Abstract
Wireless Sensor Networks (WSNs) play a crucial role in modern communication systems, enabling efficient data collection and transmission across various domains. These networks are pivotal in applications such as environmental monitoring, industrial automation, smart cities, and healthcare systems, where real-time and accurate data is essential. The purpose of this study was to develop and validate a novel wireless sensor node architecture for gas sensing applications, with a focus on improving energy efficiency, communication reliability, modularity, and adaptability to diverse environments. The proposed design integrated multiple radio chips, a stack-based architecture, and directional antennas to improve communication robustness and adaptability. A current driver circuit was introduced to mitigate sensor saturation, ensuring accurate gas concentration measurements. The stack-based architecture enhanced modularity and scalability, facilitating seamless upgrades and compatibility with emerging technologies. Additionally, directional antennas and a dedicated medium access control protocol optimised communication efficiency and localisation accuracy. Experimental evaluations, conducted within advanced research facilities, validated the effectiveness of the proposed design under diverse environmental conditions. The hardware design approach presented in this paper focused on using low-cost, off-the-shelf components strategically integrated to deliver high functionality without increasing complexity or cost. The modular design also allows additional sensing features – such as temperature, humidity, or particulate matter detection – to be incorporated easily and economically. The results demonstrated significant improvements in data transmission reliability, power consumption optimisation, and sensor longevity. The system achieved a favourable balance between performance and affordability, making it highly suitable for scalable deployment in resource-constrained settings. This work contributes to the advancement of WSN-based gas monitoring by addressing critical challenges in hardware selection, communication efficiency, and adaptive sensor operation. The architecture presents a promising solution for deployment in dynamic and harsh environments where traditional systems may fail