Environmental Monitoring Workgroup Report

Environmental Monitoring? ► It’s more than just biology ► Three classes:  Ecophysiology ► Looking for everything, later analysis  Public Health – “Environmental Alarm System” ► Looking for specifics, threshhold detection  Controlled Agriculture ► Looking for specifics, automatic response

App Ideas ► Public Health  Soil nitrate flow monitoring  Municipal water system quality  Disease tracking in animals ► Controlled Agriculture  High-density sensing and control ► What can be gained by instrumenting “every plant, stem, and leaf”? ► Limited by precision of response

Technical Challenges ► Question really isn’t: “what are the remaining technical challenges?” ► It’s really: “what has actually been solved?”  Single Hop Data Collection ...anything else?

Key Challenges ► Calibration ► Management Tools ► Combination of data from remote sensing with wider systems (e.g. GIS) ►...and, as always, cost

Calibration ► All three app classes expect accurate data ► Calibration must be an ongoing process, executable in situ  But, sending a person to “wipe the dust off the lens” is not the most cost-effective option  Consider calibration to environmental reference points (e.g. the sun at high noon)  Consider mobile artificial reference points ► Self-Testing is also a key component of calibration  Detecting faulty sensors ► Compare data to ongoing baseline, or neighboring nodes

Management Tools ► We have very little visibility into the actual operation of our sensor networks  How are the sensors performing?  Is the network meeting our standards? ► Detailed event logging ► Accurate ongoing power monitoring

Data Fusion ► Sensor networks must interoperate with large-scale, pre-existing systems ► Systems must be composed of pieces running at different scales  Wider-scale systems should be able to control narrower-scale, and vice versa ► Networks should be nonuniform, in sensing density and modality

Ideas that need trying ► Tiered sensor networks ► Mobile sensing, and maintenance ► Imaging-interpretation sensors  It’s not always possible to get a simple physical or chemical sensor for every phenomenon ► More programmable or composable systems

Key Higher-Level Challenge ► Listen to your domain experts!  We cannot come up with every application  Even if you think “geez, why would you want to sense that?”  Many domain experts are used to the reliable, and clunky data collection systems ► They may prefer high data rate and reliability over small size ► Don’t have any domain experts?  Find some!