Water & Waste Management


Artificially Intelligent Green Energy? Yes!

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Smart Wind and Solar Power Big data and artificial intelligence are producing ultra-accurate forecasts that will make it feasible to integrate much more renewable energy into the power grid. Researchers around the world are collecting wind speed and output data from wind turbines. The result: wind power forecasts of unprecedented accuracy are making it possible to use far more renewable energy, at lower cost, than utilities ever thought possible. While solar power generation lags wind power production, researchers are furiously working around the world to better harness the sun's abundant power.


New Jersey-Size 'Dead Zone' Is Largest Ever in Gulf of Mexico

National Geographic News

This year's large size is mainly due to heavy stream flows in May, Rabalais continued, which were about 34 percent above the long-term average and carried higher-than-average amounts of nutrients through Midwest waterways and into the Gulf. In its action plan for the Gulf of Mexico hypoxic zone, the Mississippi River/Gulf of Mexico Hypoxia Task Force recently extended the deadline until 2035 for achieving the goal of a 1,950-square-mile dead zone, which would be roughly the size of Delaware. Shrinking the annual Gulf of Mexico dead zone down to that size, however, will require a much higher 59 percent reduction in the amount of nitrogen runoff that flows down the Mississippi River, according to a study published in Proceedings of the National Academy of Sciences. "The bottom line is that we will never reach the action plan's goal of 1,950 square miles until more serious actions are taken to reduce the loss of Midwest fertilizers into the Mississippi River system," says University of Michigan aquatic ecologist Don Scavia, lead author of the paper.


Finding leaks while they're easy to fix

MIT News

Monterrey itself has a strong incentive to take part in this study, since it loses an estimated 40 percent of its water supply to leaks every year, costing the city about $80 million in lost revenue. That's why that desert nation's King Fahd University of Petroleum and Minerals has sponsored and collaborated on much of the MIT team's work, including successful field tests there earlier this year that resulted in some further design improvements to the system, Youcef-Toumi says. Currently there is not an effective tool to locate leaks in those plastic pipes, and MIT PipeGuard's robot is the disruptive change we have been looking for." The MIT system was actually first developed to detect gas leaks, and later adapted for water pipes.


Hazardous waste identified and sorted using simple barcodes

New Scientist

Because many processing facilities can't quickly identify the chemicals in this household waste, the items are often simply lumped together and incinerated – which is expensive. Their start-up, Smarter Sorting, has installed a barcode scanning system at four waste disposal sites in the US used by the public – in Austin, Texas; Salt Lake City, Utah; Portland, Oregon; and Mesa County, Colorado. "The machine goes'beep' and at that point the screen simply tells the worker, 'this is where you should place this item'," says Chris Ripley, who co-founded Smarter Sorting together with Charlie Vallely. Also testing the technology is Hope Petrie, hazardous materials manager at Mesa County Hazardous Waste Collection Facility, although she isn't yet using it to alter the way large numbers of items are processed.


How Machine Learning Helps Identify Toxicity In Potential Drugs

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The team believe that being able to determine the atomic structure of protein molecules will play a huge role in understanding how they work, and how they may respond to drug therapies. The drugs typically work by binding to a protein molecule, and then changing its shape and thus altering how it works.


The US Takes On the World in NATO's Cyber War Games

WIRED

Locked Shields challenges participating countries to show off their defensive prowess, rather than offensive firepower. That makes it a natural fit for the US Cyber Brigade, which defends infrastructure and "terrain" at US military bases: power plants, water treatment systems, air traffic control, and base fuel supplies. Locked Shields hosted 25 countries this week, compared to last year's 19, each defending against a simulated air base attack. Ottis and the organizers worked with global electronics giant Siemens to set up a simulated power grid for the game-playing environment, as well as drone simulators from Threod Systems, an Estonian UAV developer.


Smart Water: EMAGIN is Using Artificial Intelligence to Make Managing Water Utilities and Industries Safer and Greener

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By combining artificial intelligence with water utilities and industries, EMAGIN wants to shift the paradigm from reacting manually to proactively controlling how water utilities are operated and managed. EMAGIN's innovative, artificial intelligence-driven optimization and analytics platform is the Hybrid Adaptive Real-Time Virtual Intelligence, or HARVI. With HARVI, EMAGIN wants to leverage artificial intelligence to create an intelligent water system that connects to its natural and built environment. "It's an honour to be ranked one the top data-driven startups globally in the water sector," reveals Mohamad.


Kitchener startup applies artificial intelligence to water management

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A startup that has developed artificial intelligence to better manage city water systems is among 10 companies from around the world admitted to a San Francisco accelerator focused on turning drought, leaky pipes and pollution into business opportunities. After graduating from the University of Waterloo with a degree in environmental engineering, Gaffoor hooked up with Vedut, who graduated from the University of Ontario Institute of Technology with a degree in software engineering. Two Ontario municipalities are using the startup's artificial intelligence to help operate drinking water and wastewater systems. Gaffoor, Emagin's chief executive officer, and Vedut, its chief operating officer, say the application of artificial intelligence to municipal water systems is an emerging area.


The Use of Machine Learning Methodologies to Analyse Antibiotic and Biocide Susceptibility in Staphylococcus aureus

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Funding: This work was supported by FCT (INESC-ID multiannual funding) through the PIDDAC Program funds and under project PEst-OE/EEI/LA0021/2011 and the FP7 Cooperation Work Programme: Food, Agriculture and Fisheries, and Biotechnologies, KBBE-227258 (BIOHYPO project). Quotient Bioresearch received part-funding from the European Union in the scope of BIOHYPO project. Competing interests: During the elaboration of this manuscript, Ian Morrissey and Daniel Knight were employed by Quotient Bioresearch and belonged to the BIOHYPO European project. However, currently these two authors are no longer employed by Quotient Bioresearch.


Less Than 10% of Bovine i E. coli /i Strains Affect Human Health

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Using software to compare genetic information in bacterial isolates from animals and people, researchers have predicted that less than 10% of Escherichia coli 0157:H7 strains are likely to have the potential to cause human disease. In this study, the researchers applied machine learning to predict the zoonotic potential of bacterial isolates from the United Kingdom and the United States. "[O]ne of the cattle isolates (apart from outbreak trace-back isolates) achieved very high human association probabilities ( 0.9), potentially indicating that those posing a serious zoonotic threat are very rare," the authors write. As a consequence, experts could use targeted control strategies, including vaccination or eradication, in cattle carrying strains of high zoonotic potential, in order to better protect human health.