The understanding of complex environmental phenomena, such as deforestation and epidemics, requires observation at multiple scales. This scale dependency is not handled well by today's rather technical sensor definitions. For instance, to understand the impact of deforestation on the local fauna, it is necessary to track the path of individuals as well as the path of populations within a biotope. Movement patterns of individuals reveal information about change in territory and foraging, while the changed behavior of one population impacts the behavior of others. At the scale of the population, a sensor network should produce a single trajectory based on the tracks of the individual animals. Current definitions of sensors, sensor systems, and sensor networks are too technical to capture these abstractions of observations. For example, the definition of geosensor networks as “distributed ad-hoc wireless networks of sensor-enabled miniature computing platforms that monitors phenomena in geographic space” (Nittel et al., 2004) does not admit animals as sensors and cannot relate the phenomena to those observed at other scales. These definitions also exclude human sensors which are the key to volunteered geographic information. We propose definitions of sensors as information sources at multiple scales, relating physical stimuli to symbol systems. An algebraic formalization shows the aggregations, compositions, and generalizations. It also serves as a basis for defining consistent application programming interfaces to sense the environment at multiple scales of observations and with different devices.

Full paper to be submitted March 31 to http://www.comlab.ox.ac.uk/geosensornetworks/

The Context Toolkit A toolkit for context-aware applicationsAnind K. Dey (dey@cs.berkeley.edu) –> http://www.cs.cmu.edu/~anind/context.html

Modeling sensors as well as sensor systems and sensor networks as a single sensor allows more consistent interface specifications. The Abstract Sensor Interface specifies the basic functionality for interacting with several types, systems and networks of sensors. The developer gets an API (Application Programming Interface) for any sensing system and does not need to know whether the accessed platform is in fact a single sensor or some composition of sensors. Implementations of the Application Programming Interface for a specific sensor type will serve as a simple way of encapsulating the different abstraction levels of the sensor network stack. The API is based on algebraic specifications for the composition of sensors. The work will elaborate design patterns for the composition of sensors and will incorporate these in the abstract interface specifications.

note: interface to our algebra! USE THE SUNSPOTS!

Outlet: Discussion paper for W3C incubator group on geosensors and for OGC

Sensor A sensor is an implemented map from physical stimuli into a symbol system.

Example: Step counter for joggers, blood pressure sensor

Geosensor A geosensor is an implemented map from a physical stimulus into a system of georeferenced symbols.

Example: air temperature sensor, acid rain level sensor, human counting aedes ssp. eggs in a egg trap

Sensor System A sensor system is either an aggregation or a composition of sensors, which can behave like a sensor.

Example: system for monitoring blood pressure and heart frequency

Geosensor System A geosensor system is a sensor system containing at least one geosensor. A geosensor system like a single geosensor.

Example: weather station

Sensor Network A sensor network is a spatially distributed and connected network of sensors.

Example: Company wants to know how many of their vehicles are moving at any point in time.

Geosensor Network A geosensor network is a sensor network whose nodes are geosensors.

Example: Wireless Sensor Network for monitoring air pollution at selected locations

Sensor Web “A Sensor Web refers to web accessible sensor networks and archived sensor data that can be discovered and accessed using standard protocols and application program interfaces (APIs).” (Botts et al. 2007)

Example: Weather Forecasting Sensor Web

Observation an act of observing a property or phenomenon, with the goal of producing an estimate of the value of the property. A specialized event whose result is a data value.

Measurement an observation whose result is a measure

A framework which allows to pick sensors, tools, statistical methods, standards, and models to support decisions and understanding in geospatial applications at multiple scales. Practical outcome: cookbook.

Application of the algebraic view on sensors to the dengue fever (Aedes spp. eggs) use case. This is at the same time our mobility measure: ifgi –> inpe.

In recent years, there have been several outbreaks of dengue fever epedemics in Brazil. To monitor the mosquito agents of the dengue fever, a network of mosquito eggs buckets has been deployed. The algebraic view on sensors depicts a formalism of sensors on different spatial scale levels. In this master thesis, it will be investigated whether this formalism could be applied to the dengue fever use case. The master student will have the possibility to join the team at the Brazilian National Institute for Space Research (INPE) in Brazil to work on his thesis.

Development of suitable tools for different sensor abstraction levels. Mobility measure: inpe –> ifgi.

This Master theses aims at the development of tools for the different levels of abstractions which can be applied in sensor network scenarios. These levels include the Sensor, Sensor System, Sensor Network, Sensor Web and Application level. The tools are supposed to facilitate the deployment of sensor networks, ease the management and administration or improve the usage of sensors and their gathered data. The work includes the analysis of an existing sensor network scenario and the utilization of the developed tools in the scenario. This Master theses involves the opportunity to participate in a exchange program with the Institute for Geoinformatics (IfGI) at the University of Münster (Germany).

At which abstraction level do we need to introduce objects? can we avoid them?

Ontology (SWRL) of processes and data sources for retrieval and composition in the framework (see proposal)

Statistical methods for the conversion between the different abstraction levels of the framework (see proposal).

Different types of data need different statistical methods to be analyzed. For instance, raw sensor data can be analyzed using a given set of techniques, whereas to analyze aggregated, we have to consider this previous data processing. Therefore, once we have identified the meaningful abstraction levels for the sensor data, we propose to identify the proper statistical methods to analyze these data. These methods will be part of a general framework which allows to pick sensors, tools, statistical methods, standards, and models to support decisions and understanding in geospatial applications at multiple scales.

Goal: simplify the sensor web architectures Link to document

1. Introduction:

-survey of current definitions –> scale dependency is not handled well

2. Definitions:

-basic idea: algebraic specification of sensors

3. Proposal

4. Paper Abstract of first paper

5. Paper title for second paper

6. Thesis proposals and mobility measures