Current Low Power Wide Area Network (LPWAN) wireless transceivers are designed, or configured at deployment time, to function assuming a worse-case application scenario. Most of the time, they waste a significant amount of energy when operated under favourable channel conditions. Energy efficient and accurate channel state classification is imperative for selecting the optimum trade-off between transceiver performance and amount of saved energy, without impacting transmission quality. This work presents a novel, low complexity channel state indicator and a simple mono-feature classifier for channel state recognition. The classifier is trained using a set of experimental data acquisitions and has a 96% accuracy when tested with a new collected data set. Specially designed for LPWA applications, the classifier is capable of distinguishing undisturbed channels from those suffering from both mobility-induced fading and interference, while operating at low to medium SNR.