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Rationale: Traditional fire alarms loudly siren to alert the occupants in the building, lacking detailed information about the fire’s location, severity, and fire type. Due to this flaw, people could get trapped or stuck in burning buildings, leading to severe injury or even death. Due to the lack of information given by traditional fire alarms leading to severe injury, scientists have attempted to develop a new and improved alarm system, further minimizing fire-related injury and casualties.
Objectives: This study was designed to develop an advanced alarm system equipped with voice directing MP3 to inform occupants of the building and IoT functionality, including the type of fire to assist fire department professionals.
Procedures: The Voice Directing Fire Alarm System (VDFAS) was created with the Arduino Yun board, an MP3 player, and multiple sensors including flame, carbon monoxide, temperature, carbon dioxide, and TVOC sensors were connected together to determine the type of fire, the location of the fire, and can email such information to individuals or the fire department. The individual sensors were calibrated and tested as well as the MP3 player was calibrated for audibility. The IoT functionality of the Arduino Yun board was also tested as well as the entire VDFAS system was tested using a self-scoring survey on audibility, intelligibility, reliability, and acceptability.
Results: When tested, the VDFAS was able to alert people with higher efficiency compared to traditional fire alarms. On the scoring survey, the intelligibility, reliability, and acceptability of the VDFAS scored much higher than the two other traditional fire alarms researched and tested and scored lower in audibility than the commercial alarms.
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