The ratio of nurses and doctors to patients keeps diminishing due to increasing population health needs, however it is expected that the quality in healthcare services increases. By merging Ambient Intelligence (Ami) and semantic web technologies, PINATA aspires to address this issue. PINATA utilises pervasive devices to aid doctors and nurses to focus on the patient and thus improve the quality of healthcare services. In this paper we go over comparable Ami system architectures; summarise the physical and logical design of PINATA; provide details of the knowledgebase modelled in RDF/S and the ontologies designed for units of interest, including resources, and context-related concepts. These individual models are unified into a connected, context-rich data model through another set of classes and properties. The results presented were based on several tests done and are very promising.