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C H A P T E R 4 Develop a Methodology for Analyzing Data A list of data elements has been identified from the quali- · Remote monitoring alarm system for indication of fire, fied data sets in Chapter 3. From the various data sets, data smoke, intrusion, power outage, climate control failure, elements that need to be considered could include video and hardware failure, water presence, and high temperature; vehicle kinematic data, in-vehicle and surrounding environ- · Elevated flooring system; mental data, vehicle- and infrastructure-based data, and raw · High physical security with steel-reinforced structural walls; and reduced data. Processing and analyzing the data requires · Limited personnel accessibility; and addressing data storage issues, data storage configuration, · Two 600-ft2 secure data reduction laboratories that house reduction, and the computing necessary to analyze each data high-end Dell workstations. set. Because the candidate studies identified earlier are con- ducted by VTTI or UMTRI, the data computation capability VTTI's Data Services Center server room houses the fol- of these two institutes is discussed briefly. lowing equipment: · 250+ Dell-branded business-class desktops, laptops, and Data Storage and Computation laboratory workstations; Requirements · 15+ high-availability, high-performance Dell PowerEdge Naturalistic data collection studies that include video data usu- servers; ally generate large files that require professional management. · More than 60 TB of redundant high-speed storage with Consequently, research data at VTTI are stored on the Virtual short-term expandability exceeding 100 TB; Library System (VLS) Storage Area Network (SAN) that oper- · Redundant optical SAN switch/routers; ates within a dedicated private network. These data are isolated · A large-capacity backup system that includes a tape library from VTTI's operational network and all other networks, capable of handling 12 GB of data per min; and including the web, by high-end firewall hardware managed by · Network connections that are all high-speed Gigabit Ether- VTTI's Information Technology Group (ITG). All network net (VTTI was a pioneer in implementing this technology connections within VTTI are high-speed Gigabit Ethernet. for every network portal). The data sets can be accessed using a dedicated, high-speed structured query language (SQL) server and by means of spe- The computing requirements necessary for data manipu- cial application servers using Microsoft Sequel Server, MatLab, lation and analysis are a result of the data size, data storage or SAS. Figure 4.1 shows the data center at VTTI. configuration, reduction needs, and analysis requirements. The data center has the following features: The VTTI team created codes that extract subsets of data for analysis purposes in multiple software environments, includ- · Emergency power provided by an on-site diesel generator ing MatLab, SAS, and SQL. An example of a flowchart for a that supplies backup power for the data center, emergency MatLab function to extract a subset of data on a defined high- lighting, and a telecommunications closet; way section is provided in Figure 4.2. · External wide area network (WAN) speeds equal to an OC-3 Besides the existing commercial software, VTTI developed (45 Mbps, approximately 30 times that of a T-1 connection); proprietary data-viewing software, the Data Analysis and · A dedicated climate control system with a backup contin- Reduction Tool (DART), to allow synchronized viewing of gency system; driver performance (parametric) data and video and audio 26

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27 streams. This system allows researchers and data reductionists to work directly with large databases while providing ease of use and improved accuracy. As shown in Figure 4.3, reduction- ists can select specific variables and customize the interface of the illustration. While the video is playing, the software will draft charts for those variables along the time axis synchro- nized with the video. When multiple targets are sensed by radar units, the charts are color coded for better viewing. Similar to the data storage and calculation capability of VTTI, UMTRI has developed its data collection, storage, and computation capability over the years. UMTRI has devel- oped large, driver-vehicle databases since the mid-1990s. By the end of 2006, approximately 1 million vehicle miles of data had been collected. The data archive at UMTRI is maintained Figure 4.1. Environmentally controlled and secured on an Internet-accessible system for on-demand access by VTTI data center. Figure 4.2. Sample flowchart of a MatLab function.