This post is also available in: Deutsch (German)
We use water for so many purposes: drinking, cooking, cleaning, bathing, brushing teeth, gardening, washing cars, cooling engines, wiping windscreens and so many more. However, water is a scarce resource, let alone water that is clean enough to use safely.
“Nearly 97% of the world’s water is salty or otherwise undrinkable. Another 2% is locked in ice caps and glaciers. That leaves just 1% for all of humanity’s needs — all its agricultural, residential, manufacturing, community, and personal needs.”
Environmental Protection Agency (EPA)
This is why Big Data would be of big help to water conservation and refinement, and thus, a big step towards a sustainable world.
Early September 2020, households (and maybe businesses) in the Malaysian state of Selangor suffered a water cut, when four water treatment plants were closed due to a leakage of pollutants from a factory.
Upon hearing the announcement of a water cut, residents scrambled to load their buckets with water to cope with the disruption for a few days.
However, the buckets wouldn’t be enough for bathing, drinking, cooking and cleaning in this hot tropical country, so running out of water was inevitable.
To add the rotten cherry on top of the moldy cake, holding back frustration at the unsatisfactory management of water supply was so hard, especially for residents who always pay the water bills.
But disrupting the water supply to allow the water supply board to deal with the contamination probably saved many from the dangers of water contamination.
In Germany last year, fresh water reserves reached a very low level due to insufficient rainfall, an unusually hot summer and a dry winter.
This hot spell left many Germans so thirsty and deprived of their watery needs that what they got, instead of water, was a harsh reality check about water’s scarcity. Scenarios such as these often remind us of how precious water is, and thus, raise the issue of water conservation and refinement.
As a reminder, water conservation is the efficient usage of water to minimise water wastage, while water refinement is the removal of unwanted elements and the addition of beneficial elements for the water to be usable.
In Part 1 of our Big Data-driven sustainable development goals article series, we learnt that Big Data can drive better decisions for water conservation and refinement. Here, we take a closer look.
According to a compiled study authored by Sun and Scanlon, these are usually where Big Data for water management come from:
A study by Piratla, Matthews and Koo has a great example of Big Data’s application in water management as it dives deep into the use of Internet of Things (IoT) tech in the water supply system.
In case you didn’t know, IoT refers to objects that are connected to the internet and “talk” to each other, according to WIRED.
“Simply, the IoT is made up of devices – from simple sensors to smartphones and wearables – connected together.”
said Matthew Evans, the IoT programme head at techUK, quoted by WIRED.
Combining IoT devices with automated systems enable the gathering, analysis and decision making in a particular task or process. In the case of water management, the IoT systems are:
Downstream and upstream data are collected using Wireless Sensor Network (WSN) tech connected to IoT.
The downstream data collected provide insights on water usage and performance while upstream data are similar to traditional Supervisory Control And Data Acquisition (SCADA) and Automated Meter Reading (AMR) systems.
Matin and Islam define WSNs as:
“self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants,
and to cooperatively pass their data through the network to a main location or sink where the data can be observed and analysed.”
Matin and Islam in 2012.
According to Pule, Yahya and Chuma, WSN can be used to monitor water quality in real-time, a task which involves detecting its characteristic parameters and comparing them with set standards and guidelines.
The common water quality characteristic parameters are:
If the water supply is neutral, less conductive, has high ORP and zero turbidity, we’re safe. In contrast, if the WSN detects any deviation from these standards, it means that the water is polluted and needs to be attended to ASAP!
SCADA is a computer system that gathers and analyses real-time data to monitor a facility in industries spanning across water management, waste control, energy generation and so on.
In the International Society of Automation’s explanation, SCADA typically consists of workstations, programmable logic controllers (PLCs), a local area network (LAN) and remote terminal units (RTUs):
With such an integrated sensing and communication system in place, SCADA can:
The AMR automatically collects consumption, diagnostic and status data from water or energy metering devices via data sensing, and transfers those data to the central database for billing, troubleshooting and analyses.
An alternative to the troublesome manual meter reading, benefits of AMR include but are not limited to:
It seems that a more accurate meter reading can inform utilities about potential water leaks to determine water distribution pipelines that need replacement.
All these data are then converged to build a Big Data system through a process called data fusion.
“Data fusion is the process of getting data from multiple sources in order to build more sophisticated models and understand more about a project. It often means getting combined data on a single subject and combining it for central analysis.”
Techopedia’s definition of data fusion
In this case of water management, all the WSN, SCADA and AMR data about water quality, treatment plant conditions and meter readings are combined in one BIG FAT – I mean, Big Data system, where data miners can extract issues such as:
Smart water management isn’t limited to sustainable and safe consumption by households and business premises, but extends to sustainably watering crops, which will then be sold to consumers for consumption.
More than 70% of the fresh, usable water is used for irrigation for agriculture. However, a lot of water is wasted in irrigation due to over-irrigation, which refers to spraying more water than needed.
Farmers tend to resort to over-irrigation to avoid under-irrigation, which is obviously the opposite of over-irrigation a.k.a. spraying less water than needed.
Precision irrigation uses water efficiently, while avoiding both under- and over-irrigation, by spraying the exact amount of water needed to increase crop yield, cut costs and save water.
To enable precision irrigation, a paper by Kamienski et al presented the architecture of the SWAMP Platform, an IoT-based smart water management platform for precision irrigation.
According to them, the SWAMP Architecture has five layers (you may refer to the detailed infographic for this here):
By using a whole system of IoT-based technologies and machine learning algorithms, it’s possible to use the precise amount of water for irrigation.
An abundance of water data provides opportunities to water utilities and farmers to analyse these data and generate useful insights to make better decisions. IoT plays a big part in gathering the data they need.
WSN is used to monitor water quality by measuring the water’s pH level, electrical conductivity, ORP and turbidity. By checking if the water’s pH is neutral, conductivity is low, ORP is high and turbidity is zero, utilities can ensure that the water is safe for public consumption.
SCADA, which is spread throughout the water supply system for sensing and communication, can inform operators and managers if the water treatment facility is secure and in top condition without needlessly putting patrollers on shift.
AMR can also remove the trouble of manual meter reading and billing by automatically gathering and transferring data to the database.
A possible combination of these technologies allow farmers to know precisely how much water they need to add to the crops for crop yield, cost and water usage optimisation.
This shows that employing Big Data and IoT tech for real-time water monitoring enables timely responses to water contamination and/or leakage/wastage.
And by bringing together these tech, the data can be used to find the answers utilities and farmers seek and not just check on the surface.
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