News Article | July 13, 2015
There is nothing more peaceful that watching snowy white swans wading the waters on a sunny summer day — but not if the water is swimming with pollution. Thankfully, the swans that are now being seen in Singapore's Pandan Reservoir are not actual birds, but rather robot swans that have been sent out to test and monitor various water conditions to make sure the supply is safe from contamination. The flock of robotic swans was developed by a team of researchers at the National University of Singapore (NUS) Environmental Research Institute, along with the Tropical Marine Science Institute and the national water agency PUB. The NUSwan robots were originally conceptualized in 2010 by a small team at both institutes and began their first round of testing last year. The robots are designed to look just like living, breathing swans but are strong enough to take a blow from a kayaker or even a small boat. They are equipped with advanced technology to monitor, in real-time, various physical and biological components in fresh water. Along with identifying any water contamination, the NUSwans also monitor the level of pH in the water, the amount of dissolved oxygen, turbidity and chlorophyll. These are all compounds that can determine if there are any problems with the water. The robotic swans swim in the water autonomously but are often controlled by programmers and use GPS navigation to test the water in a specific location. The data is then sent wirelessly to the cloud, where researchers can analyze the water remotely in real-time. Because the robot swans are using GPS technology, they don't recover grounds they already tested unless instructed to, which saves time. Along with increasing efficiency, the robots also save money. "It would be expensive to do similar monitoring manually or using AUVs (Autonomous Underwater Vehicles)," one of the project's lead researchers, Assistant Professor Mandar Chitre, told Channel News Asia. "Scientifically, the NUSwan test drives a new paradigm of freshwater monitoring, one that is persistent and interactive, and is potentially able to sample the dynamics of water quality over space and time at improved resolution at an affordable cost." The researchers continue to work on the NUSwans with other university researchers to expand their technological components. This includes adding a phosphate sensor for freshwater testing. Phosphate is found in algal blooms in polluted water so the swans could possibly detect the affected areas in a more timely fashion. While the NUSwans will be tested in South China's waters, the technology could be used elsewhere to detect and address water pollution. "We see the potential of having NUSwans deployed in urban freshwater bodies and coastal water beyond Singapore. With the data stored in the cloud, collaborators may share and aggregate data and understand global phenomena," Chitre said. Just remember that you can't feed these birds.
Raghavan S.V.,Tropical Marine Science Institute |
Tue V.M.,Tropical Marine Science Institute |
Shie-Yui L.,Tropical Marine Science Institute
Journal of Hydroinformatics | Year: 2014
A systematic ensemble high-resolution climate modelling study over Vietnam was performed and future hydrological changes over the small catchment of Dakbla, Central Highland region of Vietnam, were studied. Using the widely used regional climate model WRF (Weather Research and Forecasting), future climate change over the period 2091-2100 was ascertained. The results indicate that surface temperature over Dakbla could increase by nearly 3.5 WC, while rainfall increases of more than 40% is likely. The ensemble hydrological changes suggest that the stream flow over the peak and post-peak rainfall seasons could experience a strong increase, suggesting risks of flooding, with an overall average annual increase of stream flow by 40%. These results have implications for water resources, agriculture, biodiversity and economy, and serve as useful findings for policy makers. © IWA Publishing 2014.
Ng H.H.,Tropical Marine Science Institute |
Rainboth W.J.,University of Wisconsin - Oshkosh
Zootaxa | Year: 2011
Tonlesapia amnica, a new species of dragonet lacking a first dorsal fin, is described from the Mekong River delta in southern Vietnam. It can be distinguished from its sole congener, T. tsukawakii, in having the infraorbital canal extending beyond (vs. not reaching) ventral margin of orbit, a more slender body (7.2-13.5% SL vs. 14.3-15.0) and caudal peduncle (4.4-5.2% SL vs. 5.1-6.3), a smaller eye (6.5-8.3% SL vs. 8.7-9.2) and more dorsal-fin rays (9-10 vs. 8). Copyright © 2011 - Magnolia Press.
Vu M.T.,Tropical Marine Science Institute |
Raghavan V.S.,Tropical Marine Science Institute |
Liong S.-Y.,Tropical Marine Science Institute
KSCE Journal of Civil Engineering | Year: 2015
This study focuses on the Hydro-Meteorological Drought assessments by Ensemble Climate Projections from a regional climate model (Weather Research and Forecasting, WRF) that downscaled 3 Global Climate Models under a baseline period (1961–1990) and under a future scenario A2 for 2071–2100. The Meteorological Drought is assessed using the Standardized Precipitation Index (SPI) while the Hydrological Drought is analyzed by using both the semi-distributed hydrology model SWAT and Standardized Runoff Index (SRI). The catchment under study is a small river basin lying on the Central Highland area of Vietnam. This area is the source for perennial plantation which produces most of the coffee for Vietnam making it the world’s second most exporter of coffee next to Brazil. Additionally, this region is also one of the important sources for hydropower of Vietnam and one of the main tributaries for the Mekong river at the downstream. This region has been known prone to drought, especially during dry seasons of March and April. Therefore, simulating drought for this area is significant to study the water supply and water balance for the region for future planning and adaptation. © 2015, Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg.
PubMed | Tropical Marine science Institute
Type: Journal Article | Journal: Adaptive behavior | Year: 2016
In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agents adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agents sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.