A pioneer study on laboratory safety WSN with improved adaptive segmentation clustering multi-hop protocol

An adaptive segmentation clustering multi-hop protocol targeting at lab safety monitoring WSN is studied in this paper. The protocol consists of two perspectives, namely abnormal data preprocessing and WSN parameter optimization. Abnormal data preprocessing contains transient abnormal data analysis, fault data preprocessing and data validity judgment. This study seeks to find an optimal scheme to reduce the system energy consumption that can extend the life cycle of network system through balancing other system indicators by optimizing adaptive parameters (e.g. hop count, hop distance, etc.). According to the structural characteristics of lab safety monitoring, the space structure based on multiple labs is studied and the structure of multiple isolated sub units (e.g. fire zones, isolation gates, etc.) is set. Correspondingly, the transmission scheme of equal interval multi-hops is introduced based on the structural design of sub units. The design facilitates the effective isolation of hidden dangers in the protection zones so as to protect the safety of the whole lab.