IDBR: An End-to-End Sensor Based System for Environmental Monitoring

Johns Hopkins University, Baltimore MD

Investigators

Abstract

A grant has been awarded to Drs Katalin Szlavecz, Andreas Terzis and Alexander Szalay at the Johns Hopkins University to design and develop end-to-end sensor-based systems for environmental monitoring. The recent emergence of networked sensors fundamentally changes the way we can approach many scientific problems, some of them completely intractable in the past. These networks, based on novel low-power wireless sensor platforms allow the design of affordable, non-invasive, large-scale monitoring systems. However, current systems are far from providing an off-the-shelf solution that application scientists can deploy. A long battery life for field deployment requires sophisticated algorithms to synchronize communication within the network. Attaching a variety of sensors to the network requires custom software. Communication between clusters of sensors in the field at larger separation needs long-range radio bridges. Providing an end-to-end system for the biologists requires a dynamically loaded database with high level views of carefully calibrated data, built from the raw measurements automatically. Based upon their previous work the PI?s will develop a ?user friendly? wireless network infrastructure targeted at environmental science applications. The novel features of the network will consist of a high level language to configure the network nodes for the particular sensors, modular long-range communication options, and a system with an end-to-end data flow. The end-to-end system will be first tested in two urban sites as part of the Baltimore Ecosystem Study Urban Long-Term Ecological Research: (1) an urban forest in Baltimore City and (2) in a typical suburban neighborhood in Baltimore County. This deployment focuses on the effects of land use and management and the urban heat island effect on the heterogeneous urban soil ecosystem. Understanding the many environmental problems humans face today and predicting outcomes of our actions requires long-term monitoring of many environmental factors. Established and planned environmental observatories (LTER, NEON, MOOS) reflect this need for monitoring. The high resolution data from the environmental sensor networks has the potential to transform our understanding of ecological systems. Our sensor networks will have the ability to monitor the soil ecosystem in situ. The development of the software components will enable ecologists to be in full control of their own experiments, and easily reconfigure the sensor layout without cumbersome reprogramming. This in itself will have a tremendous impact on how the experiments are designed and deployed. Sensor networks offer a rich environment for science education. They can be an inexpensive source of real, current data for K-12 and college science courses. To provide resources for such courses, the PIs will develop web-based tools and educational projects that use sensors in biology and environmental science courses at Johns Hopkins University and elsewhere. Moreover, the PIs will offer an online storage and data analysis service in which domain scientists will upload, analyze, and share the data collected by their sensor network experiments.