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The principles of Precision Agriculture (PA) can be applied also to the beekeeping branch. Precision Beekeeping (PB) (Precision Apiculture) can be implemented as a three phase cycle including 1) data collection, 2) data analysis and 3) application. The first two phases are based information technologies in case of remote recognition. The third phase is realized manually according to the decisions made after data collection and analysis. This study is dedicated to the information processing approaches taking into account the peculiarities of the beekeeping branch. Classification of deviations at several levels is proposed: colony level (most colonies in the same location behave normally); apiary level (most apiaries at other locations behave normally); bee farm level (most apiaries of other bee farms behave normally) and regional level (most bee farms in the region do not behave normally). Two levels of information analysis are suggested: bee farm level (information about individual colonies in different apiaries) and regional level (summary of information collected at the level of bee farms). Decision support systems (DSS) are proposed to automate data analysis. Continuous operation and high processing capacities of electronics can significantly improve implementations of PB. DSS may be delegated to make some decisions automatically or request the analysis of proposed decision by a specialist in data processing or beekeeper.

Information processing for remote recognition of the state of bee colonies and apiaries in precision beekeeping (apiculture)