Design and Implementation of a Fire Detection andControl System with Enhanced Security and Safety for Automobiles Using Neuro-Fuzzy Logic
Title | Design and Implementation of a Fire Detection andControl System with Enhanced Security and Safety for Automobiles Using Neuro-Fuzzy Logic |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Sowah, R., Ofoli, A., Koumadi, K., Osae, G., Nortey, G., Bempong, A. M., Agyarkwa, B., Apeadu, K. O. |
Conference Name | 2018 IEEE 7th International Conference on Adaptive Science Technology (ICAST) |
Date Published | Aug. 2018 |
Publisher | IEEE |
ISBN Number | 978-1-5386-4233-7 |
Keywords | alcohol detection, alcoholdetection, anti-theft systems, Arduino Mega 2560, automobiles, biometric ignition, biometric ignition subsystem, C++11, central control unit, Control System, data fusion, efficiency 80 percent, efficiency 95 percent, engine control, enhanced safety measures, enhanced security, Fingerprint recognition, fire detection, fire detection subsystem, Fires, fuzzy control, Fuzzy logic, fuzzy logiccontrol, fuzzy neural nets, Global Positioning System, Global Positioning System based vehicle tracking, ignition, integrated microcontroller-based hardware, Metrics, microcontrollers, modern automobiles, multisensor-based fire detection, Neural networks, neuro-fuzzy logic, neuro-fuzzy system, neurocontrollers, pubcrawl, resilience, Resiliency, road safety, road traffic control, security, security mechanisms, sensor fusion, software system, system submodules, traffic engineering computing, two-step ignition, vehicle architecture, vehicle tracking, vehicle tracking subsystem |
Abstract | Automobiles provide comfort and mobility to owners. While they make life more meaningful they also pose challenges and risks in their safety and security mechanisms. Some modern automobiles are equipped with anti-theft systems and enhanced safety measures to safeguard its drivers. But at times, these mechanisms for safety and secured operation of automobiles are insufficient due to various mechanisms used by intruders and car thieves to defeat them. Drunk drivers cause accidents on our roads and thus the need to safeguard the driver when he is intoxicated and render the car to be incapable of being driven. These issues merit an integrated approach to safety and security of automobiles. In the light of these challenges, an integrated microcontroller-based hardware and software system for safety and security of automobiles to be fixed into existing vehicle architecture, was designed, developed and deployed. The system submodules are: (1) Two-step ignition for automobiles, namely: (a) biometric ignition and (b) alcohol detection with engine control, (2) Global Positioning System (GPS) based vehicle tracking and (3) Multisensor-based fire detection using neuro-fuzzy logic. All submodules of the system were implemented using one microcontroller, the Arduino Mega 2560, as the central control unit. The microcontroller was programmed using C++11. The developed system performed quite well with the tests performed on it. Given the right conditions, the alcohol detection subsystem operated with a 92% efficiency. The biometric ignition subsystem operated with about 80% efficiency. The fire detection subsystem operated with a 95% efficiency in locations registered with the neuro-fuzzy system. The vehicle tracking subsystem operated with an efficiency of 90%. |
URL | https://ieeexplore.ieee.org/document/8507143 |
DOI | 10.1109/ICASTECH.2018.8507143 |
Citation Key | sowah_design_2018 |
- Resiliency
- ignition
- integrated microcontroller-based hardware
- Metrics
- microcontrollers
- modern automobiles
- multisensor-based fire detection
- Neural networks
- neuro-fuzzy logic
- neuro-fuzzy system
- neurocontrollers
- pubcrawl
- resilience
- Global Positioning System based vehicle tracking
- road safety
- road traffic control
- security
- security mechanisms
- sensor fusion
- software system
- system submodules
- traffic engineering computing
- two-step ignition
- vehicle architecture
- vehicle tracking
- vehicle tracking subsystem
- engine control
- alcoholdetection
- anti-theft systems
- Arduino Mega 2560
- automobiles
- biometric ignition
- biometric ignition subsystem
- C++11
- central control unit
- Control System
- data fusion
- efficiency 80 percent
- efficiency 95 percent
- alcohol detection
- enhanced safety measures
- enhanced security
- Fingerprint recognition
- fire detection
- fire detection subsystem
- Fires
- fuzzy control
- Fuzzy logic
- fuzzy logiccontrol
- fuzzy neural nets
- Global Positioning System