Digitizing paper forms with mobile imaging technologies

Dell, Nicola; Breit, Nathan; Chaluco, Timóteo; Crawford, Jessica; Borriello, Gaetano

doi:10.1145/2160601.2160604

Cited by 30 publications

(25 citation statements)

References 13 publications

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“…It uses the device's built-in camera to capture an image of a scan-compatible paper form, which it feeds into a series of image processing algorithms (SURF, fast approximate nearest neighbor, and RANSAC) to establish a point-by-point mapping between the template and the captured image [20][21][22][23]. Using this mapping, Scan segments the form into small image snippets that each contains a single data field from the original form [24].…”

Section: Description Of Technologymentioning

confidence: 99%

“…Hand-filled bubbles are multiple-choice questions that are completed by filling in the bubble that corresponds with the desired response. Scan classifies hand-filled bubbles using a Support Vector Machine (SVM) and principal component analysis (PCA) [20,25,26]. Structured number boxes are a 2 × 3 grid of dots that can be connected by straight lines to draw numerals.…”

Section: Description Of Technologymentioning

confidence: 99%

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ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

Ali¹,

Powers

Beorse

et al. 2016

Future Internet

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Abstract:The present grievous tuberculosis situation can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology, this can be achieved through quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during a testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, the application and 3G-enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to determine the impact of ODK Scan. Additionally, at the end of the study, users' feedback was collected regarding app usability, user interface design and workflow changes. A total of 122 patients' records were retrieved from the server and analysed in terms of quality. It was found that ODK Scan recognized 99.2% of multiple choice fill-in bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, but data verification and form-filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, but they were more concerned about the time-consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements.

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Section: Description Of Technologymentioning

confidence: 99%

Section: Description Of Technologymentioning

confidence: 99%

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

Ali¹,

Powers

Beorse

et al. 2016

Future Internet

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“…Digital data collection tools for humanitarian programs have been well studied [13]. The most comprehensive toolkit is the Open Data Kit (ODK) project [7,8,21].…”

Section: Related Workmentioning

confidence: 99%

DevCAFE 1.0: A participatory platform for assessing development initiatives in the field

Nonnecke

Krishnan

Patel

et al. 2015

2015 IEEE Global Humanitarian Technology Conference (GHTC)

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Abstract-The design and assessment of development initiatives is increasingly participatory, where decision makers consider feedback from affected populations. While digital data collection facilitates faster and more reliable analysis, existing data collection tools are not optimized for unstructured qualitative (textual) data and peer-topeer participant collaboration. In this paper, we propose a system called the Development Collaborative Assessment and Feedback Engine version 1.0 (DevCAFE), a customizable participatory assessment platform that collects and integrates quantitative assessment, qualitative feedback and peer-to-peer collaborative filtering. DevCAFE incorporates a library of statistical analyses for researchers to quickly identify quantitative and qualitative trends while collecting field data. DevCAFE can run on any mobile device with a web-browser and can work with or without Internet connectivity. We present results from two pilot projects: (1) 137 participants evaluating family planning education trainings at three Nutrition Education Centers in rural Uganda, and (2) 4,518 participants evaluating policy priorities for elected leaders in the June 2015 Mexico mid-term elections. DevCAFE collected over 19,000 peer-to-peer ratings of 336 submitted ideas. Feedback gathered through DevCAFE enabled targeted reforms to the family planning efforts in Uganda and the need for increased government attention to public safety in Mexico. Case studies and interactive demos are available at: http://opinion.berkeley.edu/devcafe/

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“…If multiple pieces of information are required, then the user will need to scan multiple codes, or follow web links. Previous solutions to this issue have used one code or other identifier per page of media and then automatically downloaded all information from the page 2 . This approach could easily result in downloading unwanted information, and cause higher user task loads as this content is filtered out.…”

Section: Related Workmentioning

confidence: 99%

“…Our approach takes advantage of this fact, and allows users to mark on the document itself to select items. The mScan project [2] also uses camera phones and users' marks on paper, but to scan a specific, preset form with multiple-choice bubble fields, that is placed in a known position and orientation. While encouragingly reliable, the mScan format only supports very specific marks for data gathering.…”

Section: Related Workmentioning

confidence: 99%

TicQR: Flexible, Lightweight Linking of Paper and Digital Content Using Mobile Phones

Pearson

Robinson

Buchanan³

et al. 2013

Lecture Notes in Computer Science

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Abstract. In this paper we introduce TicQR -a photo-based checkbox-enabled interface which bridges the physical and digital document domains, allowing automatic download or processing of useful data from paper documents. There is a long demonstrated need for people to be able to connect between printed material and digital information and services. By using a combination of image recognition and QR codes we are able to detect user marks on paper documents via a single photograph taken with a standard smart phone. This information can then be used to access the equivalent digital content, save contacts or URLs, or even order goods directly from local retailers.

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Digitizing paper forms with mobile imaging technologies

Cited by 30 publications

References 13 publications

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

ODK Scan: Digitizing Data Collection and Impacting Data Management Processes in Pakistan’s Tuberculosis Control Program

DevCAFE 1.0: A participatory platform for assessing development initiatives in the field

TicQR: Flexible, Lightweight Linking of Paper and Digital Content Using Mobile Phones

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