Smart agriculture: Predictive height analysis for universal crop health classification - Tsakiridis, Sotirios; Papaioannou, Nikolaos; Tsimpiris, Alkiviadis; Varsamis, Dimitrios; Papakonstantinou, Apostolos (My University, 2023)
The use of contemporary information and communication technol- ogy to maximize agricultural output while reducing labor costs is known as ”smart agriculture”. This term is becoming more and more prevalent. The primary challenge in the agricultural sector lies in the vastness of crops, coupled with varied topography and soil instability, making con- trol challenging. In this paper, a system for determining the average predicted height of healthy plants at a given growth stage is proposed and evaluated. Based on this height, we then classify agricultural plants as healthy or unhealthy. It’s important to note that our system works with any crop kind and growth stage.
Keywords: Unsupervised Learning; UAV; Smart Agriculture; Clustering