5TH ABC Challenge: Forecasting Thermal Comfort Sensations for Heatstroke Prevention: Leveraging Physiological Data for Better Outcomes

Abstract

Preventing heatstroke is of utmost importance as it poses a significant threat to life and can lead to severe health complications and even death. Heatstroke occurs when the body's internal temperature reaches hazardous levels, typically due to prolonged exposure to high temperatures or intense physical activity in hot weather. Recognizable symptoms of heatstroke encompass confusion, rapid heartbeat, accelerated breathing, seizures, and loss of consciousness. Moreover, projections suggest a 260% surge in mortality rates attributed to heat-related incidents by the 2050s. Consequently, it is crucial to familiarize oneself with heatstroke symptoms in advance.

In this challenge, participants need to forecast the personal thermal comfort sensations using physiological data on the different days' given past data. The training dataset comprises timestamped observations for 23 individuals over a span of 6 days. Each observation consists of a specific feature value at a particular time. Your goal is to create a machine-learning model that can forecast the individual’s thermal sensations based on this historical data.

Instructions:

The challenge is open to students (undergraduate, graduate, doctoral), researchers, and practitioners.
To participate in the challenge, a team must register first indicating a team name, members, and representative. Registration closes June 15, 2023.
Teams may have 1 to 10 members.
A person may not belong to two teams simultaneously (unless a supervisor).
Members of Lopez Lab (the organizer) are not eligible to participate in the challenge.
Only teams who submit their results and paper to the ABC2023 conference may be eligible for the prize.
This document may be updated at any time without notice.