×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerWomen’s safety remains an urgent challenge, particularly in moments when conventional panic button devices fail due to a victim’s inability to act or poor network coverage. To overcome these shortcomings, TRIAD-Lite is introduced as an IoT-enabled wearable framework that unites multimodal physiological sensing with lightweight deep learning for proactive distress identification. The system captures heart rate, blood pressure, galvanic skin response, and motion patterns, while incorporating a triple-tap gesture to confirm user intent, all processed locally on a Raspberry Pi for real-time inference. Unlike reactive mechanisms, this design anticipates danger by analyzing variations in physiological signals that often precede visible distress. Communication reliability is reinforced through a hybrid strategy: alerts are transmitted via GSM or Wi-Fi under normal conditions, but in the event of limited connectivity, a LoRa-based backup ensures long-range transmission. Experimental analysis using simulated datasets yielded an AUC of 1.000 with flawless precision and recall, highlighting the model’s reliability and calibration. Further field evaluation demonstrated that LoRa maintained connectivity across 5.7 kilometers with complete packet delivery, proving effective for both rural and urban environments. By combining predictive analytics, gesture-based confirmation, and dual communication layers, TRIAD-Lite offers a scalable, privacy-conscious, and highly resilient framework that strengthens women’s safety and extends protective technology into regions where conventional systems often fail.
This study simulates a free-space optical communication system that uses optical beams with varying responses to atmospheric disturbances to secure transmitted data. Atmospheric turbulence was modeled with high accuracy to replicate real-world conditions closely. Non-diffracting beams were generated and used to represent optical beams and compared in two scenarios, conventional data transmission, and optifusion data protection. This approach facilitated a comprehensive analysis of the transmission environment and the effectiveness of optifusion, identifying the most suitable non-diffracting beam types for secure data propagation. By analyzing the values of key performance metrics of the selected non-diffracting beams across different weather conditions and long propagation distances, the study demonstrated the simulation system's reliability and the optifusion method's effectiveness in enhancing data security. The results showed that non-diffracting beams resist atmospheric turbulences strongly, emphasizing their potential for secure, long-range free-space optical communications.