Echo Alert: Obstacle-Sensing Aid for the Hearing Impaired
Applied Technology- Grade:
- 8
- Teacher:
- Karen Maninang
Individuals who are deaf or hard of hearing face increased safety risks in traffic environments because they may not detect critical emergency road sounds such as police sirens, car horns, or approaching emergency vehicles. This limitation reduces situational awareness and can increase the likelihood of accidents. While assistive technologies exist, many solutions are costly, bulky, or not optimized for real-time, wearable safety applications. This project presents the design, development, and evaluation of ECHO ALERT, a low-cost, microcontroller-based audio detection system that converts emergency-level sound signals into visual alerts. The system integrates an Arduino Nano microcontroller with an analog microphone sound sensor to continuously sample environmental audio input. A programmed algorithm calculates peak-to-peak sound amplitude within a defined sampling window and compares the signal to a calibrated threshold equivalent to approximately 60 decibels. When the threshold is exceeded, a visual LED alert is activated to notify the user. The prototype was assembled using accessible hardware components and programmed through Arduino IDE. Calibration was performed using real-time amplitude monitoring via the Serial Plotter to establish reliable threshold detection. A wearable enclosure was designed using Onshape and fabricated with a 3D printer to enhance portability and real-world applicability. Controlled experimental trials were conducted under five sound conditions: siren (100 dB), music (80 dB), clapping (60 dB), speech (40 dB), and silence (5 dB). Each condition was tested for 60 seconds under consistent environmental conditions. LED activation was recorded as binary data to evaluate detection accuracy and false trigger rate. The system achieved 100% correct response under controlled testing, successfully distinguishing sounds above and below the calibrated threshold. Although the system reliably detected high-intensity sounds, results indicate that detection is currently based on amplitude rather than specific frequency recognition. This highlights a key engineering limitation and provides direction for future innovation, including frequency filtering, vibration-based haptic alerts, and real-world traffic validation. Overall, this research demonstrates that affordable microcontroller technology can be engineered into a functional assistive safety device. ECHO ALERT provides a scalable foundation for wearable, multi-sensory alert systems that could enhance independence, situational awareness, and roadway safety for individuals who are deaf or hard of hearing.