Through our efforts in sensor network research, we are investigating the adoption of a variety of networking and sensing technologies to better observe a variety of ecological phenomenon. These efforts include:
The Use of Opportunistic Networking for Smog Monitoring.
The goal of this project is to create a low-cost environmental monitoring station that leverages existing network connectivity. The ideal solution would permit interconnection with different network types and powering options and would include O3, NOx, and CO gas sensors; temperature, humidity, and barometric pressure. Sensors are controlled and sampled by a microcontroller which stores data locally and then transfers data via 802.11 or GSM (GPRS or EDGE) to a server located on the public internet. Once connected to the internet, the unit reports current conditions and thus is an example of the enabling of large scale monitoring of urban microclimate and air pollution.
With a simple and low cost design, devices will be easily deployed in any setting with a wireless access point, thus permitting their widespread adoption. When connected, there data will be published on a web site to permit public access or scientific analysis and will support general awareness of air quality issues with real data. Our current implementation is the result of a Senior Design effort by George Bishop, Peter Dib, Brandi Pitta, and Noam Yemini. See Opportunistic Pollution Monitor.
Pervasive Ecological Video Sensing
Sensor networking and video data streaming represent two maturing technologies for scientific observation and data collection with very different technical requirements. The former is designed assuming large numbers of units and long-term deployment in settings with small data generation rates. The latter can provide rich visual detail in collected data but requires significant energy resources to sustain data recording, communication, and storage. The research in this project seeks to enable networked video cameras to operate within sensor network constraints: at low energy consumption, in remote un-tethered settings, and in large spatial measurement scales.
The work is motivated by collaborations with ecologists and biologists that reveal many opportunities for the observation of species behavior that are characterized by events that are disturbed by human presence, are remotely sited, require long periods of waiting or require large, detailed area coverage. Detecting, recording, and streaming to enable scientific discovery in these settings can expand our understanding of the environment.
The project involves the development of a novel low-cost video sensor that operates on energy harvested from the environment and supports spatial and temporal sub-sampling of the camera field of view. Complementary research thrusts include the investigation of localized and cooperative in-network image analysis, data compression, and network path formation to enable delivery of video data to an outside observer while minimizing contention caused by multiple streams.
Coastal Ecosystem Monitoring with Video Networks
We are demonstrating the use of video in remote settings in pilots at the University of Massachusetts Field Station and at the Coskata-Cotue Wildlife Refuge, both on Nantucket Massachusetts. These sites are remote, possess a great variety of wildlife and features of interest, and are suitable for networks of video cameras. In association with the University of Massachusetts Field Station we have developed an underwater housing for our IP camera and plan to provide observation, live to the internet, for estuary activities.
In the summer of 2009 we deployed an additional solar-powered video camera at the Great Point Lighthouse on Nantucket Massachusetts. This camera will be used for (among other activities), the observation of a resident population of harbor and gray seals. The camera is remotely sited with communications bridging nine miles of Nantucket Sound. Stills from the camera are recorded at regular (1-10 min) intervals and are maintained in our image database in the cloud.
Relevant publications and links:
The Monitoring of Bat Habitats with Wireless Motes
This effort involves the evaluation of in-network belief propagation algorithms and their efficacy as triggers in a deployed sensor network. This technique is a foundation for our system comprised of event triggering and attribute-based routing for the purpose of achieving sensor net longevity. Undergraduates Johnathan Tang and Meghan Ryan were engaged in the application and use of a wireless sensor network for data collection for the study of the habitat of bats in several settings (barn roost and bridge roost) and to study impulse behavior in photosynthesis in an ecological research area (tree hydrology). The intent of this work has been to involve both specialists (engineers) and non-specialists (domain scientists) in the use and deployment of the wireless sensors. See Prototype Wireless Sensor Network for Ecological Study: REU Summary Report.
Video Observation of Bats
We have installed an IP-based IR video camera at Moore State Park in Paxton MA. This camera can be found here:
Rooftop Solar Monitoring for Improving the Performance of Solar Panel Arrays
For rooftop photovoltaic systems, the industry is keen on maximizing the energy production per dollar invested. One way of assuring maximum energy from an installation is through environmental feedback. Once systems are installed, the only measurement of performance involves a single sunlight sensor and an overall system AC kilowatt-hour meter. Performance degradation occurs when the real-world environment changes over the course of a year. Typical degradation comes from shading from obstructions due to changing sun-angle, soiling, temperature variations, installer errors and solar module performance.
We envision a network of sensors that would provide a two-dimensional grid of information. Adding time values to the data allows for a precise analysis of a grid of photovoltaic panel rather than the traditional single point evaluation. We also desire the sensors to provide enough information for a base station to map out their relative locations. Using the rising sun as a known event, the base station can establish sensors' east-west locations. North-south locations may need a proximity measurement.
We implemented a solution to this problem using a network of wireless motes as part of a Senior Design effort. The system is described here: Rooftop Solar Monitoring System.
Soil moisture monitoring of individual plants.
In this effort we seek to create a low-cost wireless sensor unit that can monitor soil moisture per plant in a home or greenhouse application. The device is intended to (a) measure and report, via mesh network, to a base station, and (b) provide a visual indication when an individual plant requires irrigation (so that it may be quickly located). The project includes the design of an integrated soil moisture sensor using an extension of the PCB and weatherpoof packaging to permit operation outdoors. The device is designed to operate in a standalone or mesh configuration.
In the mesh configuration, the devices relay data sampled periodically by each device and report to a data collection point provided by a laptop. Relayed data includes soil moisture, photosynthetic light, soil temperature. The base laptop performs logging, calibration, analysis, and visualization in real time. See WiGreen Soil Moisture Monitoring System.