To create a system of vehicle-mounted sensors that performs accurate air quality sensing.
Fuel conservation is among the leading problems that the world faces now. The first step, however, should be to identify where we can conserve. In Delhi, buses are the most widely used mode of public transportation among other public transit services. Their breakdown is a major cause of inconvenience not only to commuters but also to transit agencies. The aim of this project is to study the impact of the breakdown of public transport buses on traffic and fuel costs due to congestion with the help of machine learning models and thresholding techniques.
GPS signals of buses were analysed to breakdown patterns and this helped in drawing monetary inferences in terms of fuel costs. A scheduling algorithm is also proposed for creating a timetable, aiming to minimise passenger wait time at bus stops along with a real-time dashboard for bus locations. In monetary terms, the total amount sums up to about Rs 1,84,000, wasted in fuel per day owing to the breakdown of buses in Delhi.