Intelligent, Low Cost, Real Time Flame Alarm System

A fire can cause serious damage in everywhere in the world. Fire and rescue department is cooperatively working on flame prevention if there any fire happened. Lack of flame detection intelligent system and human visualization causes delay in contacting with fire department. Therefore, more causality happened before any action taken by the fire and rescue team. This research shows a design of real time flame detection system. This system consists of a non-contact flame sensor and an onboard Wi-Fi module embedded controller. A mobile apps is also developed to communicate with the flame detection system. Therefore, if the sensor detects flame then the apps will able to inform this information to the fire and rescue department in real time basis. This system is very useful for preventing our lives from fire.

[1]  Thiago de Almeida Oliveira,et al.  ZigBee Wireless Dynamic Sensor Networks: Feasibility Analysis and Implementation Guide , 2016, IEEE Sensors Journal.

[2]  Linqing Gui,et al.  RSS-based indoor localisation using MDCF , 2017, IET Wirel. Sens. Syst..

[3]  Xiao Ma,et al.  Intelligent Healthcare Systems Assisted by Data Analytics and Mobile Computing , 2018, 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC).

[4]  Yacine Challal,et al.  Energy efficiency in wireless sensor networks: A top-down survey , 2014, Comput. Networks.

[5]  Adnan M. Abu-Mahfouz,et al.  A key distribution scheme using elliptic curve cryptography in wireless sensor networks , 2016, 2016 IEEE 14th International Conference on Industrial Informatics (INDIN).

[6]  Eduardo Paciencia Godoy,et al.  ZigBee Wireless Dynamic Sensor Networks: Feasibility Analysis and Implementation Guide , 2016 .

[7]  Amir Masoud Rahmani,et al.  Systematic survey of big data and data mining in internet of things , 2018, Comput. Networks.

[8]  Abbas Javed,et al.  Smart Random Neural Network Controller for HVAC Using Cloud Computing Technology , 2017, IEEE Transactions on Industrial Informatics.

[9]  Qingwu Hu,et al.  A Case Study on Spatio-Temporal Data Mining of Urban Social Management Events Based on Ontology Semantic Analysis , 2018, Sustainability.

[10]  Dilip Kumar,et al.  Performance analysis of energy efficient clustering protocols for maximising lifetime of wireless sensor networks , 2013, IET Wirel. Sens. Syst..

[11]  Debashis De,et al.  Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network , 2016, IET Wirel. Sens. Syst..

[12]  Gerhard P. Hancke,et al.  Software Defined Networking for Improved Wireless Sensor Network Management: A Survey , 2017, Sensors.

[13]  Zeeshan Ali Khan,et al.  Using energy-efficient trust management to protect IoT networks for smart cities , 2018, Sustainable Cities and Society.