As a Computer Engineering student at IOE Thapathali Campus, my work bridges embedded hardware systems with digital logic. While browser software solves critical problems on screen, engineering hardware that interacts with physical environments brings a completely different challenge.
For this project, I engineered an IoT-Based Emergency Response System for the Elderly, powered by an ESP32 microcontroller, integrated motion/biometric sensors, and a custom-fabricated printed circuit board (PCB).
The Problem
Traditional personal emergency alarms often rely on manual SOS buttons. In acute medical crises or sudden falls, an individual may lose consciousness or physical mobility, rendering manual triggers useless.
This system addresses that gap with:
- Automated Anomaly Detection: Continuous polling of motion modules to detect abrupt impacts and posture changes.
- Instant Wi-Fi Telemetry: The dual-core ESP32 triggers emergency alerts over local Wi-Fi without relying on a paired smartphone.
- Hardware Stability: A custom-designed PCB layout ensures stable power delivery and debounces sensor noise.
Hardware Stack & Architecture
- Core MCU: ESP32 (chosen for built-in Wi-Fi, dual-core architecture, and low-power sleep modes).
- Sensor Layer: Motion and biopotential modules capturing real-time telemetry.
- Firmware: Written in C++, implementing asynchronous interrupt routines and non-blocking network calls for low-latency alert dispatching.
- PCB Design: Schematics designed and verified through circuit simulation tools prior to physical milling and soldering.
Key Engineering Takeaways
- Hardware Debouncing & Noise Filtering: Raw sensor output on microcontrollers requires software filtering and hardware capacitance decoupling to avoid false alarm triggers.
- Power Plane Routing: Routing ground planes cleanly on custom PCBs proved critical to avoiding signal crosstalk between Wi-Fi transmission bursts and sensitive analog inputs.
Connect & Explore More
- 🌐 Portfolio: dipeshsapkota7.com.np
- 💻 GitHub Archive: dszae
About the Author:
Dipesh Sapkota is a Computer Engineering student at IOE Thapathali in Nepal, an AI/ML enthusiast, and a Video Editor & Motion Graphics Designer. Connect with him on LinkedIn or visit his Portfolio.
