Smart Flood Detection and Impact Mapping System Using GSM-Based Alerts and Satellite Image Heat Maps

Floods rank among the most damaging natural hazards, and the harm to people and property grows sharply when warnings come late or never reach the affected community.Most IoT flood monitors described in recent literature depend on internet links, cloud back-ends and smartphone applications, which are exactly the services that become congested or fail during a disaster; moreover, they seldom assist with damage assessment after the water recedes.This paper presents a low-cost, two-stage framework that addresses both phases.The first stage is an Arduino-based field node that reads a water level sensor and a rain sensor, grades the situation as Normal, Warning or Danger against fixed thresholds, drives local LED and buzzer indicators, and, at the Danger grade, sends SMS messages through a SIM800L GSM modem without needing the internet.A battery or solar supply allows deployment at remote sites.The second stage is a Python pipeline that compares pre-and post-flood satellite images, isolates newly inundated regions, assigns severity classes and renders red-orange-green heat maps together with the affected area in km².A bench prototype using a water container demonstrates the sensing and indication logic.The framework supports early warning for residents and farmers and provides authorities with a spatial view for planning relief.