Rivernet - A Wireless Sensor Network for remote monitoring of riverbed ecosystems

Overview

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:

  1. 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.
  2. 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. 
  3. 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.
  4. 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.

Deployment Site

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 Design

Harvesting node picture

Energy Harvesting Node (Slightly smaller than a shoebox)

Underwater Camera Picture

Modified Pelican case containing underwater camera


We have 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.

Publications

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.

People

Prashant Shenoy
Deepak Ganesan
David Irwin
Jeremy Gummeson
Navin Sharma
Timothy Somerville


2008 Sensors Lab, Computer Science Department, University of Massachusetts Amherst