Learning automaton based context oriented middleware architecture for precision agriculture

The continuous alteration of living landscape in earth due to the greatest impact of information technology has converted the whole earth into a small digital village. That means anyone could share information in any form with any other person residing anywhere in the earth. With the availability of information and communication technology like cloud computing, heterogeneous networking, crowd sensing, web services and data mining, anywhere and anytime information sharing is possible, but this will bring out lot of challenges like incompatibility in standards, data portability, data aggregation, data dissemination, differential context and communication overhead. The ICT has changed many aspects of human lifestyle, work places and living spaces. However, there is one sector namely agriculture which has been deprived of the real advantages of ICT. Hence, there exists a digital divide between farming industry and other industries. Farming industry consumes large amount of natural resources such as water, energy and fertilizers that could escalate issues such as global warming, soil degradation and depletion of ground water to the next level. To reduce the global warming effect, farming industry needs to be integrated with relevant technologies. This paper proposes ubiquitous context oriented middleware architecture for precision agriculture (LA-COMPa) to solve major issues such as waste of water, improper application of fertilizer, choice of wrong crops and season, poor yield and lack of marketing.