Getting Started with Drought Prediction and Monitoring
- Weather Impacts human, as well as business without bias and understanding the impact of weather conditions, empowers industries and human to make smarter decisions about the potential damage caused by the winds, rain, and flooding in the aftermath of the storm.
- Big Data technologies help us to integrate and process large datasets, mathematical algorithms with high computing power.
- Using Machine learning and Deep Learning, the industry can predict and forecast the local Weather Conditions and do the analysis of Retail Sales, historical weather data mapping with Sales, Demand Planning, Forecasting, GIS-based Analytics.
Challenge for Building Real Time Ingestion and Processing Platform
- Real Time Data Ingestion and Processing of data from 280 Weather station with defined Interval and message length of data with Real-Time Analytics and Weather Forecasting for Drought Prediction.
- Drought Weather Forecasting to examine the beginning and end of the drought and detects, analyze and measure the extent of drought with strong statistical Data Points.
Solution Offerings for Deep Learning Based Platform
- SPEI (Standard Precipitation Evapotranspiration Index) to fulfill all the requirements of the drought index.
- Convert the collected data from messy to tiny format data.
- Perform Forecasting using Holt-Winters forecasting method for predicting the future occurrence and extent of drought.