lesson 2b - emerging sensors · • tools available: camera, gps, data management apps • data...

Lesson 2b - Emerging Sensors

• Mainly we have discussed sensors for physical and basic chemical properties

• This section discussions advanced sensors under development, including: – Miniaturization of existing sensors

– Biosensors – These sensors typically use molecular biology approaches to identify organisms or specific molecules

– “Ruggedized” instruments – These are conventional instruments made ready for use in harsh, field conditions

– Lab-on-a-chip – These sensors aim to scale-down conventional laboratory instruments for use in the field (so as to be less expensive)

– Imagery sensing – This technique uses data-mining techniques to extract useful information from images

– Participatory sensing – This technique employs smart phone hardware and social networking to achieve monitoring objectives

IITR UCM NI Water Sustainability & Sensor Networks Course

Chemical sensor availability and

cost

Parameter

Field-

Readiness Scalability Cost ($)

Dissolved Oxygen High High 800–2,000

Electrical Conductivity High High 800–2,000

pH High High 300–500

Oxidation Reduction Potential Medium High 300–500

Major Ionic Species (Cl-, Na+) Low–Medium High 500–800

Nutrients (Nitrate, Ammonium) Low–Medium High-Low 500–25000

Heavy metals Low Low NA

Small Organic Compounds Low Low NA

Large Organic Compounds Low Low NA


Miniaturization of existing sensors

• Smaller generally means mass production is possible, so costs are reduced

• This means we can place more sensors spatially for the same budget

• For simple sensors, this has been highly successful

• For more complex sensor systems (moving parts, etc) become more challenging

Traditional weather station sensor system

Vaissala WXT510 (no moving parts)

Miniature temperature, humidity, light loggers


Example: Miniaturizing nitrate (NO3-) sensors

• Good – Fast analysis – Stable when stored under ideal

conditions – Easy to make and miniaturize – No power needed for

measurement • Bad

– Detection limit is…limited (2 or 3 ppm as nitrate) without amplification

– Notorious calibration drift – Linear with the logarithm of

concentration…so a little drift means big errors

1

logC

C

Fz

RTEMF x

x

Slope = 59.6 mV per log interval or monovalent ion


Example: Miniature nitrate sensor fabrication efforts

7 mm diam. carbon

fiber-based nitrate

microsensor

Bendikov et al. Sensors and

Actuators B: Chemical (2005; 2007) Allen et al. Bioscience 57(10) (2007)


Still challenges with mini-nitrate sensors

• Temperature changes the calibration

• Competition with high concentrations of other anions, such as chloride

• Each sensor is slightly different, so calibration is a lot of work

• Need to add microfluidics and automate some of the calibration and conditioning actions

Current field prototype

Data-logger battery + signal conditioner sensors


Miniature & biosensors: Much basic research recently

• See: Chemical Reviews special issue Feb 2008 – Optical Chemical Sensors, McDonagh et al. [288 refs] – Potentiometric Ion Sensors, Bobacka et al. [324 refs] – Chemical Sensors with Integrated Circuits, Joo and Brown [115 refs] – Surface Plasmon Resonance Sensors … Chemical and Biological Species,

Homola [335 refs] – DNS Biosensors and Microarrays, Sassolas et al. [444 refs]

McDonagh et al. Chemical

Reviews, 2008, 108(2)


Biosensors are advancing rapidly

• Publications on biosensor development using DNA array technology

• What does this mean?

• DNA Hybridization is generally the mechanism here – This is the process of

establishing a sequence-specific interaction between two or more complementary strands of nucleic acids into a single hybrid

– The hybridization results in a signal transduction (such as electrochemical (most common), optical, or piezoelectric)

For review of recent research, see: Sassolas et al (2008) (however, this topic is beyond the scope of this course)

publications for DNA

biosensors and

microarrays


DNA/Biosensor example

DNA detection utilizing a chrono-coulometric detection method Redox-cycling current is detected at the electrodes over time – when labeled target DNA is hybridized with the probe DNA, current change occurs

Schienle et al. IEEE J. Solid-

State Circ. (2004)

chip dimensions: 6.4 x 4.5 mm

Sassolas et al. Chemical

Reviews (2008)


Challenges to creating useful biosensors

• Not the molecular biology!

• Sample preparation – Collecting and processing

the environmental sample (perhaps concentrating the sample)

– Avoiding system fouling or clogging (filtration)

• Example at right is the award-winning Environmental Sample Processer (ESP) developed by MBARI (Monterrey Bay Aquarium Research Institute)

See an illustration of how it works here: http://www.mbari.org/ESP/espworks.htm

Obviously, the system is still quite large—fine for the ocean, but not so good for a small stream


http://www.mbari.org/ESP/espworks.htm

Imagery sensing

• For larger organisms in the water (phytoplankton, algae, etc), images can serve as sensors

• Flow-thru instruments: – FlowCAM: phytoplankton,

etc. by image recognition • Surrogates

– Fluorescence (Chlorophyll, CDOM, etc.)

images from:

Fluid Imaging Technologies


Example: Processing images to monitor seasonal change

(biologist + computer scientist)

Images segmented into evergreen, deciduous and understory

vegetation types; excess green (EG) calculated for each pixel

Winter Fall

Spring Summer

Readily available webcam images provide a mean to daily monitor

changes in the phenology of plants

Work by Eric Graham UCLA/CENS


Deciduous Evergreen Understory

Seasonal changes in plant phenology:

global change monitoring

Ground-based data to link with remote sensing imagery

Work by Eric Graham UCLA/CENS IITR UCM NI Water Sustainability & Sensor

Networks Course

Example of imagery sensing: Solar radiation on a river • Solar radiation heats the water and drives photosynthesis • We can casually observed it, but can we quantify it?


Example continued: combine camera and self-logging light (visible) sensors

camera

Self-logging temp and light sensors

Use the camera a sensor for irradiance, validating with an array of light sensors


We had one PAR sensor (in the center of the cross-section)

• Not a lot of points, but the “best correlation” here is between morning PAR and GPP • Temperature plays an important role too as this shallow river heats quickly and unevenly


Some early results look promising (but this is another story…)

17：05 17：35

Shadow changes

Light sensors above and below water surface


Participatory Sensing • Participatory sensing puts humans in the sensor loop using smart

phones

• Tools available: camera, GPS, data management apps

• Data volume could be huge if many people participate


Open Data Kit (ODK) is a free and open-source set of tools which help organizations author, field, and manage mobile data collection solutions. ODK provides an out-of-the-box solution for users to:

• Build a data collection form or survey; • Collect the data on a mobile device and send it

to a server; and • Aggregate the collected data on a server and

extract it in useful formats.

http://opendatakit.org/ http://naturemappingfoundation.org/

Example app for mapping biodiversity:

http://opendatakit.org/

http://opendatakit.org/

http://naturemappingfoundation.org/



Example: Invasive species

• What’s Invasive app

• US National Park Service and others are using it to map invasive plants and animals


http://whatsinvasive.com/

Mapping observations in space, showing who

provided the data



Example: Participatory Sensing in Water

McConnell SP

SJR confluence


We can combine images with chemical observations (bathymetry, temp, DO, salinity, nitrate, DOC/TOC)

McConnell SP

SJR confluence


Summary: Emerging Sensor Technology • Miniaturization of existing sensors

• Biosensors – These sensors typically use molecular biology approaches to identify organisms or specific molecules

• “Ruggedized” instruments – These are conventional instruments made ready for use in harsh, field conditions

• Lab-on-a-chip – These sensors aim to scale-down conventional laboratory instruments for use in the field (so as to be less expensive)

• Imagery sensing – This technique uses data-mining techniques to extract useful information from images

• Participatory sensing – This technique employs smart phone hardware and social networking to achieve monitoring objectives

IITR UCM NI Water Sustainability & Sensor

Networks Course

lesson 2b - emerging sensors · • tools available: camera, gps, data management apps • data...

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