PMC:7796058 / 5526-6044 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7796058","sourcedb":"PMC","sourceid":"7796058","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7796058","text":"ations, and types of activities (e.g., disinfecting activities) was modelled using the IndoorGML graph data model [19,20]. This research presents the innovative use of the Open Geospatial Consortium (OGC) [21] SensorThings Application Programming Interface (API) [22,23], as well as, the IndoorGML that uses Poincare duality to geo-reference IoT sensor observations for both 3D spaces and Node-Relation graphs in topology space. Our paper also argues that the integration of the IndoorGML and SensorThings API is criti","tracks":[{"project":"LitCovid-sentences","denotations":[{"id":"T33","span":{"begin":123,"end":428},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"attributes":[{"subj":"T33","pred":"source","obj":"LitCovid-sentences"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"LitCovid-sentences","color":"#d593ec","default":true}]}]}}