Just Quit: A Modern Way to Quit Smoking

Literature Review

Smoking is a significant global public health concern responsible for millions of deaths yearly. Smoking is becoming one of the leading causes of early death. According to the World Health Organization, around 8.2 million people die yearly from smoking. (W.H.O., 2022). According to health experts in U.A.E., over 40% of university students began smoking just at the age of 14.

Despite the well-known health risks associated with smoking, many people still find it challenging to quit. The development of digital interventions, such as mobile applications, has provided an opportunity to help people quit smoking. Quit smoking applications are a modern way to allow individuals and assist them in their journey to quit smoking using machine learning technology. Several apps in the market help people reduce or quit their smoking habits. A Digital Intervention to Reduce Smoking in the United Arab Emirates (Abdulrahman et al., 2019) describes a mobile application that helps users quit smoking by providing them with motivational messages and educational materials. Another such application, called Breatheasy, provides users with personalized messages and advice to help them quit smoking. Such applications help users keep track of their smoking habits and provide them with distractions through games and exercise suggestions to help them fight the urge to smoke. Research on quit-smoking applications and the rising trend in the use of digital technology indicate that mobile applications can be a beneficial tool in assisting individuals who wish to quit smoking and require extra help in their journey to reduce their smoking habits.

However, all existing quit-smoking applications require users' input to track their health status and smoking habits. Many, if not all, quit-smoking applications can be ineffective e because they need a high amount of user participation. These applications rely on the user to constantly evaluate their progress and record the number of smoking lapses, which is very unpleasant and requires much effort, making it demotivating for them to use such applications.

The use of smartwatches equipped with accelerometers and gyroscope sensors has gained popularity in various applications such as health monitoring, fitness tracking, and activity recognition. These sensors provide an opportunity to monitor human motions, and machine learning algorithms can be used to detect various activities.