Solar dryers are increasingly used in developing countries as an alternative to drying in open air, however the inherent variability of the drying conditions during day and along year drive the need for achieving low cost sensors that would enable to characterize the drying process and to react accordingly. This paper provides an approach for smart sensors that make use of the psychrometric properties of the air inside the drying chamber along day. The proposed model shows a high agreement with bibliographic dat