OPEnS Hub - A Real-Time Decentralized Internet Portal, Connecting Field
Sensors to Google Sheets
Abstract
Advancements in sensing technology have sparked a new age of data
acquisition and transmission that continue to change the way we
understand the world around us. In earth science, we often must move and
store tremendous amounts of data from remote locations. Present options
are limited to costly propriety devices, which are rigid in structure
and have numerous expenses associated with their use. The solution
developed in the Openly Published Environmental Sensing Lab (OPEnS) at
Oregon State University, was to employ a new methodology using
low-power, open-source hardware, and software, to achieve near-real-time
data logging from the field to the web. This new approach simultaneously
lowers the cost of experimentation and data collection and breaks down
traditional technical barriers. Data can be collected remotely from
nearly anywhere on Earth using a decentralized OPEnS Hub which can
utilize a host of low bandwidth transmission protocols and modes of
communication, such as: 900 MHz Long Range Radio (LoRa) with a
transmission distance of up to 25 km, the Global System for Mobile
communications (GSM) using well established cell network infrastructure,
Wi-Fi for high bandwidth applications, and Ethernet where LAN
connections are available. It is notable that LoRa technology is still
developing and has been expanded to transmit to an ever-growing
constellation of satellites, making this technology truly global in its
applicability. The OPEnS-Hub is capable of mesh networking with other
nodes and will parse and back up the data to an onboard microSD card. By
first exploiting a free open-sourced Application Programming Interface
(API), PushingBox, acting as a data broker, and secondly, a customized
Google App script, the OPEnS-Hub was able to achieve a dynamic, low
latency portal connecting to google sheets. These methods working in
tandem allowed for near real-time data logging of over a dozen devices
each with unique sensor suites to form valuable time series data. This
poster details our methods and evaluates the application and development
of PushingBox’s API, Google App Script, Adafruit’s open-hardware Feather
development boards, the Hypertext Transfer Protocol (HTTP) and various
modes of data communication used to collect nearly half a million data
points dispersed across remotes sites in the state of Oregon to date.