Sensor Web Enablement of environmental monitoring and process control

By Gavin Fleming, Senior

GISc and Sustainable

Development Researcher:

Mintek

Keywords: [acid mine

drainage, EIA, EMP,

environmental impact

assessment, environmental

monitoring, GEOSS,

geospatial, GRI,

instrumentation,

interoperability, Krugersdorp

Basin, mashup, OGC,

pollution, process control,

Python, Sensors Anywhere,

Sensor Web Enablement,

SOS, standards, SWE,

TransducerML]

Adding geospatial information to measurement data provided by

instrumentation provides new and valuable insights for environmental

monitoring. Could this become pervasive in process control?

Abstract

This paper explores the potential of Sensor Web Enablement for environmental

monitoring and process control, illustrated by a mine environmental monitoring prototype

in the Krugersdorp Basin, a mineral processing process control concept and a mining

operations management concept.

The task of measuring and interpreting environmental and process variables is becoming

increasingly large and complex. Many proprietary and open technologies are in use for

observing, communicating, analysing and reporting these variables.

Several international initiatives have created the conditions for interoperability among

these systems at technical, organisation, semantic and political levels. Examples include

the Global Earth Observation System of Systems, the Open Geospatial Consortium’s

(OGC) Sensor Web Enablement (SWE) initiative and the Semantic Web.

Sensor Web Enablement allows for the integration and analysis of streams of sensor data

from multiple and diverse sensors in a standards-based and thus interoperable manner.

For instance, observations from water quality sensors can be fused with those from

weather instruments and satellite remote sensing instruments. Measurements of anything

from process or biophysical variables to higher level indicators such as re-vegetation or

landscape function and even social impact potentially can be Sensor Web Enabled.

Collection, management and analysis of these data can be automated and adaptive,

handling the disruption of service from some sensors or the addition of new sensors.

Sensor Web Enablement of mines and their entire footprints ultimately can enable greater

understanding of the systems at play by capturing their dynamics in time and space.

In the Krugersdorp Basin, disused gold mines, whose groundwater is no longer being

pumped out, are overflowing at several egress points. Acid Mine Drainage is

contaminating surface and groundwater over a large area. Water quality and quantity

sensors have been placed in six clusters throughout the system in an attempt to

characterise it, monitor compliance and to flag events that need urgent attention, such as

flow pulses or dips in pH.

In a Sensor Web Enablement prototype, these sensors have been exposed through an

OGC SOS (Sensor Observation Service), described by OGC SensorML (Sensor Model

Language) and visualised in a SOS graphing client.

1 Introduction Modern mine monitoring requirements are discussed and challenges in achieving these

are raised. Increasingly complex, onerous and costly monitoring requirements necessitate

a new approach to monitoring. Technically, organisationally and semantically isolated

monitoring systems dominate in the industry. These are generally provided by competing

proprietary vendors.

An emerging concept called Sensor Web Enablement (SWE) is introduced and described.

SWE results in interoperable monitoring systems with less redundancy and wider

application. The application of SWE in mine environmental monitoring is explored,

focussing on aspects of closure and rehabilitation. An example of SWE of a water

monitoring system in a closure situation near Krugersdorp is presented to demonstrate

some SWE concepts.

2 Monitoring challenges and solutions Mine environmental monitoring is increasing in importance and complexity. Many

governments are imposing more stringent regulations and compliance with environmental

management programmes. Mining companies monitor more for improved risk assessment

and management; they are showing greater responsibility to mine-affected communities

and are responding to shareholder activism. Comprehensive corporate reporting, such as

GRI (Global Reporting Initiative), requires extensive monitoring.

South Africa’s Mineral and Petroleum Resources Development Act (MPRDA) of 2002

specifies objectives for the monitoring and assessment of Environmental Management

Programmes (EMPs). These are to: Detect short and long term trends; recognise

environmental changes and analyse causes; measure impacts and compare with predicted

impacts; and improve monitoring practices and procedures for environmental protection

(MPRDA).An EIA (Environmental Impact Assessment) defines levels of acceptable

change of various environmental variables. These variables need to be monitored so that

the levels of change are not exceeded. The MPRDA specifies that a monitoring

programme must ‘identify trends, causes and impacts’ and ‘assess performance and

compliance’. Furthermore, Regulation 55 of the MPRDA specifies that monitoring by

mine permit and rights holders must be continuous until closure is granted, that post–

closure risk indicators must be monitored, and that measurements must be stored and

reported to National Department of Minerals and Energy (DME).

New water regulations in South Africa require that the polluter pays according to a

‘waste-discharge charge system’ (WDCS) (Moodley, 2006). A good observation

programme and associated alerts and prediction models will reduce financial risk for

mines.

Mine tailings dams around Johannesburg are a major source of radon, dust and water

pollution. Monitoring for compliance is required on a large scale. It is also required

during reprocessing and moving of the dumps to new superdumps (Anon, 2002).

While it essential to monitor during operations and closure, it is ideal to begin an

observation programme well before mining or even exploration start. The MPRDA

requires that mines be rehabilitated to their natural state. A proper observation

programme can start by helping to define what that natural state is and what indicators

need to be measured to monitor progress back to that state.

These monitoring requirements pose several challenges to the mining industry. What is

the optimum approach to measuring so many variables accurately and continuously?

How can the resulting observation data be stored, managed and distributed? How can

data from multiple different sources be integrated for scientific research and summarised

for communication?

The Sensor Web is an emerging concept that promises to revolutionise measurement and

observation in the mining industry and elsewhere. Sensor Web Enablement, or SWE, of

mine environmental monitoring, while in its early days, has the potential to solve many of

the challenges posed above. I present a vision of a Sensor Web Enabled mining industry

with an example of an early application.

3 The monitoring status quo Figure 1 shows typical components of a monitoring system. Instruments, computers,

people and communications technologies are involved throughout the system. There are

many potential points of failure, inefficiency and unnecessary cost.

There are several dimensions to the complexity of monitoring. One is the range of

phenomena that are measured. There often are separate monitoring systems for each

phenomenon. Another dimension is the users or systems that ‘consume’ the observations.

The environmental reporting department and the risk management department might have

to measure the same phenomena, but because their requirements are different they

maintain separate monitoring systems, causing unnecessary redundancy. Multiple

vendors and lack of standardisation (multiple proprietary data formats for example) are

other important factors. Figure 2 illustrates some aspects of the status quo. There is often

little if any communication among domains. Custom after-market integration software is

usually expensive and problematic.

4 Sensor Web Enablement Sensor Web Enablement (OGC SWE 2007) is an OGC (Open Geospatial Consortium)

initiative that has seen several standards and specifications emerge for describing sensors,

encoding observation data and making these data available via standard web service

interfaces. SWE will facilitate the discovery, exchange and processing of sensor

observations. SWE promises to make a multitude of sensors and their observations

available on the Web. Together with OGC Web Processing Services (WPS) SWE will

exploit distributed computing to fuse and integrate these data through real-time service-

chain composition to generate up-to-date, dynamic and accurate information products

that have been difficult, costly or impossible to access before. Any sensor can potentially

participate in the sensor web, from an in situ borehole water quality sensor to a satellite

remote sensor to a human visual observation or questionnaire.

Figure 1. The monitoring stack.

Each observation in the Sensor Web is tagged with time and location, allowing for

realistic spatio-temporal modelling and a richer understanding of environmental

dynamics.

Extending the scope of OGC SWE, the Semantic Web (W3C 2001) will enable users to

define queries that will automatically be interpreted; automatically locate, interrogated or

task sensors on the Internet, acquire and process observations and return answers.

SWE uses a subset OGC Web Services (OWS), a Service Oriented Architecture (SOA)

that can operate in any service paradigm, from 'SOAP' to 'REST'.

SWE is an essential component of GEOSS, the Global Earth Observation System of

Systems (GEO 2007). Many governments, including that of South Africa, have agreed to

the GEOSS 10-year Implementation Plan, which aims to coordinate earth observation

activities globally, thereby reducing costs, increasing accuracy and resulting in greater

benefit to society. SWE forms part of the architecture needed to bring this vision about.

Figure 2. Mine monitoring silos.

Sensor Web Enablement currently involves some or all of the following components, all

operating in the framework of the OGC service-oriented reference architecture:

• O&M (Observation and Measurements): XML schema for encoding sensor

observations and measurements (Figure 3).

• SOS (Sensor Observation Service): Web service interface for interrogating

sensors and retrieving observations and sensor descriptions.

• SensorML (Sensor Model Language): XML schema for describing sensors and

processes they can participate in.

• SAS (Sensor Alert Service): Web service interface for subscribing to sensor-based

alerts.

• SPS (Sensor Planning Service): Web service interface for tasking sensor

activities.

• TransducerML: XML schema for describing transducers. Supports real-time low-

level data streaming and actuator control.

• WNS (Web notification service): Web service interface for handling

communication of messages from SAS or SPS.

Figure 3. Example of OGC observations and measurements XML.

Every component within the scope of a Sensor Web intervention is standards-based.

Therefore, perhaps the most beneficial outcome of SWE is interoperability.

In SWE, “any Observation is an Event whose Result is an estimate of the value of some

Property of a Feature of Interest, obtained using a specified Procedure”. The capitalised

terms in the preceding sentence are keywords in Observations and Measurements XML

documents, and imply that observations thus encoded are specified precisely and in the

same way, no matter what is being measured.

5 How does SWE impact on mine monitoring? Figure 4 shows mine monitoring systems integrated through SWE. Only the sensors that

are necessary to describe a phenomenon of interest, need to be deployed. SWE enables

observations from these sensors to be processed and communicated in such a way that all

<om:Observation gml:id="obsTest1"

xmlns:om="http://www.opengis.net/om"

xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

xmlns:xlink="http://www.w3.org/1999/xlink"

xmlns:gco="http://www.isotc211.org/2005/gco"

xmlns:gmd="http://www.isotc211.org/2005/gmd"

xmlns:gml="http://www.opengis.net/gml"

xsi:schemaLocation="http://www.opengis.net/om ../om.xsd">

<gml:description>Observation test instance</gml:description>

<gml:name>Observation test 1</gml:name>

<om:time>

<gml:TimeInstant gml:id="ot1t">

<gml:timePosition>2005-01-11T16:22:25.00</gml:timePosition>

</gml:TimeInstant>

</om:time>

<om:location>

<gmd:EX_GeographicDescription>

<gmd:geographicIdentifier>

<gmd:MD_Identifier>

<gmd:code>

<gco:CharacterString>Subiaco Markets</gco:CharacterString> </gmd:code>

</gmd:MD_Identifier>

</gmd:geographicIdentifier>

</gmd:EX_GeographicDescription>

</om:location>

<om:procedure xlink:href="urn:x-ogc:object:feature:Sensor:OGC:scales"/>

<om:observedProperty xlink:href="urn:x-ogc:def:phenomenon:OGC:mass"/>

<om:featureOfInterest xlink:href="http://some.interested.org/vegetables/instances/banana1"/>

<om:result xsi:type="gml:MeasureType" uom="urn:x-ogc:def:uom:OGC:kg">0.28</om:result>

</om:Observation>

users have access to them in the form they require. These users, or ‘Sensor web clients’

include: Disaster management systems; risk management systems; operational

monitoring; mine planning, modelling and forecasting; reporting to the public; reporting

to government; reporting to global corporate headquarters; and monitoring progress

towards rehabilitation and closure.

Figure 4. The effect of SWE on mine environmental monitoring.

6 Krugersdorp Basin example The decanting situation in the Krugersdorp Basin west of Johannesburg, South Africa, is

a typical future closure scenario for many other mines (Fleming, 2007). Water levels rose

in several old adjoining mines after pumping ceased along with mining operations.

During the life of mine the pumping rate was 60Ml/day, and in late 2007 it was 6-23

Ml/day (pers comm., Council for Geoscience, CGS). Large quantities of contaminated,

acidic water started decanting and are still doing so from several openings. This water is

contaminating surface and ground water over a large area. Some of it is being retained in

buffer dams and treated but much still escapes untreated. The CGS placed six groups of

sensors in shafts, dams, rivers and other locations in the basin, aimed at characterising the

problem so that a suitable solution could be found, as well as to flag potential emergency

situations, such as a large drop in pH or increase in flow. The monitoring system initially

consisted of sensors, data loggers, GSM communications via SMS to a central service

provider and manual downloading of data by CGS staff. Each component in the system

was proprietary and hence closed and inflexible.

6.1 SWE intervention

A data pre-processor was developed to acquire observations from the central service

provider in their proprietary text format at regular intervals, parse them and write them to

a database conforming to the SOS schema. A Python-based SOS implementation adapted

from Bill Howe's at www.oostethys.org exposes these observations via the OGC standard

SOS interface for any client to access. A simple SOS client (Figure 5) fetches data for a

defined period and graphs it. Figure 6 show time series from the Krugersdorp Basin SOS

for six variables over one day. A graphing client such as this is a simple application of the

Sensor Web. If a SOS is public, the world is free to build any application simple or

complex, to use its observations.

Figure 7 shows a more complex SOS client that plots fire observations spatially, in this

case along with a map of South Africa retrieved from an OGC WMS (Web Map Service).

It serves to indicate further application of SWE. To translate this example to a mine,

picture a mine plan showing environmental incidents that need attention during an

emergency.

Figure 5. Simple client for the Krugersdorp Basin SOS (Sensor Observation Service).

Mashup

In web development, a mashup is a web application

that combines data from more than one source into a

single integrated tool. The term Mashup implies easy,

fast integration, frequently done by access to open

API's and data sources to produce results data owners

had no idea could be produced. An example is the use

of cartographic data from Google Maps to add location

information to real-estate data, thereby creating a new

and distinct web service that was not originally

provided by either source.

Source: Wikipedia

Figure 6. Time series of five variables at five sensor pods over one month retrieved from the

Krugersdorp Basin SOS.

Imagine custom dashboards on the computer screens of managers and operational staff,

bringing together in meaningful and useful ways, observations from multiple and diverse

sensors around a mine, all using standard Web technology.

Figure 4. A SOS client showing fire observations from the AFIS SOS (Advanced Fire Information

System, CSIR).

7 Process control While environmental monitoring is the focus of this paper, measurements are made and

used routinely in process control and mining operations as well. The author is

undertaking research with the Cyanoprobe team at Mintek to investigate Sensor Web

Enablement of mineral processes that use cyanide. While SCADA and OPC systems are

routinely used in process control, there is scope for investigating Sensor Web Enablement

to improve interoperability and expand the application of process measurements. With

TransducerML, SWE could be used directly in the process control loop, as part of

cyanide input control and waste treatment control. But outside the normal realm of

control systems, SWE can make process measurements available for operational

warnings and alerts, reporting, compliance monitoring and general environmental

monitoring, without investing in additional, redundant systems.

8 Mining operations The CSIR is investigating the Sensor Web Enablement of mining operations, exposing

production, geology, safety and other routine observations and measurements through

OGC standard web interfaces.

9 Barriers to Sensor Web Enablement Several standards and specifications for SWE are mature and have been implemented.

Others are in early stages of development. Currently there is no operational example of

all the components of the Sensor Web working together. The OGC’s own Test Beds (e.g.

www.opengeospatial.org/projects/initiatives/ows-5) are cutting-edge environments where

implementations of SWE components are tested and demonstrated. The ‘real-world’

domain that has progressed furthest with SWE is the Global Ocean Observing System

(www.ioc-goos.org). Large international research projects like Sensors Anywhere

(SANY 2006) are making inroads into SWE technology and application.

10 Recommendations The Mining industry can learn from these pioneers and start by adopting mature

components of SWE while assisting with Research and Development of SWE for less

mature components, or where special development is required for the mining

environment.

Behavioural and organisational changes are required to adopt something new like SWE.

Thus, implementing the standards upon which SWE is based will take foresight in the

industry. Stakeholders in the monitoring industry need also to participate in the

development of or upgrading to standards-based software applications.

Acknowledgements

Members of the Sensor Web Alliance (www.sensorweb-alliance.org) have been

instrumental in developing many of these ideas and associated technologies. Thanks to

Joan van Genderingen and Bridget Fleming for the original illustrations.

References

• Fleming, G. (2007) Sensor web enablement in the mining industry. Internal report number 40088,

Mintek, South Africa.

• Fleming, G., N. King, M. Mugonda, S. Dlamini (2008). Human-environment interactions: Integrated

indicators of sustainable development and sensor web enablement. Internal report number 4892,

Mintek, South Africa.

• Moodley, N. (2006) New waste water levy to impact mining. Mining Weekly, 22 March.

• Anon (2002) The disappearing act of Gauteng’s golden dumps. Mining Weekly, 7 June.

• MPRDA (Minerals and petroleum resources development Act 28 of 2002). Government of South

Africa.

• SANY (2006) Sensors anywhere. EU IST FP6 integrated project: http://sany-ip.eu/

• GRI (2006) Global reporting initiative. Sustainability reporting guidelines, G3 Version.

www.globalreporting.org

• W3C (2001) World Wide Web Consortium. Semantic Web. www.w3.org/2001/sw

• OGC SWE (2007) Open Geospatial Consortium Sensor Web Enablement working group.

http://www.opengeospatial.org/projects/groups/sensorweb.

• OGC (2006) Observation and Measurements. Document reference OGC 05-087r3.

• GEO (2007) Group on earth observations. Global earth observation system of systems.

http://earthobservations.org/

For more information contact Gavin Fleming, Mintek, +27 (0)11 709 4668,

GavinF@mintek.co.za, www.mintek.co.za

1 About the author

Gavin is a Senior GeoInformation Science and Sustainable Development Researcher

at Mintek, in the Mineral Economics and Strategy Unit (MESU). He qualified from

Wits with an MSc in population genetics, after a BSc and Hons in genetics and

microbiology.

In 1996 Gavin switched to GIS, starting at GIMS. In 1999 he moved to the GIS lab in

Environmentek (now Natural Resources and the Environment) at the CSIR. Still at the

CSIR he spent a year at the Satellite Applications Centre and then a year at ‘ICT4EO’

(ICT for Earth Observation) at the Meraka Institute before moving to Mintek in 2006.

Gavin heads up Mintek’s GIS department which captures, manages and publishes

spatial information and products such as paper and online maps. He is a staunch

advocate of Free and Open Source Software (FOSS) as well as of open standards and

interoperability and applies these wherever possible. He led the organisation of ‘Free

and Open Source for Geospatial 2008’ (www.foss4g2008.org), an international

conference that is happening in Cape Town in spring.

A specific niche of GIS that overlaps with various other fields is ‘Sensor Web

Enablement’ (SWE), which is the subject of his MMP presentation. He is running a

research project to develop Sensor Web applications for mine environmental

monitoring. That topic overlaps with his other work interest which is sustainable

development through mining. In that arena he is working on projects investigating

water and mining and local economic development in mine-affected communities.