This paper develops an Internet-of-Things data highway embracing end sensors, sensor nodes, databases, big data processors, web connections, and high-end statistics engines. It is aiming at automatic, pseudo real-time, and integrative sensor stream processing, fully benefitting from the capability of sophisticated statistics packages supporting a variety of artificial intelligence and data mining libraries. Specifically, Raspberry Pi nodes capture signals from attached sensors via GPIO interfaces and insert into a remote MySQL database table using its connector utility. In the Linux machine, the table entry is purged at each fixed time and dumped to a text file for a later batch analysis using Hadoop. The R package running in a Windows PC periodically downloads the sensor stream from the database table via the implementation of a library extension invoking relevant operating systems calls. In the R space, even a spatial analysis and visualization can be provided comprehensively.