Report from the first workshop on geo sensor networks

Advances in sensor technology and deployment strategies are revolutionizing the way that geospatial information is collected and analyzed. For example, cameras and GPS sensors on-board static or mobile platforms have the ability to provide continuous streams of geospatially-rich information. Furthermore, with the advent of nano-technology it becomes feasible and economically viable to develop and deploy low-cost, low-power devices that are generalpurpose computing platforms with multi-purpose on-board sensing and wireless communications capabilities. Special IT infrastructure challenges are posed by systems consisting of large numbers of unattended, untethered and collaborative sensor nodes that have small, non-renewable power supply and communicate via short range radio frequency with neighboring nodes. All these types of sensors may act collaboratively as nodes within broader network configurations. Such configurations may range in scale from few cameras monitoring traffic to thousands of nodes monitoring an ecosystem. The challenge of sensor networks is to aggregate sensor nodes into computational infrastructures that are able to produce globally meaningful information from raw local data obtained by individual sensor nodes. In geo sensor networks the geospatial content of the information collected, aggregated, analyzed, and monitored by a sensor network is fundamental; this might be performed locally in real-time on the sensor nodes or between sensor nodes, or off-line in a scattered or central repositories. Thus, a geosensor network may be loosely defined as a sensor network that monitors phenomena in a geographic space. This space may range in scale from the confined environment of a room to the highly complex dynamics of a an ecosystem region. The spatial aspect of the overall technology may be of importance in multiple levels of a geo sensor network, as the concepts of space, location, topology, and spatiotemporal events may be recognized on various abstraction levels. For example, the hardware and communication layers handle the physical space of sensor deployment, and communication topologies. The database layer generates execution plans for spatiotemporal queries that relate to sensor node location, and groups of sensors. Applications deal with the relation between sensor networks and phenomena in a geographic space. We feel that the academic and practical expertise of the spatial information theory and engineering domain are crucial to advance the development of sensor networks on all different abstraction levels. The ultimate objective is to develop generic sensor network programming infrastructure that is reusable, and widely applicable in all types of different domains.