Abstract:
This work delves into the urgent issue of air pollution caused by unroadworthy vehicles,
particularly in light of the growing concerns about climate change. In Kenya, UNEP
estimates that 90% of urban air pollution in rapidly growing cities like Nairobi comes
from motor vehicles. Through the application of cutting-edge IoT systems, our aim is
two-fold: first, to pinpoint these vehicles and, second, to mitigate their detrimental
environmental impacts. By seamlessly integrating advanced sensor technologies with
real-time monitoring, our proposed solution advocates for sustainable transportation
practices, ultimately leading to improved air quality and reduced greenhouse gas
emissions. The system compromises of; proximity sensors (PIR sensor and NDIR sensor),
ESP32 OV2640 board with built in microcontroller with a ttgo camera, WIFI module
and Bluetooth module, A GSM module and a trained machine learning model. The
motion sensor (PIR sensor) acts as a switch as once triggered it activates both the camera
and carbon monoxide sensor (NDIR sensor) which collect data and send it to a central
database. Need for implementation of machine learning is crucial based on a number of
reasons: Majority of the roads in third world countries are A2 roads and congestion is the norm
as there is high level emission within the small area allocated for the road. In addition, the roads
are at times occupied by other parties such as pedestrians, animals crossing the roads or even
a
still, cyclists. Due to the challenges mentioned above, our proposal goes miles ahead by
incorporating k-means clustering CNN machine learning model for image processing. This will
enable differentiation between motor vehicles and non-motor vehicles. Our project is not
only justified but also crucial in the face of the substantial health and environmental
risks posed by air pollution. Traditional inspection methods have proven inadequate,
necessitating the integration of IoT technology for a more robust approach. By utilizing
IoT devices and image processing, we're enabling continuous monitoring of vehicle
emissions and roadworthiness, leading to timely intervention measures.
