Real-Time Data Capture Model for Accelerated Payment of Small-Scale Farmers
Natasha Mwansa and Jackson Phiri
DOI : 10.3844/ajeassp.2018.1164.1177
American Journal of Engineering and Applied Sciences
Volume 11, Issue 3
Most developing countries especially in Africa face a number of challenges in the area of food security. These challenges include proliferation, theft, poor inventory system, poor transport and communication network. Zambia is one of the countries with these challenges and has been losing millions of dollars each year due to various challenges in managing the inventory system. In this paper, we are proposing a model for the inventory system based on Quick Response (QR) and cloud computing for real-time capture of grain bags brought in by farmers at the satellite depot. The government supplies farming input to local farmers and buys the grain back from the farmers. This study is looking at part of the buying process which requires the movement of grain from the local farmer to the government. The grain forms part of the national food storage reserve. The proposed system first requires tagging the grain bags then capture the details of the farmer and attach to the grain bags. Our proposed model based on cloud technologies is integrated with the mobile application used to read the QR code attached to the grain bags. These details are then linked to the details of the farmer in the database. These captured data regarding the farmer and grain bags supplied at the satellite depot are made available to the decision makers in real-time. Out results show that the proposed model will helps to address a number of challenges that the current system has been facing. These include accelerated process of paying the local farmers supplying grain to the government which used to take months. It will also help to give the grain stock statistics in real time per region and the country at large. This model will be very useful for most developing countries in managing their grain.
© 2018 Natasha Mwansa and Jackson Phiri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.