Rivernet - A Wireless Sensor Network for remote monitoring of riverbed ecosystems
Given the growing global importance of water issues caused by dwindling water resources
and global climate change, building and deploying a real-time sensing infrastructure across water
bodies - including rivers, streams, and watersheds - will be one of the great scientific hurdles
and also one of the great research opportunities of the next several decades. Despite numerous
technological advances in the area of sensors and wireless sensor networks, a chasm separates
what is offered by off-the-shelf wireless products and what is needed by scientists for robust, easy deployment of a monitoring infrastructure over running waters. As a result, the vision of real-time data continuously streaming from remote sensors to the laboratory servers remains elusive
for most scientists today.
To facilitate research in water-based sensor network deployments, we are developing hardware and software systems that give the following capabilities:
- Support for a diverse array of sensors. River scientists are interested in many different aspects of river ecology. A non-exaustive list of desirable sensors includes underwater digital cameras, hydrophones (underwater microphones), water quality sensors, thermometers, and geological imaging equipment.
- Robust energy harvesting capabilities. The effort involved in deploying water based sensing equipment motivates a perpetually operating sensor network. Our prototype system has the ability to harvest solar energy and recharge a Lithium-ion battery. Energy monitoring hardware allows system performance to be scaled depending on the availability of solar energy.
- Hardware that supports performance scaling. Our system prototype uses low-power but computationally-limited hardware to control higher-power but more capable hardware. A low-bandwidth, long-range radio is used to schedule the usage of an 802.11 radio and Linux-based microcomputer.
- Remote troubleshooting capabilities. When networks become large, the capability of quickly identifying a faulty node becomes increasingly important. The ability to diagnose and correct troublesome software over a control channel is also desirable.
We plan to acquire, build and deploy a solar-powered river sensor
network over a four mile stretch of Fort River in Amherst (see Figure
below). We have permission from the Town of Amherst's Conversation
Commission to deploy this equipment and conduct studies. This local
river is routinely used by scientists at UMass and other local
colleges for a variety of research and educational activities, and
thus is an ideal site for our testbed. Broadly our testbed will
involve (i) a network of shore-based solar-powered wireless mesh nodes
and wireless gateways, (ii) solar-powered multi-radio sensor platforms
for opportunistic and robust data transmissions, (iii) interface
boards and sensor platforms for data acquisition from monitoring
sensors, and (iv) support infrastructure. The figure below illustrates
our planned deployment.
The testbed will connect to the Town of Amherst public mesh
network; the Town of Amherst IT department has q deployed one Cisco
access point on Fort River for this purpose and our testbed will
provide four additional access points over the 4 mile stretch to serve
as Internet gateways. In addition to enabling CS research, our
testbed will enable scientists to investigate patterns of flows
(surface and subsurface), velocities, depth, temperature, sediment,
light penetration, dissolved oxygen, phosphorus, bacteria as well as
fish movements patterns, community structure and biological
interactions such as prey-predator, spawning migrations.Our users
include the Rushing Rivers
Institute and the The
Environmental Institute at UMass.
Pictorial depiction of the river sensor network testbed and
the Fort River venue for its deployment.
Energy Harvesting Node (Slightly smaller than a shoebox)
Modified Pelican case containing underwater camera
designed an energy-harvesting capable node that will enable the
exploration of the goals mentioned above. More details of the hardware and sensors are available here.
Christopher Vigorito, Deepak Ganesan and Andy Barto, Adaptive
Control for Duty-Cycling in Energy Harvesting-based Wireless Sensor
Networks, Proceedings of the Fourth Annual IEEE
Communications Society Conference on Sensor, Mesh, and Ad Hoc
Communications and Networks (SECON 2007), San Diego, CA, June
2007. Best Paper Award.
©2008 Sensors Lab, Computer Science Department,
University of Massachusetts Amherst