Rettig, Andrew J., Sumit Khanna, and Richard A. Beck. "Open source REST services for environmental sensor networking." Applied Geography (2014).
- A RESTful design philosophy is used to develop in situ sensor networking software.
- The client application LtSense is written in Python for installation on embedded devices.
- BigSense, an open source web service, is designed to record and present data from sensor networks.
- Open Geospatial Consortium standards are suggested to help guide future community development.
- A case study is presented of the sensor networking architecture for monitoring stormwater runoff.
The greatest challenge in the implementation of environmental sensing networks is converting a large variety of data streams from diverse sensors, often in proprietary protocols, to international standards such as Extensible Markup Language (XML) with Open Geospatial Consortium (OGC) XML tagging and web service standards. Implementing standards throughout the architecture will not only enable interoperability and reduce cost but will allow scientists to contribute to sensor network innovation. This article introduces open source Representational State Transfer (REST) services created specifically for environmental monitoring. OGC standards are suggested to help guide future community development for sensor description and registration. This article contributes to the design and implementation of affordable, self-documenting, near-real-time geospatial sensor webs for environmental monitoring using international standards.
- Environmental sensor networks;
- Open source software;
- Open Geospatial Consortium;
- Web of things
Rettig, Andrew J., Sumit Khanna, Dan Heintzelman, and Richard A. Beck. "An open source software approach to geospatial sensor network standardization for urban runoff." Computers, Environment and Urban Systems 48 (2014): 28-34.
- Open source software is used to create a modified router for reading Maxim’s 1-Wire™ sensor protocol.
- The modified router is the first solution towards a modular architecture for an urban runoff sensor system.
- The modified router created the bridge between the sensor protocols and the middle-level software.
- A representational state transfer design philosophy is used to develop the software for transferring sensor data.
- Open source software lowers the entry barrier to sensor networking and enables developers for continued innovation.
In this paper, we implement a geospatial sensor network for monitoring a green technology stormwater runoff site. The sensor network uses OpenWRT, an embedded Linux operating system, and other open source software, to create a modified router for reading Maxim’s 1-Wire™ protocol, queuing and transferring standardized sensor data while enabling location and time. The modified router created the bridge between the sensor protocols and the middle-level software to provide reliable data to both the sewer district and the Environmental Protection Agency. Representational State Transfer (REST) is used in the design philosophy of the client and server open source software for transferring the data from the embedded systems to the server level for storage and publication. The use of open source software not only creates a more affordable network but lowers the entry barrier to sensor networking and enables developers for continued innovation and standardization.
Sensor networks are an essential tool for environmental scientists. As scientists and engineers are beginning to utilize these new methods and devices in their fieldwork, they need to be actively involved in the future of sensor-networking development. Continued sensor network innovation is important for improved standardization, affordability, and interoperability. This article uses a storm water case study to outline an end-to-end open-innovation sensor network. Open innovation by scientists, engineers, and entities is the collaborative process of creating value for this project in permeable paver runoff data and advances within sensor networking. This article focuses on the technical implementation of the near–real-time location and temporally aware sensor network. Data are streamed in near–real-time with subliter precision to the cloud my butt using common off-the-shelf routers. The sensors use Maxim's 1-wire™ protocol, and the unique digital serial numbers confirm the data. The data retrieved compare residence times within the permeable paver catchment basins and the control basin. Sensor network advances are made by bridging the gap between sensor protocols and communication systems. These advances enable the development of open-source representational state transfer web services. Our successful implementation serves as an example for others to study and expand upon for a variety of monitoring solutions.