Solving Global Water Crisis With Artificial Intelligence
The water crisis has become one of the major concerns across the globe. A report suggests that the US alone wastes 7 billion gallons of drinking water per day. As only less than one percent of earth surface water is suitable for human consumption, it becomes crucial that we save water so that our future?
- AI techniques such as Artificial Neural Networks and Support Vector Machine (SVM) are being popularly used as they are less cost-effective when compared to big data mechanisms.
- They used the precipitation, temperature and groundwater level data as the vector for neural networks for prediction.
- They used aquifer depth, aquifer sensitivity to pesticide, pesticide leaching and samples for a specific time as vectors for these ANN.
- They used previous data of groundwater level, tide level and precipitation as vectors.
- Performance of ANN prototypes was compared using correlation coefficient, mean squared error, and coefficient of efficiency.