Heterogeneous networked cooperating objects for pollution detection and monitoring

Background/Question/Methods

Wetland ecosystems of the world maintain biologically diverse communities of ecological and economic value. Water pollution has been identified as one of the most important threats for water ecosystems. Biologist and management authorities need physicochemical and biological monitoring for assessing the risks due to freshwater pollution and to provide maximal information for adequate management of aquatic ecosystems. One of the problems for monitoring aquatic environments is the difficulty of access to these areas, which has promoted diverse solutions such as the installation of sensors that storage data that can be collected periodically or remotely sent to managers for analysis.

During the last decade, the evolution of embedded systems has led to the emergence of diverse machines with embedded capabilities for computation, communication and interaction with the environment. Cooperating Objects applications have been used in sectors of impact on society (security, home and office, healthcare and others), but their implementation in environmental monitoring has hardly been explored.

In the context of the EU Project PLANET, we aimed to provide an integrated planning and maintenance platform that enables the deployment, operation and maintenance of heterogeneous networked COs in an efficient way for wetlands monitoring, including pollution detection and its assessment.

Results/Conclusions

We conducted a validation demonstration in April 2014 simulating the protocol in the case of a pollution event in Doñana National Park marshlands (Southwest of Spain), where each CO performed its specific task and PLANET platform coordinated the whole system, whose operation could be monitored through an interactive interface: 1) Static ground and water sensors deployed in the area informed about environmental conditions; 2) A Rotary Wing Unmanned Aerial System took water samples (500 ml) in autonomous mode and deployed a small Unmanned Ground Vehicle; 3) An Unmanned Ground Vehicle was deployed with a camera on the surroundings of the marshlands providing real time video and equipped with a system to gather water sensors data; and 4) A Fixed Wing Unmanned Aerial System gathered ground sensors data, deployed nodes from the air and captured images with an onboard camera, allowing to build a high-resolution mosaic of the area shortly after the flight.

While the focus in our work was on water pollution in sensible ecosystems, other natural scenarios and the exploration of other fundamental ecological questions could benefit from these capabilities.