Profitability ranking of precision agriculture measurement system implementation

Precision Agriculture (PA) methods are adapted to various agricultural branches. One of the PA tasks is to continuously collect real time data about agricultural objects to monitor the object behavior and state of development to recognize any anomalous event or important state. In many cases the objects could have many different important parameters and the farmer has to decide which parameter should be monitored and which measurement system implementation will give the best return of investments (ROI). A formal method for profitability ranking of precision agriculture measurement system implementation is proposed. The method calculates the ROI coefficient of measurement system implementation taking into account gains and/or losses of recognition of different object states, the expected frequency of events, probability of their correct remote recognition by a particular measurement system and the costs of the system implementation. The unit of ROI is a number of years, and it expresses how fast investments for implementation of the specific measurement system will be returned. Based on the proposed method the farmer will be able to evaluate all theoretically possible measurement systems and evaluate which one is more suitable and more effective for practical implementation. The proposed method can be used in different precision agriculture branches. The method is demonstrated on an example from Precision Beekeeping (Precision Apiculture) field ranking bee colony level measurement and monitoring systems for remote recognition of swarming, theft and death of honeybee colonies. Software SEPA (System Evaluator for Precision Agriculture) for support of the proposed method is demonstrated.