Projektdaten

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Multi-Sensor Crop Monitoring for Cacao Production (SeMoCa)

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SeMoCa aims at investigating and developing a proof-of-concept prototype of a multi-sensor system that provides a digital representation (world modelling) of a cacao farm by delivering a map with a set of semantic variables. The latter might include cropping pattern (which plants bear more fruits), plagues and disease distribution (which areas are aected and to what extent) and production development (level of ripeness, fruit size, etc.). Both, accuracy of the mapping and the higher level semantic inference depend on the quality of the sensors which, in turn, is limited by the overall cost and weight requirements. This being said, our research in this project addresses methods for sensing, data fusion and orld modelling for eective cacao crop biomass and cacao fruit state estimation and mapping.