Maintaining water quality, especially in urbanized landscapes, is highly challenging since water bodies are exposed to varying sources of pollutants from urban run-offs and industries. Simultaneously, active recreational use of these water bodies promotes urban livability in the cities that requires maintenance of clean water and aesthetically pleasing surroundings. Several methods and protocols in monitoring pollutants are already in place. However, the boundaries of extensive assessment for the water bodies are limited by labour intensive and resource exhaustive methods. To ensure good quality, large coverage and safety of the water bodies, NUS researchers have developed an innovative system for monitoring pollutants is required for better management and sustainability.
NUSwan - New Smart Water Assessment Network is an innovative concept on spatial-temporal water quality monitoring. Building upon aesthetics and recreation, NUSwan is a comprehensive solution to maximize use of resources and cost effectiveness. It is a simple yet powerful tool to observe the water environment. Its ability to collect data according to directed mission in real-time allow interactive sampling at any location of interest. It has the capability of performing simultaneous multi-node, high speed sensing for observing concentration gradients for better characterization and detection of time varying hotspots.
NUSwan is an on-going research to develop low cost autonomous robotic swans capable of real-time sampling in fresh water bodies with centralized data storage tools for diverse data acquisition by autonomous sensing nodes, effective visualization as well as interoperability with existing database and prediction models.
The NUS researchers have demonstrated the NUSwan prototype with multi-parameter probes in local reservoir according to directed mission. The data collected can be transmitted real-time through WiFi network within range.
The NUS researchers have envisaged the development of future work on upgrading visualizations, diving capability and adaptive sampling. Smart navigation will be employed using natural water movement and cooperative sampling research to extend the monitoring endurance of the mobile platform. The upgraded performance will be test-bedded to evaluate its sampling capability, real time data transmission, power usage and navigational capabilities. Continuous efforts are being undertaken in seeking collaborators for future development and scale-up as well as partners who are willing to venture into commercialisation.For inquiries, please contact:
Assistant Professor Mandar Chitre