Assistive Vehicle for Surveillance in Remote Areas

Conventional surveillance systems often struggle to detect hidden or invisible threats such as landmines, hazardous gas leaks, accidental fires, or unknown intruders especially in remote or high-risk areas. Static cameras and human monitoring delay real-time threat response and reduce coverage efficiency. This paper presents an aid support vehicle that aims to improve and support surveillance and real-time detection of threats in these petitioning spaces. The vehicle installs a metallic detector for detecting landmines or any metallic object under the soil, a temperature sensor for perceiving fire danger and a gas sensor for a poisonous gas. It even includes ESP32-CAM module with Python image processing by Haar Cascade and ResNet for both face detection and recognition. The live video along with environmental data is send through Wi-Fi to a distant webpage using the IOTBeginner platform. Known intruders are shown through a trained model and unknowns are reported for prompt feedback. This IoT-enabled system improves safety, reduces human risk, and provides continuous surveillance through automation and edge-level artificial intelligence.