Improving Multispectral Image Processing for Real-Time Agricultural Indices Tracking Using an Embedded System

Recently, embedded systems have been used in precision agriculture for application control, tracking, and agricultural field monitoring. The integration of embedded systems in precision agriculture will help much better in making decision. This needs the study of such systems in terms of complex algorithms processing and results from consistency. This study requires software optimizations and hardware requirements to speed up processing times while keeping the results reliable. This work presents the evaluation of the most known vital indices in agriculture precision algorithms on a heterogeneous embedded system using the OpenCL parallel programming language. The algorithm evaluated in this work is dedicated to agricultural field tracking.

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