Acoustic Sensors data transmission integrity and endurance with IoT-enabled location-aware framework

Area of Science:

• Underwater acoustic sensor networks (UASNs)
• Internet of Things (IoT) applications
• Environmental monitoring and disaster mitigation

Background:

• UASNs face challenges like high latency, limited bandwidth, and energy constraints.
• Existing protocols struggle to optimize performance in underwater environments.
• GPS modems are often impractical for underwater node localization.

Purpose of the Study:

• To introduce an IoT-driven location-aware framework (ILAF) for enhancing UASN performance.
• To enable location determination and neighbor identification without GPS modems.
• To optimize node placement and routing for energy efficiency and reliability.

Main Methods:

• Developed an IoT-driven location-aware framework (ILAF) using non-GPS geographic coordinates.
• Implemented neighbor identification based on coordinates and transmission range.
• Optimized node placement and routing strategies within the framework.

Main Results:

• ILAF achieved a 99% packet delivery ratio (PDR), outperforming existing protocols.
• Demonstrated a 20% reduction in energy consumption compared to state-of-the-art protocols.
• Resulted in fewer dead nodes (12 after 1,000 rounds) and higher throughput (5.7 kbps).

Conclusions:

• ILAF significantly enhances UASN performance, offering superior energy efficiency and data reliability.
• The framework is suitable for real-time underwater applications requiring robust communication.
• Future work includes integrating lightweight IoT protocols (MQTT, CoAP) for further improvements.