Mesh Wireless Sensor Networks: Will Their Potential Ever Be Realized?

Although the idea of mesh wireless sensor networks is not new, the realization of their many benefits have gone largely unrealized. The low success rate of most wireless systems makes the accomplishments of this Johns Hopkins group unique.

Soil moisture and temperature are major drivers of seasonal dynamics, soil respiration, carbon cycling, biogeochemical functions, and even the types of species living in a certain area.

The ability to measure soil moisture and temperature is vital to ecologists who work in heterogeneous environments because these parameters are major drivers of seasonal dynamics, soil respiration, carbon cycling, biogeochemical functions, and even the types of species living in a certain area.  But ecologists’ scientific understanding of environmental conditions is hindered when soil moisture measurements disturb the research site, or when field measurements are not collected at biologically significant spatial or temporal granularities. Soil ecologist Dr. Kathy Szlavecz and her husband and computer scientist, Dr. Alex Szalay, both at Johns Hopkins University, are working to solve this dilemma by testing a wireless sensor network (WSN; Mesh Sensor Network), developed by Dr. Szalay, his colleague, computer scientist Dr. Andreas Terzis, and their graduate students. These generate thousands of measurements monthly from wireless sensors. The husband/wife team says that WSN’s have the potential to revolutionize soil ecology by generating a previously impossible spatial resolution.

Architecture of an end-to-end mesh network data collection system. (Image: lifeunderyourfeet.org)

What is a Mesh Network?

In a mesh wireless sensor network, specially designed radio units (nodes) use proprietary or open communications protocols to self-organize and can pass measurement information back to central units called gateways. Different from star networks where each node communicates directly to the gateway, mesh networks pass data to each other, acting as repeater for other nodes when necessary.

These are the 37 sampling locations at the Smithsonian Environmental Research Center (SERC) in Edgewater, MD. Data from this deployment is aimed at understanding the effect of forest age, leaf litter input, and earthworm abundance on soil carbon cycling. (Image: lifeunderyourfeet.org)

With low power and reliability as their goal, they are deployed in dense networks to automatically measure conditions such as temperature and soil moisture. These node measurements are taken every few hours over several months. The data are then uploaded onto computers, where it can be maintained and searched. Kathy explains “Without an autonomous sensor system, experiments in need of accurate information about a multitude of environmental parameters on various spatial and temporal scales require a superhuman effort. The inexpensive nature of these sensors enable scientists to place a high-resolution grid of sensors in the field, and get frequent readouts.  This provides an extremely rich data set about the correlations and subtle differences among many parameters, allowing ecologists to design experiments that study not only the gross effects of environmental variables, but also the subtle relations between gradients and small temporal changes.”

Without an autonomous sensor system, experiments in need of accurate information about a multitude of environmental parameters on various spatial and temporal scales require a superhuman effort.

Landscape Studies Benefit from Mesh Networks

Kathy and Alex have deployed mesh wireless sensor networks at several study areas around the state of Maryland.  Kathy says, “Once we record the measurements, we can combine that information with observations of soil organisms to better understand how soil organisms and the soil environment interact. This means we can make better predictions about how human activities will affect the soil environment.” In one urban landscape study, Kathy and her team deployed over 100 nodes around a CO2 flux tower looking at the two major landscape covers in an urban environment: grass and forest.  She explains, “We collected data from nodes connected to soil moisture and temperature sensors for over two years at these sites, and the system worked quite well. We collected about 180 million data points, and that’s no small feat.”

Next week: Learn the results of this research group’s mesh network testing and what Kathy thinks the future holds for this technology.

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