With climate change causing more extreme weather, and drought a huge challenge in many parts of the world, there is a widespread need to manage water supplies more efficiently.
IoT has a key role to play here, and Plutoshift is bringing its expertise to bear on water treatment, for both industrial and municipal users. Internet of Business spoke to Prateek Joshi, founder and CEO of Plutoshift, to find out more.
Internet of Business: IoT and AI have the potential to transform the way we manage scarce resources such as energy and water. Can you explain why that’s the case?
Prateek Joshi: “There is immense potential for AI-based smart water technologies to address energy and water challenges as there is a great need to better manage the uncertainty of water supply, weather impacts, and rising costs, while also maintaining profit margins.
“Due to the large volumes of historical and new data readily available, water companies are well positioned to unlock the hidden efficiencies and realise ROI by applying operational analytics and AI to their data. AI can analyse a much larger data set in a shorter amount of time, providing deeper insights into the state of operations, as well as allowing for greater time and resource gains for managers and employees.”
What about water treatment plants? What do they do, and how can IoT and AI improve their efficiency?
“Operators have to make decisions every day to control the movement and purification of water within their plants. They tend to rely on unreliable tests and intuition to make these decisions. Plutoshift leverages AI and IoT to help operators look at real-time insights derived from their data and then make more informed decisions. We help operators produce more water with less energy by providing data analytics to track key performance indicators and by recommending actions that can increase throughput efficiency.
Examples of how AI can improve efficiencies include the ability to: increase throughput by increasing energy efficiency, reduce excess chemical usage and minimise resource consumption, and realise cost savings using existing data collection systems, without installing new hardware.
So, water treatment plants are inefficient when they don’t aggregate data and can’t identify inefficiencies. Can you give some real-world examples?
“Today, operators can’t accurately plan for risks because they are inundated with a lot of raw data. With the help of AI, water treatment plants will become more proactive. Instead of relying on unreliable tests and static rules of thumb, the decision-making process can utilise more data-driven approaches. AI-based solutions convert sensor data into wisdom using relevant algorithms, which can then be used to operate the plant more efficiently. The end result is more water using less energy.
“Our solution has been deployed at multiple water treatment plants, and we work with some of the largest water operators in the world. For example, our recent work at a treatment plant in Tennessee was focused on helping them forecast and predict models for future water overflows. Leveraging their SCADA and sensor data, we built a model that forecasts influent flow based on weather patterns and provides risk-cost analysis based on historical plant behaviour. The results were used by the operators to more accurately plan pump runtimes, modify staff schedules, and proactively divert flow to storage to avoid overflows.”
What does all this mean for consumers of water – for you and me as individuals, and for the many industrial, business, healthcare, and other users of water?
More and more consumers today are making decisions based on climate change, energy footprints, and sustainability, which impacts brands in all markets. The risk of not acting on environmental issues as part of any production scenario will not only affect our planet adversely, but the bottom line of companies.
“The goal is always to create more water using less energy, which has far-reaching benefits and implications across all industries, not just water treatment plants. Beverage production, food processing, chemical companies and manufacturing facilities can all leverage AI to better monitor and optimise a much broader range of operational data and procedures.”
What does all this mean for water conservation at a time when many national infrastructures – such as sewerage systems – are ageing, which often means leaks, and when droughts mean systems are required to operate as effectively as possible?
“A 2017 report from the American Society of Civil Engineers (ASCE) gave the U.S. a D grade on drinking water systems and a D+ for wastewater systems. ASCE estimated that leaky, aging pipes are responsible for wasting 14 to 18 percent of water treated daily, resulting in lost drinking water for 15 million households.
“Successful asset management requires regular inventory and evaluation of critical asset condition and performance to develop plant maintenance and replacement plans. The ability of sensor and data-logging technologies to monitor and track water losses and sudden system changes has empowered managers and decision-makers with critical information on the timing of investments, to cost-effectively replace aging infrastructure assets. AI and machine learning is a critical component of this process now and in the future.”
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For more on leveraging the power of IoT and AI, IoTBuild is taking place on 13-14 November 2018, Olympia Conference Centre, London