Automating Government Emergency Alerts: A Low-Code, Multi-Channel System Using Microsoft Power Platform

Abstract

Government agencies across the world are experiencing immense challenges in the delivery of up-to-date and reliable emergency message to residents. The alternative is a traditional emergency communication route that is usually based on legacy technology that is hard to scale, intertwined, and capable of providing cross platform integration. This paper discusses the design and deployment of a multi-channel low-code emergency alert app on Microsoft Power Platform.

Using Power Automate, Power Apps, Dataverse, Azure Logic Apps and Azure Communication Services, the system has the capability to distribute alerts in real time via SMS, email, push notifications and social media channels. Low-code automation reduces custom code dependence and shortens the deployment time as well as increases flexibility in the dynamic nature of a crisis.

This paper is based on a mixed methodology, and uses both simulation testing to quantitatively evaluate a explored solution, and qualitative evaluation of the scalability of the explored solution, its efficiency and usability by the end users. The key findings include the fact that a proposed system enhances the speed of the alert dissemination by 40%, cuts the system downtime by 30AT, and provides the 95% reliability of communication channels.

The cost-effectiveness is augmented by the minimization of IT overhead and the simplification of maintenance of the system. Such results support the idea that low-code solutions have potential in the modernization of the emergency communication infrastructure of the civil sector, which can offer an inexpensive, scalable, and citizen-friendly solution.

This study will make a contribution both in academic as well as practical field as it has the potential to demonstrate how the process of digital transformation of governmental operations can support the resilience of crisis communications. The paper ends with suggestions on how policy integration, usage of data security can be done and how AI are good potential future ways of personalizing emergency alerts.