IowAccess Project 8 : statewide geographic information systems (GIS) support, 1998

This is the final report of the of IowAccess Project 8, which designed and implemented a geospatial data infrastructure for Iowa, including a formalized coordination body, a coordination staff, and enhanced data clearing house, and a statewide GIS training and education effort.

Data Processing Systems Manual: Highway Noise Prediction, 1972

The Data Processing Department of ISHC has developed coding forms to be used for the data to be entered into the program. The Highway Planning and Programming and the Design Departments are responsible for coding and submitting the necessary data forms to Data Processing for the noise prediction on the highway sections.

Field Data Acquisition Technologies for Iowa Transportation Agencies, HR-366 August 1994

This report describes the results of the research project investigating the use of advanced field data acquisition technologies for lowa transponation agencies. The objectives of the research project were to (1) research and evaluate current data acquisition technologies for field data collection, manipulation, and reporting; (2) identify the current field data collection approach and the interest level in applying current technologies within Iowa transportation agencies; and (3) summarize findings, prioritize technology needs, and provide recommendations regarding suitable applications for future development. A steering committee consisting oretate, city, and county transportation officials provided guidance during this project. Technologies considered in this study included (1) data storage (bar coding, radio frequency identification, touch buttons, magnetic stripes, and video logging); (2) data recognition (voice recognition and optical character recognition); (3) field referencing systems (global positioning systems [GPS] and geographic information systems [GIs]); (4) data transmission (radio frequency data communications and electronic data interchange); and (5) portable computers (pen-based computers). The literature review revealed that many of these technologies could have useful applications in the transponation industry. A survey was developed to explain current data collection methods and identify the interest in using advanced field data collection technologies. Surveys were sent out to county and city engineers and state representatives responsible for certain programs (e.g., maintenance management and construction management). Results showed that almost all field data are collected using manual approaches and are hand-carried to the office where they are either entered into a computer or manually stored. A lack of standardization was apparent for the type of software applications used by each agency--even the types of forms used to manually collect data differed by agency. Furthermore, interest in using advanced field data collection technologies depended upon the technology, program (e.g.. pavement or sign management), and agency type (e.g., state, city, or county). The state and larger cities and counties seemed to be interested in using several of the technologies, whereas smaller agencies appeared to have very little interest in using advanced techniques to capture data. A more thorough analysis of the survey results is provided in the report. Recommendations are made to enhance the use of advanced field data acquisition technologies in Iowa transportation agencies: (1) Appoint a statewide task group to coordinate the effort to automate field data collection and reporting within the Iowa transportation agencies. Subgroups representing the cities, counties, and state should be formed with oversight provided by the statewide task group. (2) Educate employees so that they become familiar with the various field data acquisition technologies.

Maximizing the Use of Roadway Weather Information Systems: Final Report, TR-404, 1998

This project was proposed as Phase I of a 2-phase program to evaluate the present use of weather information by Iowa Department of Transportation (IaDOT) personnel, recommend revised procedures, and then implement the resulting recommendations. Midway through Phase I (evaluation phase) the FORETELL project was funded. This project is a multi-state venture that engages the National Weather Service (NWS) and the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration and proposes to supplant the current weather information-generation and distribution system with an advanced system based on state-of-the-art technologies. The focus of the present project was therefore refined to consider use of weather data by IaDOT personnel, and the training programs needed to more effectively use these data. Results of the survey revealed that two major areas - training of personnel on use of data from whatever source and more precise information of frost formation - are not addressed in the FORETELL project. These aspects have been the focus of the present project.

Improved Employment Data for Transportation Planning, 1998

Transportation planners typically use census data or small sample surveys to help estimate work trips in metropolitan areas. Census data are cheap to use but are only collected every 10 years and may not provide the answers that a planner is seeking. On the other hand, small sample survey data are fresh but can be very expensive to collect. This project involved using database and geographic information systems (GIS) technology to relate several administrative data sources that are not usually employed by transportation planners. These data sources included data collected by state agencies for unemployment insurance purposes and for drivers licensing. Together, these data sources could allow better estimates of the following information for a metropolitan area or planning region: · Locations of employers (work sites); · Locations of employees; · Travel flows between employees’ homes and their work locations. The required new employment database was created for a large, multi-county region in central Iowa. When evaluated against the estimates of a metropolitan planning organization, the new database did allow for a one to four percent improvement in estimates over the traditional approach. While this does not sound highly significant, the approach using improved employment data to synthesize home-based work (HBW) trip tables was particularly beneficial in improving estimated traffic on high-capacity routes. These are precisely the routes that transportation planners are most interested in modeling accurately. Therefore, the concept of using improved employment data for transportation planning was considered valuable and worthy of follow-up research.

Black Hawk County Criminal Justice Information Systems, Independent Auditor's Reports, Financial Statement and Required Supplementary Information, Schedule of Findings, June 30, 2004

Other Audit Reports - 28E Organizations

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Report on a special investigation of the University of Iowa Hospitals and Clinics, Health Care Information Systems Department, for the period January 1, 2005 through July 5, 2013

Report on a special investigation of the University of Iowa Hospitals and Clinics, Health Care Information Systems Department, for the period January 1, 2005 through July 5, 2013

Report on a special investigation of the Cerro Gordo County Management Information Systems (MIS) Department for the period January 1, 2008 through July 31, 2013

Report on a special investigation of the Cerro Gordo County Management Information Systems (MIS) Department for the period January 1, 2008 through July 31, 2013

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.