Digital Water

As the water industry faces increasingly complex challenges from climate change, increased population growth, and aging infrastructure on one hand; and the digital industry explodes with new technology including developments in artificial intelligence, machine learning and neural networks on the other, lies an innate opportunity for “digital water”.

How do these technologies aid in managing water system?

Prove cost reduction
Reduction in maintenance costs – instead of buy expensive new instrumentation, utilize existing instrumentation to predict water quality accurately with no new probes.
Reduce the amount of new water plant builds utilizing existing infrastructure more efficiently
Turn historic and current data into management information and future predictions
Use historic gathered data to feed AI, and identify patterns for forward data point predictions and decision making.
Allow machine learning to make or recommend best fit decision making reducing the need for human input

Kelnir Projects Digital water process

Understand and establish value proposition.
Selecting the neural network architecture and the relevant type of neural network and AI required
Establish the multiple data inputs and associated processes
Design and structure the machine learning process
Implement pilot solution and validate with non digital measures
Deploy AI and machine learning process.
Establish decision making protocols based on pattern recognition
Monitor the machine decision making

IOT and other Sensors

Use existing sensors or new sensors for data
Establish virtual sensor profile

Communication

Mobile networks
Industrial Data Networks

Data Storage and Cleaning

Cloud storage
Cloud data management

Decision Making and Action

Machine Learning
Human Oversight

Prediction and Forecasting

Alarms and discrepencies are highlighted

AI Pattern Recognition

Time series pattern recognition
Other statistical methods