The problem GoodNight solves

In contemporary India, a significant portion of the population grapples with the challenge of insufficient sleep. Despite growing awareness about the importance of adequate rest, there exists a notable disparity between understanding the significance of healthy sleep habits and implementing them in daily life. This discrepancy is exacerbated by the prevailing fast-paced urban lifestyle, characterized by prolonged screen time and decreased physical activity, both of which contribute to the deterioration of sleep quality.

The ubiquity of digital devices and the allure of social media platforms have led to a marked increase in screen time among Indians, especially in urban areas. With smartphones, laptops, and tablets becoming indispensable tools for work, communication, and entertainment, individuals often find themselves engrossed in screen-based activities late into the night. The blue light emitted by electronic screens interferes with the body's natural circadian rhythm, suppressing the production of melatonin—the hormone responsible for inducing sleep. Consequently, prolonged exposure to screens before bedtime disrupts the onset of sleep and compromises its quality, leading to fragmented and insufficient rest.

Challenges we ran into

Integrating Dialogflow into our Flutter app posed a significant challenge, particularly in ensuring seamless communication between the AI chatbot interface and the user interface. Additionally, embedding our machine learning models for sleep analysis into the Flutter environment required careful adaptation to maintain performance and accuracy. Establishing a robust connection with the backend infrastructure to support these advanced features while ensuring data integrity and responsiveness was another complex aspect we navigated, striving for a harmonious blend of AI, ML, and mobile app development.