A stochastic approach towards inclusive rural development using demographic data

• Published in: 2015 IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR) pp. 102 - 105
• Main Authors: Mukundaram, P., Pravien, M., Thilak, P. Ram
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2015
• Subjects: Agriculture; Conferences; demography; Productivity; rural development; Sociology; Statistics; stochastic approach; Stochastic processes; Technological innovation
• DOI: 10.1109/TIAR.2015.7358539

Technology has advanced immensely in India in the recent years but its advantage has not been wholly utilized by the rural parts of our country. Villages hold a diversified job environment where most jobs can be made highly profitable by establishing proper communication among various professions. Information awareness in cities is playing a major role in improving small scale businesses which is missing in villages. This can be achieved by using appropriate use of available technology in villages which will help us determine correlations in rural India. A demographic analysis using stochastic mechanisms focusing on specific aspects can be used to learn about villagers and target appropriate methods to improve their lifestyle by the application of technology. We attempt to extract the demographics (like age, gender, place, skill sets) of a person and find various overlaps of his/her job nature with other professionals in a specific geography. This analysis would give us insights on a lot of interrelations among the various professions which can be exploited to maximum extent so that we achieve higher levels of productivity. A stochastic approach on the demographic data can be used to achieve this and thereby we can expect an inclusive rural development. Since, there are high levels of uncertainty on a variety of parameters we go for a stochastic approach to carry out our analysis. If we take probability theory into consideration, a purely stochastic system is one which is randomly determined and also has a random probabilistic distribution. The pattern which is derived from this system can only be analyzed statistically but cannot be accurately predicted. The probabilistic patterns obtained finally would provide us insights of how rural development is being carried out in a village and what factors should we need to focus on a that village to ensure wholesome development.