Develop an innovative iPhone app designed to provide comprehensive monitoring and support for elderly individuals using Machine Learning and data analysis.

The MB Verizon Innovation Lab was a small group of multidisciplinary individuals tasked with rapidly developing prototypes outside of the typical Verizon product development process. Due to the team’s small size, my responsibilities spanned across UX, Design, and iOS development. I collaborated with the Product Manager, a Copy Writer, and an additional developer to bring these projects to fruition.

My Role

  • UX Design
  • Interaction Design
  • iOS Development

Customer

Client: Verizon
Employer: Verizon  McGarryBowen Innovation Lab

The Challenge

Develop a mobile application to address the safety and tracking needs of seniors and alleviate caregiver concerns. Existing solutions lack user-friendliness and fail to cater to seniors’ unique requirements. This app should seamlessly integrate tracking, communication, and safety features while prioritizing user-centric design for both the senior and the caregiver

The Process

  1. Research: Understand user needs and preferences through interviews and surveys.
  2. Conceptualize: Prioritize features based on research findings.
  3. Prototype: Create and test low to high-fidelity prototypes.
  4. Design: Develop an accessible and visually appealing interface.
  5. Develop: Build the app with security and privacy in mind.
  6. Test and Iterate: Continuously test and refine the app based on user feedback.
  7. Accessibility: Ensure usability for seniors with varying abilities.
  8. Deployment: Launch on the App Store and provide ongoing support.
  9. Marketing: Promote the app to the target audience.
  10. Monitoring: Use analytics to monitor usage and performance.
  11. Feedback Loop: Maintain user feedback channels for improvements

The Solution

Health Monitoring: The app tracks vital health metrics such as heart rate, blood pressure, and sleep patterns through compatible wearable devices or iPhone sensors.

Activity Tracking: It uses ML to monitor daily activities, ensuring that the elderly are staying active and maintaining a healthy lifestyle.

Fall Detection: The app employs ML to detect falls and sends immediate alerts to caregivers or emergency services.

Medication Reminders: Caregivers can set medication schedules, and the app sends reminders to ensure medication compliance.

Location Tracking: GPS-based tracking helps keep tabs on the elderly’s whereabouts, providing peace of mind to caregivers.

Data Insights: ML algorithms analyze collected data to detect anomalies or health trends, offering valuable insights to caregivers and healthcare providers.

Emergency Alerts: In case of emergencies, the app can automatically notify designated contacts or emergency services with the elderly person’s location

The Results