A compression-based mobile data collection system: a test case with climatepal project
Data collection is the process of preparing and collecting data as part of accountability and process improvement. Organizations globally, and particularly in the developing countries, are being forced to internalize and account for costs and impacts of environmental and community projects through monitoring and evaluation. Data collection and aggregation is conducted for this purpose and is done using various tools, the most common being paper-based methods. The use of mobile phones for quick-time data collection is increasing rapidly around the world. Mobile-based data collection has proven to be a more efficient tool to perform data collection activities. While current mobile data collection solutions provide the necessary requirements for data collection, they are inefficient in terms of network bandwidth consumed during data transmission, especially when collecting significantly large amounts of data from a large population and a large number of surveyors. This is because as quantity of data increases, this increases the amount of data bandwidth, increasing the time it takes to upload surveys, data bundles consumed and stretches local memory which is limited. There is need to solve these problems through implementation of more efficient data collection systems. This research proposes a mobile-based data collection system that uses data compression methods in order to improve data collection efficiency. To test the proposed data collection model a mobile- web based monitoring and evaluation system was implemented to collect data for an on-going environmental project by Climate Pal Kenya. The findings indicate the efficiency of this approach for mobile-based data collection tool and the effectiveness of the chosen data compression method in reducing the amount of data collected, saving on time, data transmission costs and device storage.