Smart　agriculture　can　enhance　agricultural　production　efficiency,　improve　the　ecological　environment,　and　realize　the　sustainable　development　of　agriculture.　Many　countries　and　companies　are　working　hard　to　develop　or　introduce　smart　agricultural　solutions.　Because　of　the　shackles　of　traditional　agricultural　management　methods　and　fierce　competition　with　a　variety　of　different　solutions,　it　is　a　difficult　task　for　enterprises　to　select　and　implement　smart　agricultural　solutions　smoothly.　Hence,　enterprises　must　assess　alternative　solutions　and　select　a　feasible　solution　in　advance.　This　study　drew　a　novel　assessment　and　selection　for　smart　agriculture　solutions　using　an　information　error-based　Pythagorean　fuzzy　cloud　algorithm.　First,　an　evaluation　index　system　built　on　smart　agriculture　solutions　was　constructed　from　four　aspects.　Then,　a　new　concept　of　Pythagorean　fuzzy　clouds　was　defined　to　express　the　evaluation　information　for　each　indicator.　Simultaneously,　the　Pythagorean　fuzzy　cloud　weighted　Bonferroni　mean　(PFCWBM)　operator　was　developed　to　aggregate　the　assessment　information　of　multiple　indicators.　Next,　an　assessment　and　selection　decision　framework　for　smart　agriculture　solutions　based　on　the　PFCWBM　operator　was　presented.　In　addition,　an　example　was　given　to　illustrate　the　effectiveness　of　the　proposed　algorithm.　Finally,　a　discussion　was　conducted　to　verify　the　superiority　of　our　approach.　The　results　showed　that　our　algorithm　can　characterize　and　evaluate　complex　information　and　has　high　sensitivity　and　environmental　adaptability.