Akademik Veri Yönetim Sistemi
Future Technologies Conference, FTC 2020, San Francisco, Amerika Birleşik Devletleri, 5 - 06 Kasım 2020, cilt.1290, ss.160-179
A major concern for public and private organizations worldwide is to ensure that its constituents are healthy. However, the degree to which this is ensured differ from country to country and even from community/individual to community/individual based on the level of wealth/income, education, etc. In developing countries the concern for the health of its population is particularly important the populations of since these countries often suffer from serious health issues. These health issues have attracted the attention of international organizations who have been focusing on raising awareness of the health issues within the local communities through education. Assessment of the status of the health of a population is dependent on data. This data is used to determine the allocation of the resources that are used to improve the health of the population. Traditionally, organizations have used paper surveys for collecting such data. Since this is a manual process it is prone to errors that also consumes a significant amount of time and effort. It is possible to overcome the limitations of paper surveys by using advanced technology for the collection process. This leads to digitized surveys which may be conducted using hand-held devices. Hand held devices can help getting more reliable and secure data in less time, with lower cost and with less effort. This paper contributes to these efforts by proposing a hand held device framework that has a user-friendly visual interface suitable for data collection in the field. The proposed framework has been implemented and used for the first time in Uganda. It has been well received by domain experts who showed that it was very successful and it was capable of collecting reliable data in less time than when they were using the paper-based process. We describe various components of the proposed framework along with the data storing feature for in-the-field accumulation of data. This was combined with after hours bulk data transmittal of the accumulated data from central points to a data repository.