins show up as black lines (Fig. 1(b)). After the device successfully captures the image, the authentication system extracts a vein pattern image (Fig. 1(c)). The data in the vein pattern image can be used for authentication because each person has unique vein patterns. That is a theoretical outline of the technology.
(b) Infrared image of palm
(c) Vein pattern image
Fig. 1. Outline of contactless palm vein pattern authentication [10]
IV. PHASE 1: ANALYSIS OF EXISTING TECHNOLOGIES The first step in building an IA is to analyze existing technologies and business areas, which are elements belonging to the “Innovation Trends” level in the IA structure. The members of the R&D team at the start of the project
were experts in image recognition technologies: for example, technologies for the edge detection and distortion correction of video pictures. The R&D team also had know-how of image processing technologies using infrared sensors. The authors suppose that the purpose of the R&D team at that time was to deploy technologies to professional markets. Fig. 2 shows the business situation in the IA structure.
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Innovation Trends Businesses
Image Processing Service for Companies
Quality Assurance
Surveillance Service
ProductSystemsServices
Inspection Systems
Video Surveillance Systems
Functions
Image Processing
Edge Detection
Authentication Service
Fingerprint Facial Authentication Authentication
Pattern Matching
Infrared Image Processing
Technology Platforms
Sensor Technology
Software Technology
Scientific Knowledge
Physics
Information Processing
Distortion Correction
Fig. 2. Phase 1: IA structure of existing technologies
V. PHASE 2: CHALLENGE TO DISCOVER NEW BUSINESS AREAS The second step in building an IA is to discover new business areas to target for deployment of the existing technologies belonging to the “Innovation Trends” level in the IA structure. A. Decision-making and the discovery of a new market At this point, the R&D team decided to go outside the conventional application field for image processing to look for a new concept. They discovered the concept of general-purpose security systems for public use. The market for authentication products at this stage already had several released products, featuring authentication using iris patterns for entry into important facilities and authentication using fingerprints pattern for login authentication on personal computers in offices. In this market scenario, authentication technology for use by large numbers of the general public seemed to be in a field with an undeveloped market. Public opinion in those days had become increasingly strident on the issue of information security because of certain events. For example, there were discussions on Japan’s Basic Resident Register Network in 2002 and the events of September 11, 2001. Intertwined with these discussions was a growing trend for people to pay more attention than ever before to information security. At a time with this social consciousness, the R&D team had been watching market trends involving authentication techniques using vein patterns, since an earlier stage of development. The authors think that the R&D team must have studied the benefits of authentication using palm vein patterns, which are more robust than other types of biometric data, such as fingerprints or iris patterns, against the malicious capture of
biometric information. To prove their hypothesis, the R&D team collected authentication data--facial images, voices, fingerprints, and vein patterns--from 700 persons, and they studied which data type was most suitable for authentication purposes. The authors also think that the R&D team studied the advantages and disadvantages of the technology from various perspectives to find the best application. For example, a prototype developed at an earlier stage was designed to capture a wider area of the vein patterns from the upper arm. According to this trial, the authors assume that the R&D team tried to find the best use of the authentication device, by discussing the advantages and disadvantages for each prototype. B. Release of the first product Through trial and error and repeated discussion, the R&D team established the quality (in precision and stability) of the authentication technique. Ultimately, the team came to the conclusion that palm vein patterns were the most suitable data type for the authentication of a person. The first product from the R&D team came in August 2002, and it was a mouse with a built-in authentication module. Personal computers equipped with the specialized mouse were capable of providing business users with a login authentication function. After the release of the first product, the R&D team set for themselves the goal of releasing a security system for the general public. Considering the demand by the public for an authentication function in public places, they chose a “contactless” feature for hygiene reasons. Most of high-performance mainstream products in those days were in a “contact-type” category. Against this trend, the R&D team chose to incorporate the contactless feature in their technology.
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET Their contactless authentication device would not require users to touch the device directly. To realize the device, however, the R&D team had a major problem to solve. Conventional technologies could not ensure that the images captured from the palm of a hand held in the air would be clear enough to extract vein pattern images without excessive blurriness. To solve the problem, the R&D team utilized their existing image processing techniques for automatic correction. In the end, the R&D team released the contactless palm vein authentication technology in March 2003 (Fig. 3). Their existing know-how of image processing technologies contributed to the new authentication technology. One attractive quality of the device as noted in the press release was that members of the public were expected to have less of a psychological barrier to using the device in a public space.
R&D team’s decision to start development of the contactless authentication device. In practical business processes, decision making by the marketing department is necessary to find and define a “New Innovation Trend” in a company, and introduce a new product. However, a practical marketing process is beyond the scope of this paper.
C. New business trend in the IA Fig. 4 outlines the steps of the above-described events in the notation added to the IA framework. As previously mentioned, a need for public security systems emerged in the market. This trend appears as Public Security System at the “Innovation Trends” level of the IA structure. It triggered the
Fig. 3. Contactless authentication device prototyped in 2003 [11]
Existing Trend
Innovation Trends Businesses
Image Processing Service for Companies
Quality Assurance
Surveillance Service
ProductSystemsServices
Inspection Systems
Video Surveillance Systems
Functions
Image Processing
Edge Detection
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Public Security System
Authentication Service
Fingerprint Facial Authentication Authentication
Pattern Matching
Infrared Image Processing
Technology Platforms
Sensor Technology
Software Technology
Scientific Knowledge
Physics
Information Processing
Distortion Correction
New Elements to Realize New Innovation Trend
Fig. 4. Phase 2: IA at the stage of developing a new field for deploying the technology
The R&D team at this point did not have a solution to how to make the “Innovation Trends” elements a reality. They had to prepare the several components that were necessary to realize the Public Security System. D. Deployment of new components Fig. 5 illustrates the next step of implementing the Public Security System. The newly added elements appear in green and belong to the new trend in “Innovation Trends,” representing a security system for public places. In this case
study, the (new) “Functions” for implementing the contactless feature are deployed as modified existing “Functions.” The following steps describe the development history expressed from the viewpoint of the IA framework. Firstly, the target of realizing a security system for public use was set at the “Innovation Trends” level. Secondly, the authentication system was described at the “Functions” level. Finally, the R&D team customized their existing functions to put together the technology.
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Existing Trend
Innovation Trends
Image Processing Service for Companies
New Trend
Public Security System Medical Use
Businesses
Quality Assurance
Surveillance Service
ProductSystemsServices
Inspection Systems
Video Surveillance Systems
Functions
Image Processing
Edge Detection
Authentication Service
Fingerprint Facial Authentication Authentication
Technology Platforms
Sensor Technology
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Physics
Pattern Matching
Infrared Image Processing
Public Security Service
Contactless Palm Vein Authentication System
Correction of Distortion
Software Technology Added element for Medical Use Information Processing
Modified Element (at the “Functions” level) for Medical Use
Fig. 5. Phase 2: IA with a deployment scenario for a new field
Typically, in using the IA design methodology, R&D teams often introduce quite a few new elements to “Functions” to reach their objectives at the “Innovation Trends” level. These elements are indispensable to realizing great innovations, so though it is theoretically true that they are needed, it is not always true for daily R&D processes. Application and modification of existing technologies (i.e., reuse of technologies) are also effective for creating new trends in “Innovation Trends.” From the authors’ analysis, the case study in the paper is a case of best practices. In this case, the “Public Security System” is composed by the re-use, modification and combination of existing functions.
With this assumption, the authors suppose that the R&D team had a special interest in public security systems in the medical field. In contrast, the financial field was not a high priority target for the R&D team. However, the team would later choose the financial field as the first target. Financial companies (e.g., banks) had an increasing problem with spoofing in this period. To solve the problem, financial companies sought new features to advance and upgrade the existing ATM cards in the market into new IC cards equipped with novel technologies such as biometric authentication. This need was the turning point that led to the R&D team discovering the ATM market.
VI. PHASE 3: DEPLOYMENT TO A NEW MARKET
B. IA customization for the financial field Fig. 6 shows the IA structure including a new scenario for deployment to the financial (ATM) field. The red elements represent those added or modified by the feedback of market-pull from financial customers’ strategies.
This section describes the process leading to the discovery of the financial field for deployment of the authentication technology. A. New demand from the financial field The press release issued in March 2003 about the contactless palm vein pattern authentication technology [9][10] has an interesting issue to note. The authors assume that the R&D team may have carefully considered demonstrating their technology at that year’s general assembly of the Japanese Association of Medical Sciences1. 1 The Japanese Association http://jams.med.or.jp/en/index.html
of
Medical
Sciences,
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET
New Trend
Existing Trend
Innovation Trends
Image Processing Service for Companies
Public Security System Financial Use
Medical Use
Businesses
Quality Assurance
Surveillance Service
ProductSystemsServices
Inspection Systems
Video Surveillance Systems
Functions
Image Processing
Edge Detection
Technology Platforms
Authentication Service
Fingerprint Facial Authentication Authentication
Pattern Matching
Infrared Image Processing
Sensor Technology
Software Technology
Physics
Information Processing
Public Security Service
Public Security Service for ATM
Contactless Palm Vein Authentication System
Contactless Palm Vein Authentication System for ATM
Data Compression
Distortion Correction
New Level
Scientific Knowledge
Business Platforms Business Knowledge
Tuning for ATM
Business Unit For ATM
Financial Service
Added Element for Financial Use Modified Element (at the “Functions” level) for New Innovation Trend Added Element (at the “Functions” level) for ATM Product
ATM：Automatic Teller Machine
Added Element at the Level for Business field
Fig. 6. Phase 3: IA structure with developments for the financial field
In addition, the authors added new elements at the “Functions” level, based on the feedback of market-pull, and these elements compose a new authentication system for ATM products. The two new elements (in yellow) at the “Functions” level are deployed as shown in Fig. 6. The Data compression element was made according to performance requirements to improve the data compression speed and data transmission speed. The other element, Tuning for ATM, represents an implementation technique for proper installation and operation of the authentication module in an ATM. The performance of image processing functions and other existing functions (in blue at the “Functions” level) also needed improvement so that the technology could be optimized for ATM products, such as for a compact chassis design or resistance to environment degradation. The gray part contains two new levels: “Business Platforms” and “Business Knowledge.” It represents particular knowledge for business in the financial field (as discussed in the next section). VII. DISCUSSION This section discusses some outstanding issues in the case study.
A. Interaction between technology-push and market-pull In the case study, technology-push was driving the development and deployment of the authentication technology for the financial field. At the same time, however, market-pull could also be said to be driving the development. The reason is as follows. Generally speaking, the focus of the IA design methodology on making great innovations by market-pull was as follows. First, the R&D team created an idea at the “Innovation Trends” level. Then, the team created new elements at the “Functions” level to implement the “Innovation Trends” elements. Finally, the team discussed strategy at the “Businesses” level. Practically speaking, however, the IA design rules do not require users to strictly follow the standard process. If the customer provides concrete information for a service, market-pull can drive the development path from the “Businesses” level toward the “Functions” level (technology-push). B. Adding the new “Business Knowledge” level The authors’ new idea was to add the (new) “Business Knowledge” level (at the same level as “Scientific Knowledge”) for the further study of business feasibilities. The “Business Knowledge” level supports implementation of the above-mentioned ATM functionalities. The idea is to handle business knowledge at the same levels as scientific
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PICMET 2009 Proceedings, August 2-6, Portland, Oregon USA © 2009 PICMET knowledge and technology platforms. Based on the authors’ analysis of the case study, the following two business facts contributed to the success of the project: 1) Fujitsu has an affiliated company that has an ATM product division. 2) That company could provide knowledge on deployment of ATMs to the market. The authors expect that users will understand the benefits of an IA as a communication tool when they look at it from a business perspective. In other words, the IA could be a highly flexible framework for operations.
deployment to the R&D field, is the benefits obtained from the practice in building an IA using an existing project. ACKNOWLEDGMENTS These research activities were organized in Sub-working group A of the Japan Techno-Economics Society (JATES). The authors would like to express their gratitude to the JATES members who contributed their ideas through discussions and the JATES management office for supporting the research activities. REFERENCES
C. Benefits of using a case study The points to note on building an IA using a case study (a well-known case example) are as follows: 1) Actual projects can be pushed forward by the mutual interaction between market-pull and technology-push in the IA design process. 2) The IA is effective for making “Functions” a reality through the feedback of market-pull. 3) New requirements from a market present challenging but soluble problems for R&D teams. In this case study, the new element added to the “Businesses” level represents an ATM security service for banks. The element was put together based on demand from financial companies. VII. CONCLUSION This paper has discussed a methodology for introducing an innovation architecture using an existing well-known case example. Practice with case studies can help accelerate R&D teams’ understanding of the benefits of an IA. By repeating this process with several different examples, users can obtain a deeper knowledge of an IA and improve R&D quality. Since the details of the case study were not actually reproduced in a physical system, the authors analyzed the case study as “virtual” members of the project team. For this reason, the analysis results might differ from the actual results. Quite a few researchers and engineers implicitly use their own original techniques that are similar to an IA. The IA design methodology in the paper could be a guideline to establishing these “locally-operated” processes and be a powerful tool to helping users plan mid- and long-range R&D strategies. To apply an IA at R&D sites, users have to take into account the specific circumstances at each company and adapt the design processes for their own organizations. The authors believe that the IA methodology has no strict rules on building an IA. The core value of an IA is to provide R&D teams with a communication tool as well as a strategy roadmapping tool. The most important value to IA users, from the viewpoint of
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