Ended on 12th Sep'22 03:30 PM (Coordinated Universal Time)
Data Sprint 89 - Sensor-Fusion Smoke Detection Classification
Detect smoke with the help of IOT data and trigger a fire alarm.
105
Easy
Challenge Starts
09 Sep 03:30 pm
Registration Ends
12 Sep 03:30 pm
Challenge Ends
12 Sep 03:30 pm
A smoke detector is a device that senses smoke, typically as an indicator of fire. Smoke detectors are usually housed in plastic enclosures, typically shaped like a disk about 150 millimetres (6 in) in diameter and 25 millimetres (1 in) thick, but shape and size vary.
Smoke detectors save a lot of lives. For example, the number of fire victims fell by more than 48% in France from 1982 to 2012 and 56% in the UK from 1982 to 2013. These reductions can largely be linked to increased fire safety regulations and smoke detectors. In the U.S. 96% of all homes have smoke alarms and approximately 20% of homes with smoke alarms have non-operational smoke alarms. It is estimated that if every home had working smoke alarms, U.S. residential fire deaths could drop by 36%, with nearly 1100 lives saved per year. With an increasing number of smoke detectors, false alarms became a problem. The number of false fire alarms is increasing continuously, which is a severe issue for firefighters.
Your task is to devise a Machine Learning model that helps us detect smoke with the help of IOT data and trigger a fire alarm, thereby preventing any mishap.