In　recent　years,　the　development　of　cloud　computing　and　big　data　technology　has　promoted　business　model　changes　and　productivity　development　in　more　and　more　industries.　Traditional　agriculture,　especially　the　production　process　of　agriculture,　requires　manual　processing　in　most　of　the　links,　resulting　in　low　efficiency　and　failure　to　detect　abnormalities　in　the　crop　production　process　in　time.　Based　on　this,　this　article　analyzes　and　designs　an　agricultural　production　monitoring　cloud　platform,　and　uses　big　data　technology　and　machine　learning　technology　to　complete　the　storage　and　analysis　of　massive　crop　data.　Provide　agricultural　producers　with　visualization　of　crop　growth　monitoring　data　and　early　warning　of　abnormalities　and　smart　suggestions.　And　ultimately　promote　the　development　of　agricultural　productivity.　©　2022　IEEE.