Oral Cavity Cancer (OCC) is one of the most common oral malignancies which according to the World Health Organization accounts for almost 3% of all cancer cases diagnosed worldwide. More than 80% of OCC cases are preceded by manifestations of lesions especially on the tongue that are generally considered as initial signs of many systematic disorders and several oral diseases. Early screening of these tongue lesions would reduce their chances of cancerous transformation thereby increasing patient survival rate. Automating the initial screening process using trained TinyML models deployed on embedded devices or smartphones for detecting benign and premalignant oral tongue lesions can prove to be an effective and inexpensive technique; that can support physicians in their daily clinical duties to triage patients for appropriate clinical care. Such intelligent devices can be leveraged as a point of care diagnostic tool in remote healthcare clinics where access to specialized medical resources is limited.