Smart cities need smart water management and distribution system. In advanced countries, telecommunications, computing, computer-based modelling, AI, Machine Learning, Data analysis and processing have changed the way water resources are managed. In fact, they have given rise to what is called hydroinformatics systems. A similar change may happen in India as well.
Two students of IIT Kharagpur, Stuti Modi and Aditi Kambli recently presented their paper on an intelligent water management and distribution system based on data-driven models at the Third International Conference on Machine Learning and Soft Computing (ICMLSC) in Da Lat, Vietnam. They won the Best Presentation Award at the conference held in January 2019.
Stuti and Aditi proposed the use of two data-driven models – recurrent neural networks (RNN) and fuzzy-logic based models. With the use of these models, they demonstrated how daily average water demand can be predicted, how drought/flood could be predicted and an optimum level can be maintained in the dam reservoir, how the water level in reservoirs in houses and localities can be controlled, how the drinkability of water can be judged and water treatment can be planned.
Previous works in this field have concentrated on any one aspect of the water management process, for example, on either water demand prediction or treatment. “What we offer is a complete one-package solution. Our model is segmented in such a way that in case of any breakdown, we can easily track the root cause for it and get it fixed. All the individual models here come together and form a platform for water management,” said Aditi.
Aditi is from the Department of Ocean and Naval Architecture and Stuti belongs to the Department of Electrical Engineering. They had worked under the guidance of Prof. Sudhir Kumar Barai of the Department of Civil Engineering on a course of Soft Computing that he teaches to all departments.
For the prediction of daily average water demand, the duo work on the presumption that smart water meters are installed in all houses or localities. Data on water use of individual households, collected by the sensors of the smart water meters, are sent to a central medium. This data is used to train an LSTM based RNN, which then predicts the water usage for the upcoming day.
To validate their assumption, they used the time series data of daily water usage for the last four years. Water usage of the past 30 days was provided as an input to the network. The training of the RNN was performed using Keras.
In the case of drought/flood prediction and the optimum dam reservoir level, the fuzzy inference system is implemented using percentile storage, percentage full storage capacity of the reservoir and rainfall to predict the condition of the dam reservoir. Too much water in the dam threatens dam safety and could cause flood and too little could cause drought. The fuzzy inference system predicts what should be the optimum water level in the reservoir and the Fuzzy PI Controller controls the reservoir water level by releasing or not releasing water.
Such fuzzy logic controller could also man how much water needs to be present in individual water tanks of residential houses. It is often seen that the inlet of water into the tanks is not proportional to the outlet rate, causing the water tank to empty out faster than it fills up. To obtain the water level, however, an ultrasonic water level sensor has to be installed on the top of the reservoir to monitor input and output flows. The water reservoir also has to be modelled as a tank in Simulink whose input and output rates can be controlled.
The water quality model is divided into two parts in this research. One, the assessment of water quality, and two the treatment of moderate/non-drinkable water in a water treatment plant.
For water to be drinkable, various parameters – such as pH, dissolved oxygen, alkalinity, coliform etc – have to be within safe limits. Stuti explains, “Suppose the turbidity of the water is poor and the DO (dissolved oxygen) is moderate, but if the pH and coliform component is rated good, the water is drinkable. This means, all the parameters do not necessarily have to be good for water to be drinkable.” Their fuzzy expert system creates a water quality index that is easy to understand, logical and useful for common people.
Once the fuzzy expert system grades a water to be moderate or non-drinkable through the data collected by sensors and assessed by MATLAB program installed on the computers of the water treatment plant, the water ought to be sent for treatment. For treatment again, the fuzzy logic based system sets ideal values, and based on the error, the correction methodology is powered.
Aditi and Stuti know that the ideas proposed can be improved further with actual sensor data and constant updating of standard points. They would also like to create separate models for each region, since the same parameters don’t work for every region.
Prof. Barai says, “Aditi and Stuti need to implement their model on a large scale hardware model to observe the results and fulfil their goal to implement an intelligent system that conserves and uses water efficiently.”
“Be the change you wish to see in the world.”
Ms. Nadira Patheriya did not agree with Prof. Chetri on radical solutions, such as dictating the change of diet, but she stressed on the use of environmentally-friendly materials in exchange of plastics. “I look at plastics and I feel angry. What have we done?” she said. She was happy at seeing corn flour being used to make the small packets for the ‘prasad’ distributed at Golden Temple of Amritsar. “Even for paper bags, we cut down trees. Why not make jute bags, which would also bring in revenue?”
Rohit Kishan Ray stressed on the need to run a “propaganda” on a war footing to make people aware of the environmental disaster awaiting us if we continued in our ways. Recent political developments had convinced him how fear could be used to influence opinion. “People had to be convinced that they need to save themselves, not Nature… the ‘threat’ was to their own existence.”
“Our foremost aim is to spread awareness regarding the importance of tree conservation, reducing the carbon print and encouraging the student community in plantation drives which is crucial to the sustenance of life on earth,” says a group member. Vision Prabaho, which is also mentored by Mrs. Barnali Chakrabarti, botanist and wife of the Director, Prof. Partha Pratim Chakrabarti, observed World Environment Day 2018 with a “Green Talk” featuring Prof. Souvik Bhattacharya, Vice-Chancellor, BITS Pilani among other green activists and thinkers.
Kgpian Dr. Piya Pal has been conferred with 2019 Young Investigators Award by the Office of Naval Research (ONR). She has been to the group for her work in ‘New Unified Framework for Super-Resolution Imaging with Prior Information.’
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The promo for the Sant’Anna Business Game says, ‘A unique experience which will leave you with a lifetime of memories.’ This is so true. I came back from the competition in Pisa with a bag load of them.
The competition presents real-life business challenges on marketing, organizational strategy and operational management. Students enrolled for a bachelor’s or a Master’s degree program can enrol for the game and take an online pre-selection test before they go for a higher challenge set by one of the corporate partners (Bain & Co. this year) of the event.
What should have been a 20-minute bus ride, took hours because I had clambered onto a bus marked ‘Lam Vardi’ when I should have taken one marked ‘Lam Verde’. Such are the vagaries of foreign travel for the uninitiated. Had it not been for the kindness of a lady, who provided me the internet hotspot (I had no internet as the SIM I had carried along wasn’t working), I would still be roaming the streets of Pisa.
On the first day of the competition, the challenges were set by Luxottica and Generali. The Luxottica challenge mainly focused on recruitment problems. Generali asked us to ponder on the role of an insurance company in a world dependent on Internet of Things (IoT). We were to gauge how the scenario of the insurance industry will change once IoT penetrates into the general life of more and more people. This challenge required a good understanding of the insurance sector and required innovative thinking about ways to integrate insurance and IoT.
I didn’t win but my overall experience of the competition is amazing as I got to learn a colossal amount of things. The exposure to different kinds of people and performing together as a team despite language barriers and different perspectives was one of the most valuable takeaways from the event.
The 30-minute walk took hours as I walked aimlessly in the dark, not knowing the route. A taxi I stopped asked for a sum I couldn’t afford. I ultimately had to plead with a beer-joint owner, who was about to shut down, to give me a few minutes’ time to charge my battery (it didn’t sustain though), and then, after taking many a turn in pitch darkness, I reached my destination taking a tree as my pole star.