CO Detection in High-Mileage Vehicle Cabins and Traffic Density Analysis Using Fuzzy Logic

Carbon monoxide (CO) inside vehicle cabins poses a significant health risk to passengers and can even lead to fatalities. This danger primarily arises from inadequate ventilation, which allows exhaust fumes to seep into the cabin and be gradually inhaled. CO is a gas that lacks color, odor, taste, and does not cause irritation, making it difficult to detect without proper tools. It is commonly encountered in industrial environments and is produced by the incomplete combustion of fuel in motor vehicles, heating systems, devices that burn carbon-based materials, wood stoves, train emissions, gas burning, and even tobacco smoke. However, the primary contributor is the residual combustion from vehicle engines. Given these concerns, this study aims to develop a system to monitor and control carbon monoxide concentrations within vehicle cabins using fuzzy logic. The system achieved an average error rate of 2.9% in reducing CO concentrations, with responsive fan control latency below 5 seconds. A microcontroller will serve as the core component for processing and control. The implementation of this system is expected to enable real-time detection of CO levels in the cabin and alert the driver accordingly. Ultimately, this can help reduce incidents of CO poisoning among vehicle occupants