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SECURE DUAL-MODE PERSONAL ALERT DEVICE WITH GSM, GPS TRACKING

HIMA BINDU SAMMETA

(02 – 2026)

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Emergency response delays endanger everyone—elderly falls, traveler assaults, worker accidents. NCRB 2024 reports 445,000 vulnerability incidents requiring instant location sharing. Smartphone apps fail without internet (40% rural coverage) or when users cannot manually activate. Our prototype eliminates these gaps with complete autonomy: panic button delivers 10ms response, automatic sensors trigger independently, and GSM ensures 99.7% Pan-India delivery regardless of data connectivity. Women’s safety continues to be a pressing concern in India, 445,000 crimes against women recorded in 2024 (NCRB). This research presents the development, testing, and validation of a cost-optimized wearable safety prototype integrating manual panic activation and automatic dual-sensor detection (accelerometer + acoustic) for emergency alerting. The system architecture employs Arduino Uno as the central controller interfaced with SIM900A GSM module (95% SMS delivery reliability), NEO-6M GPS receiver (±2.5m positioning accuracy), and ADXL345 3-axis accelerometer (96.7% fall detection accuracy over 30 trials). The end-to-end response measures 3.2 ± 0.5 seconds from trigger detection to SMS transmission containing Google Maps hyperlinks. Prototype specifications: Total cost ₹3,150 (75% cost reduction vs. ₹12,000 commercial alternatives), 5V/2A power, breadboard implementation. Extensive validation include 100 SMS transmission cycles, 72-hour stability testing, and GPS accuracy assessment across 20 locations. Key differentiators include complete 2G network independence (no internet/WiFi dependency), dual-threat detection reducing false positives to 1.8%, and rural deployment suitability leveraging India’s ubiquitous GSM infrastructure. Limitations encompass GSM signal dependency and indoor GPS performance; future enhancements target 4G migration and LiPo battery miniaturization. This work demonstrates technical feasibility and commercial viability for mass deployment addressing India’s 350 million women demographic.

 

 

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