Sensor Networks for Experience and Ecology

Wetlands are critically important ecosystems, providing numerous benefits to the global environment. As cranberry farms in southeastern Massachusetts come out of production, many are undergoing active restoration with the goal of returning them to functional wetlands. This is a developing practice, and we are still learning about techniques that lead to the most favorable outcomes. It is also a disruptive process that brings significant and very visible changes to the landscape. But the process of wetland restoration and the restored wetlands themselves present fantastic opportunities for learning and enjoyment.

In this dissertation, I present a custom sensor network installed at the Tidmarsh Wildlife Sanctuary, a former cranberry farm in Plymouth, Massachusetts that underwent active restoration in 2016. This network combines hundreds of custom low-power environmental sensor nodes with high-bandwidth continuous audio and video streams and the required supporting communications and data storage infrastructure.

As a permanent fixture of the site, the network was designed to serve multiple functions, making Tidmarsh a testbed for many ideas. Long-term continuous monitoring, both before and after the restoration, allows us to observe changes that take years to decades and answer questions about restoration techniques and outcomes. Broad sensing capabilities allow us to make observations and gather data about questions we may not have thought to ask. Real-time data streaming and access protocols allow us to build novel ways of
exploring and experiencing the site, both while physically present and remotely. Rich media streams enhance these experiences and allow us to assess complex factors such as biodiversity.

I describe the design, implementation, and deployment of two generations of custom wireless sensor hardware and the supporting network infrastructure; a multi-channel audio streaming installation; and a setup for video streaming and timelapse recording. I demonstrate how the network is used for scientific research through an experiment to determine the impact of microtopography (a restoration technique) on soil hydrology. Finally, I enumerate the many projects that have made use of the network to learn from the data and connect people to restored wetlands through novel experiences and creative expressions.

Exploded view of a Tidmarsh sensor node.


Brian Mayton. Sensor Networks for Experience and Ecology, Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, September 2020.
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Brian Mayton


MIT Media Lab