Storm Alert is a weather anomaly detection application.
Storm Alert utilizes machine learning to detect anomalies based on predefined storm criteria. It precisely identifies locations and defines their statistical confidence. With daily use in mind, I aimed to create a simple UI for a fast and seamless user experience, facilitating day-to-day use.
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User Flow Created to help better understand what I was making and how I was making it.
Problem - Most storm alerting applications on the market are currently marketed at high costs and consistently underdeliver on their promises. They provide delayed updates and have subpar user interfaces, which hinder effective decision-making during critical weather events. Having dealt with these issues firsthand through his business, Bell Automation Services was approached to create one for a construction company. This would enable them to use it for finding work and undercutting the market.
Solution - Create a storm alerting application that utilizes machine learning to detect anomalies based on predefined storm criteria provided by the client. Additionally, ensure precise identification of the location and establish the statistical confidence level.
