An Intelligent Approach to Water Management
20 May 2015 | Michael SullivanTagged: Planet,
The Third in a Series About Machine-to-Machine Technology and Water Management.
Properly maintained water systems underpin our quality of life. Inefficiencies in how we manage our precious water resources are very costly. Municipalities must spend a tremendous amount of money moving and treating water, and on average 25 percent of water produced never reaches end users because of leaks and water main bursts. Couple all these expensive repair bills with extreme weather patterns that are either leaving cities with way too much -- or far too little water -- and it’s no wonder why water crises are now ranked as the top threat to economic development worldwide.
By putting more data and better tools to work in analyzing our water systems, water authorities will be better able to make cost-effective decisions to repair and replace aging water infrastructure based on predictive insights, not reactions to catastrophic failures.
Look no further than to our West Coast and ask Californians about dramatic consequences of what it’s like living through these new extremes and the crippling impacts of operating in a water-constrained economy. Creative solutions are needed to help cities stretch taxpayers dollars and better balance water supply and demand. Today, big data and analytics can be used to overcome the complexity and truly manage our water supply as holistic systems.
The integration of big data into existing water-control systems presents major opportunities for how water use is managed around the country. City officials can use this data to analyze use and flow of water, which, in turn, allows them to build new insights to make better management decisions in the future. Data, and a city’s ability to use it as a tool in their planning, will improve water delivery systems. By providing information about water flow in real time, steps can be taken proactively to counter-balance the negative effects of aging and failing water infrastructure.
The use of big data in water management can be best illustrated using an example: in a particular pipe or set of pipes, water management officials can observe and collect existing and new sources of operating data as inputs for supporting advanced analytics in the areas of leak detection, pressure management and pipe failure prediction capabilities to proactively reduce water lost from leaks and bursts. By putting more data and better tools to work in analyzing our water systems, water authorities will be better able to make cost-effective decisions to repair and replace aging water infrastructure based on predictive insights, not reactions to catastrophic failures.
The challenge and opportunity for smarter water management is global. By 2030, rising population and growing urbanization will increase global water demand by 30 percent according to the United Nations. Yet even as the challenges increase, so do the capabilities that government, cities, utilities and businesses have at their command to respond. Big data, sophisticated analytics, sensors and the cloud provide the flexible, cost-effective foundation needed to finally make the most of the existing and new information available to address the problem of managing one of the world’s most essential resources – water.
IBM is participating in the NIST Global City Teams Challenge with AT&T.