Almost a third of the global population lacks access to safely managed drinking water. As the world recovers from healthcare and financial repercussions of the pandemic, effective water management becomes imperative, water being a critical resource for most residential, commercial, and industrial activities. Even before the COVID-19 pandemic, climate change caused by global warming was disturbing the water ecosystem balance.
While we try to mitigate the impact of climate change, we can optimally distribute and utilize the available water resources for effective conservation. A key metric in managing the effectiveness of water distribution to the last mile is Unaccounted For Water (UFW). It is the percentage of water that is lost along the water supply chain from the source to user premises. Keeping UFW in control for an increasingly urbanized, dense population poses many challenges. Here are some of them:
Leakage – Distribution pipelines from reservoirs to pumping and purification stations and then further to user premises often have high flow rates and hydraulic pressure. It often results in pipe breakage, valve malfunction, and subsequently significant water leakage. Measuring the pressure and flow rates at various points of water distribution networks helps in optimizing the network and ensuring its integrity. Another approach is using vision systems for detecting the beyond threshold leakage from the distribution network of the overhead tanks and pipes.
Wastage – Inadvertent, unattended water flow from outlets is a major reason for water wastage in residential as well as commercial premises. While deploying measurement and monitoring infrastructure at every water usage endpoint is not practical, we can build intelligence into a smart meter and valve to regulate the supply to a set of endpoints in a technologically and economically feasible manner. Another source of wastage is the sub-optimal performance of water processing equipment (purifying, cooling, or heating) in commercial and industrial applications.
Let us now look at how AIoT technologies help address these challenges.
How AIoT technologies help
Water leakage in the distribution network
Ruggedized outdoor sensors and communication modules with medium to long-range connectivity help in transmitting the telemetry data of flow rates, pressure, rate of change, and timewise patterns from points across the distribution network. This solution approach relies on leak localization by analyzing the flow rate and pressure change data through machine learning pipelines. Both supervised and unsupervised techniques deliver good localization accuracy. From the analytical perspective, historical data on leakage events and telemetry data patterns sent to Cloud applications could be integrated with the weather data to predict probable time to failure for various parts of the distribution network.
Technicians managing the network can fetch insights regarding the components that might be about to fail. These components of the distribution network could be repaired or replaced just in time to avoid water leakage. Computer vision-based pipelines on a video feed on known bottlenecks in the network i.e., points where leaks have been localized on multiple instances can help prevent major leaks from developing. These camera systems capturing video feeds could also be mobile, moving along the pipeline length to cover large portions of the distribution network as per demand and seasonality patterns.
Water wastage at the consumer location
Just like in the distribution networks, inadvertently opened yet unused or persistently leaking water outlets significantly increase per capita consumption of water at the user location. Water flow rates can be monitored to detect possible instances of water wastage on-premises. Smart meters can facilitate it by detecting periodic trends in water flow rates. Based on the standard flow rates of various water outlets and their historical usage patterns, machine learning models are used to detect one or more simultaneous leaks – an open kitchen sink faucet, a malfunctioning flush tank, or a leaking shower head.
We may require frequent water replacement for recreational water usage in outdoor pools because of degraded water quality w.r.t safe usage standards. We can also use computer vision models deployed on the poolside or inside the pool to detect biodegradable (dried tree leaves, fruits, flowers) and non-biodegradable (cans, bottles, plastic bags) rubbish. It could be cleaned using human or machine intervention to ensure high water quality without frequent replacement.
Water processing equipment like heater, cooler, and purifier performs sub-optimally or even break down, subsequently causing significant water wastage in many cases. This is a major problem for large, spread-out commercial establishments like malls, stadiums, and commercial complexes. Connected vision or sensor data-based ML solutions help detect the wrong configuration of deployed equipment, deteriorated critical components, or sustained lack of SOP adherence by the user or operator. Taking corrective actions using these sensor data-based insights surely helps prevent ineffective or broken-down processing equipment.
To sum it up, AIoT technologies help improve water utilization across the value chain in the residential, commercial, and industrial segments. This has the potential to contribute significantly to achieving the sustainable development and conservation of water resources.
eInfochips has strong competency in product engineering using AI and IoT technologies for diverse industry use cases for optimized control and insights. Our expertise in commercial and open-source technology platforms in hardware, as well as software layers, has helped us create meaningful value for customers across industry verticals including water management.
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