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In view of the problem that the traditional fire detection node is not intelligent enough for data processing when building fire occurs, a design and evaluation method of wireless fire detection node based on multi-source sensor data fusion is proposed. Firstly, the temperature and humidity sensor, carbon monoxide sensor and smoke sensor are selected to collect three kinds of fire information eigenvalues at the same time. Secondly, the analysis and processing method of two-level data fusion is established, and the fire information is processed in STC89C52 microcontroller. The first level data fusion uses fuzzy proximity algorithm to get the eigenvectors of environmental parameters, so that the measured values are closer. The second level data fusion uses D-S evidence theory to analyze the data systematically. According to the probability distribution function after fusion, more accurate decision results are obtained. Finally, the fire signal is sent to the superior data management center through ZigBee wireless transmission network, and the alarm signal is triggered in time. The whole node design gives a complete hardware selection and software data fusion processing method. Compared with the traditional fire detection node, it significantly reduces the false alarm rate. At the same time, the node has good application effect in the experiment, and realizes a wireless intelligent fire detection node with low cost, wide application range and high intelligence.

Design and Evaluation Method of Wireless Fire Detection Node Based on Multi-source Sensor Data Fusion