An All-Girls Team’s Innovative IoT Solution at PIWOT 23-Hackathon – DATAQUEST

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In a significant stride toward gender inclusivity and innovation, the PIWOT 23-Hackathon witnessed an outstanding display of talent from an all-girls team, challenging conventional gender stereotypes in the tech and engineering domain.

In a world increasingly advocating for gender equality, the realm of Science, Technology, Engineering, and Mathematics (STEM) is witnessing a notable surge in discussions surrounding the participation of girls. This shift is particularly pronounced in events like Hackathon 23 at PIWOT, where a remarkable development unfolded. Among the 30 finalists competing for the coveted winner’s position, a standout occurrence emerged – the presence of an exclusively all-girls team.

Traditionally, STEM fields, especially engineering, have been characterized by a gender disparity, with fewer girls pursuing careers in these domains. Stereotypes often perpetuate the notion that girls are more inclined towards software and coding, making their representation in other engineering disciplines comparatively sparse.

The Innovative Solution

The spotlight of this report falls on the unique project undertaken by the all-girls team at Hackathon 23. Sai Disha Jayaram, Umme Ayman Z, Rutuja Rahul Deuskar pursuing B.E in Information Science at RV Institute of Technology and Management.; their project revolves around the development of an accident alert system, leveraging sensors to send instant SMS notifications to emergency contacts in the event of an accident. What sets their solution apart is its independence from internet connectivity, utilizing SMS as the primary platform for alerts.

Central to their project is an alcohol sensor designed to detect whether the driver is inebriated beyond safe limits. If an excessive level of alcohol is detected, the system triggers an alert, preventing the vehicle from being operable. Another unique feature is that once the accelerometer detects an overspeed it automatically reduces the speed to the safe limit. This dual-function system, applicable to both private and commercial vehicles, addresses critical safety concerns on the roads.

Target Audience and Market Differentiation

The team underscores the relevance of their solution for a broad spectrum of users, emphasizing the unique challenges faced by long-haul truck drivers and operators of heavy commercial vehicles. These individuals often operate under intense pressure, separated from their families for extended periods. The real-time alerts generated by the sensor-based system are tailored to reach various stakeholders, including hospital emergency rooms, police stations, and pre-designated family contacts in the event of an accident.

Addressing concerns about competition from smart cars, the team positions their solution as distinctly pocket-friendly. They argue that a substantial portion of the consumer base comprises non-smart car users and commercial vehicle drivers. By catering to this extensive demographic, they aim to demonstrate that their Internet of Things (IoT) based solution not only enhances safety but also minimizes the time required for emergency response, thereby reducing the loss of lives in accidents.

In conclusion, the project undertaken by the all-girls team at Hackathon 23 not only challenges gender stereotypes in STEM but also introduces an innovative, practical, and inclusive solution to enhance road safety, making a compelling case for the broader adoption of their IoT-based accident alert system.

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