Considerations for system design in IoT-based autonomous ecological sensing

The level of global GHGs (Green House Gasses) production has increased dramatically over the past 20 years. To meet new targets for global GHG levels, it is key to monitor and model the effects of land use on GHG production. Peatland areas play a significant role in GHG modeling. Recent research in the area has been working to provide solutions to better monitor the environment through the provision of real-time data streams on key drivers of the environment. The Internet of things (IoT) technologies has found application in peatland monitoring as it provides useful tools to better monitor the environment. Current IoT systems, however, are too expensive to be deployed on a scale that would allow for refined monitoring of the biodiverse region. Also, deployment of IoT sensing devices requires expertise and specialized equipment resulting in prohibitive costs for many sites. Furthermore, there is no formalized architecture in existence for the application of ecological surveying and no complete system have been developed for data handling and analysis. This paper therefore aims to detail a system that enables cost-effective collection, curation and processing of data in peatland areas, however, the system can be generalized for any environmental monitoring case.