Approximately 1.2 million people are living with HIV, with many of them unaware of their infection. Pre-exposure prophylaxis (PrEP) is available to minimize transmission among those at high risk for infection, including men who have sex with men, people who inject drugs, and female sex workers. Despite its availability, there is low usage of PrEP. To address this problem, various digital tools have been examined in HIV research. Among those, conversational agents are still underused and their capacity warrants examination to reach at-risk populations. In this paper, we discuss the potential of conversational agents in increasing uptake of PrEP by addressing barriers experienced among those at high risk for infection.

The increasing popularity of mHealth presents an opportunity for collecting rich datasets using mobile phone applications (apps). Our health-monitoring mobile application uses motion detection to track an individuals physical activity and location. The data collected are used to improve health outcomes, such as reducing the risk of chronic diseases and promoting healthier lifestyles through analyzing physical activity patterns. Using smartphone motion detection sensors and GPS receivers, we implemented an energy-efficient tracking algorithm that captures user locations whenever they are in motion. To ensure security and efficiency in data collection and storage, encryption algorithms are used with serverless and scalable cloud storage design. The database schema is designed around Mobile Advertising ID (MAID) as a unique identifier for each device, allowing for accurate tracking and high data quality. Our application uses Googles Activity Recognition Application Programming Interface (API) on Android OS or geofencing and motion sensors on iOS to track most smartphones available. In addition, our app leverages blockchain and traditional payments to streamline the compensations and has an intuitive user interface to encourage participation in research. The mobile tracking app was tested for 20 days on an iPhone 14 Pro Max, finding that it accurately captured location during movement and promptly resumed tracking after inactivity periods, while consuming a low percentage of battery life while running in the background.