In order to enhance the early warning ability of monitoring and early warning systems and strengthen fire control, the author proposes to design a high-rise building fire safety monitoring and early warning system based on the Internet of Things. The system consists of two parts: hardware and software design. The hardware is implemented by establishing a DS18b20 temperature sensor and associating it with a relay control module; The software sets fire interactive warning instructions in the reverse recognition monitoring database for implementation. Select a high-rise building to test the warning system. The test results indicate that: When testing the monitoring and early warning effects on different floors, using a single-chip microcontroller home fire monitoring system and a cultural relic building fire safety early warning system, the average monitoring recognition rates were 83.82% and 85.93%, respectively, with an average reverse recognition error of 0.0551 and 0.0371, and an average early warning response time of 4.81 s and 1.81 s, respectively. The monitoring recognition rate, reverse recognition error, and early warning response time were all higher than the standards in Table 1; When using this system, the average warning response time is about 1.00 s, controlled within the standard requirement of 1.02 s, with only 1–5 layers exceeding 1.01 s. This value is relatively low and can meet application requirements. Conclusion: The system has high coverage recognition rate, small monitoring error, and fast warning speed. For complex high-rise buildings, accurate data can be obtained, which has practical application value.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Design and Implementation of Fire Safety Assessment and Early Warning System for High Rise Buildings

  • Yanmin Zhang

摘要

In order to enhance the early warning ability of monitoring and early warning systems and strengthen fire control, the author proposes to design a high-rise building fire safety monitoring and early warning system based on the Internet of Things. The system consists of two parts: hardware and software design. The hardware is implemented by establishing a DS18b20 temperature sensor and associating it with a relay control module; The software sets fire interactive warning instructions in the reverse recognition monitoring database for implementation. Select a high-rise building to test the warning system. The test results indicate that: When testing the monitoring and early warning effects on different floors, using a single-chip microcontroller home fire monitoring system and a cultural relic building fire safety early warning system, the average monitoring recognition rates were 83.82% and 85.93%, respectively, with an average reverse recognition error of 0.0551 and 0.0371, and an average early warning response time of 4.81 s and 1.81 s, respectively. The monitoring recognition rate, reverse recognition error, and early warning response time were all higher than the standards in Table 1; When using this system, the average warning response time is about 1.00 s, controlled within the standard requirement of 1.02 s, with only 1–5 layers exceeding 1.01 s. This value is relatively low and can meet application requirements. Conclusion: The system has high coverage recognition rate, small monitoring error, and fast warning speed. For complex high-rise buildings, accurate data can be obtained, which has practical application value.