STaaS: Spatio Temporal Historian as a Service

Applications of geospatial big data in the Internet of Things

“…IoT objects generate a massive amount of potentially spatiotemporal data on the environment in which they are placed (Ding, Xu, & Yang, 2013). The increasing number of sources, such as social media, smart energy meters, geolocated sensor networks, and satellite images, has resulted in a rise in the volume of data in IoT applications and can imply a growth in the spatiotemporal data from the monitored objects (Chen et al, 2015).…”

“…The OGC (2000) proposed Geography Markup Language (GML; see also Luan et al, 2015;Cai et al, 2016). There is also applicability for JavaScript Object Notation (JSON; Benedusi et al, 2015;Chen et al, 2015;Chianese et al, 2017;Crockford, 2000;Gupta et al, 2020;Leung, Braun, & Cuzzocrea, 2019;Qader & Hristidis, 2017;Suárez et al, 2015), a format for storage and exchange of data; GeoJSON (Butler et al, 2016;Işikdağ, 2020;Kraft et al, 2019), a JSON variation oriented to the codification of geographic structures; and…”

“…Notably, the relational model of PostgreSQL and its spatial extension, PostGIS, have been used in many works (Anejionu et al, 2019;Ding et al, 2013Ding et al, , 2014Voland & Asche, 2017). Other relational databases were applied in the studies investigated, such as Microsoft SQL Server (Wen et al, 2016;Xuyao et al, 2013), VoltDB (Rathore et al, 2016), and Informix (Chen et al, 2015). Along with geospatial extensions of relational database management systems, geographic information systems such as ArcGIS For the processing of massive data, cloud computing has proved to be a viable alternative.…”