big data and machine learning for phd in water management with environment - phdassistance

BIG DATA AND MACHINE LEARNING FOR PHD IN WATER MANAGEMENT WITH ENVIRONMENT

An Academic presentation byDr. Nancy Agnes, Head, Technical Operations, Phdassistance Group www.phdassistance.comEmail: info@phdassistance.com

In briefWater ManagementRecent PhD Research BDABig Data in Water Management with Environment Machine Learning in Water ManagementFuture Scope for Big Data and Machine Learning in Water Management

Outline

TODAY'S DISCUSSION

In briefRain Water Harvesting is the best method to invest the Water, which induces the groundwater levels.

Big data manipulates and deals with the massive amount of datasets generated via dynamic data that will generate every second.

Due to many contaminants in the groundwater, the purity of drinking water diminishes its certainty.

Contd . . .

Water Management

Need not panic about the word Water Management.

It stores and preserves the water from rain, kitchens, gardens, and other areas for future purposes.

Contd. . .

71% of the World's water content is scarce, to 60% due to improper and irresponsible water management.

Rain Water Harvesting is the best method to invest the Water, which induces the groundwater levels.

It gives double benefits, Increases the water table and ensures the healthy Environment.

Water Management is the stage, where the PhD scholars using Big Data Analytics have an enormous scope to develop the solutions for the crisis.

Contd . . .

Recent PhD Research BDA

To safeguard the Environment and preserve the Water for next-generation, many researched it in ideal ways.

The recent research article from Brazil concludes with System analysis models that lend a hand to address and track the variety of water risks and issues all over the World.

Contd . . .

As the name suggests, Big data manipulates and deals with the massive amount of datasets generated via dynamic data that will generate every second.

There are many tools in Big Data to manipulates the data and produce accurate results.

The work proposed that using Big Data and IoT and monitoring the Environment changes, based on differences, will generate the data.

These data will be used for analytics purpose.Contd . . .

BIG DATA

Machine Learning is the emerging technology to reduce the complex manipulations and computations by Humans.

The Machine will learn itself according to its source code, what exactly it has to do.

Machine Learning implies it’s root on Water Management to reduce the unsolvable manual complexities.

ML possesses its algorithms and techniques for all kind of Data Analytics and Data Science purposes.Contd . . .

MACHINE LEARNING

Super-vised Machine Learning algorithms Unsuper-vised Machine Learning algorithms Artificial Neural NetworksBadger Prairie Needs Network Gradient Boost Regression algorithm

The proposed article pictures the Water's quality by remote-sensing inrural areas using Machine Learning algorithms based on image pixels.

Those images will be treated as evident data for Data analysis procedures.

Contd . . .

Some of the familiar algorithms,

Big Data in Water Management with Environment

To kickstarts Farming and improves crop production, a bit of need for technology in it.

Article 4 proposed the theory of Human-Centered Intelligent Systems to monitor and track the crop's growth, climatic conditions, pest control, manure rate through sensors and information systems.

The impact of the Environment in Water Management hits the groundwater levels in the Urban life cycle.

The proposed article 5 will resolve the issue of water scarcity due to climatic conditions.

Contd. . .

MachineLearning in Water Management

The proposed work 6 enhances the originality using the Machine learning algorithm XG Boost, ANN, to analyze the groundwater's purity texture and whether it is legitimate to consume.

Contd . . .

Due to many contaminants in the groundwater, the purity of drinking water diminishes its certainty.

The impact of Anthropogenic activities shakes and hits biodiversity.

The deviation and extinction of aquatic biodiversity are dueto emissions.

anthropogenic

The core review of literature 7 is to preserve marine biodiversity usingMachine Learning algorithms.

Contd. . .

Future Scope for Big Data andMachine Learning in Water Management

BDA and ML have already planted its root deeply.

Still, Water Management, Environmental Ethics, Farming and Agriculture is in hunger to feed with technology.

Let's drive into some future ehancements for BDA and ML in respective fields,

Contd . . .

1.BDA and ML lend a hand to improve the water utilities, which scrutinize the Customer Service.

EXAMPLE: Intensity of purity can be determined efficiently.

2.Data Analytics has the long way to go, but Water preservation doesn't have the same. Using BDA, we can efficiently predict future climatic conditions and generate the report. Based on the report, further forecasting procedures will be enhanced.

EXAMPLE: Identify the water scarcity region and Magnifies the causation for the scarcity. Put forth an action accordingly.

Contd. . .

3.Using Machine Learning algorithms, we can efficiently forecast the project's cost- effectiveness, which implemented to preserve Water. Every detail will be monitor and control the water level deviations.

EXAMPLE: Comparing with other algorithms, machine learning algorithms produces best results with high accuracy

4.Communicating through sensors, forecasting the water levels using Machine Learning algorithms is emerging.

EXAMPLE: To access and analyse the remote-sensing areas will become tedious one. Like Quarries, Mine fields and Marine areas in such cases, Sensors is mandatory.

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