Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web

UNIVERSITY COLLEGE DUBLIN DUBLIN CITY UNIVERSITY TYNDALL NATIONAL INSTITUTE

Views from the coalface:chemo-sensors, sensor networks and

the semantic sensor web

Jer Hayes – CLARITY / IBM

Dublin, Ireland


Who?• The Adaptive sensors group (ASG) is the sensor

element of the CLARITY: Centre for Sensor Web Technologies, a joint DCU-UCD research partnership funded by Science Foundation Ireland under 07/CE/I1147.

• CLARITY is a research centre that focuses on the intersection between two important research areas - Adaptive Sensing and Information Discovery.

• IBM is a CLARITY industry partner. Various Irish-based centres under the Innovative Environmental Solutions grouping.


ASG• Novel sensing…


About me…• I currently work for IBM

within CLARITY…

Testing wireless sensor networks at sea

Remote sensing: sea surface temp.

Food technology: spoilage sensor


Outline

• Sensor networks

• Problems with sensors – bias?

• Core problems & an example sensor system

• Intelligence in the network

• Summary


Sensor networks• The semantic sensor web offers the unique opportunity

to unify the real and virtual world.

• We are on the cusp of unifying real-world and virtual world…

• Large scale sensor-networks will be built around internet-enable devices (in some cases only the base-station may be internet enabled).


Physical sensor bias• Biased towards considering sensors to be like

thermistors which is understandable as they exhibit almost ideal behaviour:– low cost, long-life, very low-power, small form factor, high

accuracy and precision, rugged, reliable, etc.

• Bias colours the expectations of SSW/WSN researchers in that they expect all sensors to conform to this ideal.

• Sensors aren’t always reliable– leaching of active components from sensing membranes,

physical damage, lack of selectivity, baseline drift and biofouling (particularly in the marine environment!).


Dealing with raw data streams

• Given any sensor we can ask - what does this data stream mean ?

• Generally speaking data streams are not self identifying

• We require outside information, metadata, to understand the stream.

• The main driver for the use of metadata so far has been data sharing.

• Scientists generate large amounts of data and often we wish to share this data with other researchers.


Data sharing…

SEACOOS:southeastern Atlantic coastal ocean observatory system

It involves 13 universities

and institutions

NETCDF file format

Distributed Oceanographic Data Systems (DODS)

Open Source Project for a Network Data Access Protocol (OPeNDAP)


Core problems from our perspective

1. The heterogeneity of data sources and data transport methods that all must neatly fit into the SSW.

2. The quality of the data must be described and understood.

3. Data streams from different sources and modalities (esp. contextual information) which vary across many dimensions, including spatial, temporal, granularity of data, must be integrated.

4. The SSW must be capable of supporting analytics (e.g. decision making) across the SSW nodes.


Phosphate system

• Component of “SmartCoast” project, which aims to develop a smart water quality monitoring system, to aid compliance with increased monitoring requirements under the Water Framework Directive.

• Phosphate is a key limiting nutrient in freshwater ecosystems.

• Eutrophication:– A major water quality problem in Ireland and many

other countries– Elevated nutrient levels lead to excessive

growth of algae and aquatic plants– Oxygen depletion fish kills– Algal blooms toxicity in water bodies


Objective and Requirements• Develop an autonomous,

remotely controlled phosphate sensor capable of monitoring PO4

3- at appropriate levels at remote locations over long deployments

• Requirements:– Sensitive– Stable chemistry– Communicate wirelessly– Low power– Robust & portable– Low cost & low maintenance

requirements


Principle of Operation

• Yellow method for phosphate detection– Forms vanadomolybdophosphoric

acid (yellow)– Absorption proportional to phosphate

conc.– Advantages

• Excellent reagent stability• Fast reaction time (minutes)

• Microfluidic technology– Minimizes reagent consumption,

storage requirements and pumping power

• UV-LED and photodiode– Low powered, inexpensive &

sensitive optical detection


Current Status• Mark II sensor designed to

build on the successes and address the limitations of the original.

• Improvements– Lower power, more flexible fluid

handling system.– More sensitive optical detection

system.– More reliable and lower powered

communications using GSM modem in SMS mode.

– 2 point calibration protocol.– Solar panel for energy harvesting

during long deployments.– Improved ruggedisation.

Yeah, so what? What about the semantic sensor web?!!!


Problems at the coalface…

1. How do we plug this sensor into a sensor network and / or the semantic sensor web?

• What? Where? When? Who?

2. What is “context” for this sensor? How do we find it and can we trust it?

• Weather? Other water quality parameters.• Data from models? Topology, soil type, land use in river basin

district…• For other sensors what “context” is could be complex.

3. Can the network control the device properly? Can it change sampling rates etc.?

• Do we just pass on data or can we control the device? Who is allowed to control it?


Problems at the coalface…

1. We are looking for a “complete picture” – so data streams will come from hardware & software, e.g. modelling.

• Air quality…• Ground based in-situ

sensors

• Remote sensing

• Models: chemical transport, weather etc.

Software sensors (Models/Database & Hardware sensors?


CH4

CO2

VOCs

Landfill gas generation

Borehole well

Gas sample extracted

Analysed using IR gas sensor

Chemometric program analyses data and decides if concentrations are within threshold limits

If thresholds are exceeded, a message to sent to personnel onsite to investigate further


Intelligence?

• OGC's Sensor Web Enablement (SWE):

Where should the analytics take place?

How do we know contextual information is accurate?

Should “bad data” be released?

Where does the landfill site fit in?


Summary…

1. Sensors aren’t as reliable as we’d like to think.• Need to account for data quality….

2. Contextual information is required for the “complete picture”.• From a large variety of possible sources…

Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web

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