Enabling Seamless Connectivity: Networking Innovations in Wireless Sensor Networks for Industrial Application.

Area of Science:

• Computer Science
• Electrical Engineering
• Industrial Automation

Background:

• Industrial Wireless Sensor Networks (IWSNs) are crucial for IoT applications, facing challenges in performance scalability, energy efficiency, and reliability.
• Existing systems struggle with deterministic communication and end-to-end reliability, especially for low-power autonomous nodes.

Purpose of the Study:

• To evaluate the performance scalability of mature IWSNs.
• To propose a new classification approach for industrial IoT.
• To introduce an integrated protocol framework for energy-efficient connectivity and real-time event detection in IWSNs.

Main Methods:

• Integration of 6LoWPAN, MQTT-SN, and ContikiMAC protocols for sensor nodes.
• Simulation using Contiki COOJA WSN simulator for static and moving scenarios.
• Development and deployment of a novel sensor design using selective surface activation induced by laser (SSAIL) technology.
• Evaluation of a novelty detection system (NDS) for real-time intrusion detection.

Main Results:

• Energy efficiency increased by 50%, extending battery life by 350%.
• Duplicated packets and data collisions reduced by 80%.
• Demonstrated long-term functionality and reliability of the SSAIL technology and proposed framework through simulations and experimental validation.

Conclusions:

• The proposed integrated protocol framework and sensor design significantly improve IWSN performance metrics.
• The methodology is effective for developing telemetry node networks, enabling accurate event and breach detection in industrial IoT.
• The study provides a comprehensive assessment of challenges and solutions for reliable and energy-efficient industrial IoT systems.