TorqueMax-RS: An IoT-Synchronized Deep-Shaft Robotic Extraction Framework for Borewell Emergency Intervention

Abstract

Rescuing victims trapped in deep and narrow borewells is highly challenging due to confined space, lack of visibility, and the inability of humans to access such environments directly. To overcome these limitations, this work proposes a compact and remotely operated Borewell Rescue Robot (BRR) developed using an Espressif Systems Processor (ESP32-CAM) Microcontroller Unit (MCU), designed to provide real-time monitoring and precise control during rescue operations. The system integrates live video streaming with mechanical actuation through a wireless interface, allowing operators to guide the robot safely from a remote location. A 32-bit embedded processor supported by Pseudo-Static Random Access Memory (PSRAM) enables smooth Video Graphics Array (VGA) image transmission, while WebSocket-based communication ensures continuous and low-latency data exchange. The robotic mechanism utilizes dual high-torque servo motors for gripping and positioning, enabling accurate manipulation within confined vertical shafts. To address poor lighting conditions, a Pulse Width Modulation (PWM) controlled Light Emitting Diode (LED) system is incorporated for effective illumination. The software follows an asynchronous, event-driven architecture using the ESPAsyncWebServer framework, allowing simultaneous handling of video streaming and control commands without delays. Additionally, a fail-safe mechanism is implemented to reset actuators and disable critical components in case of communication loss, ensuring safety and reliability. The system operates through a Wireless Fidelity (Wi-Fi) Access Point (AP), eliminating dependency on external infrastructure and enabling deployment in remote locations, making it a scalable and efficient solution for emergency rescue scenarios.