This week, we focused on and discussed how we should collect the fall data with different strategies. Also, the requirements for the mobile application features are set with details. Searching proper APIs and tools for the application features will be continued, and implementation for sending a message should be set up next week. The current project progress is on schedule, and we will bring the initial environment up for each component next week.
Team Status Update for 02/15/2020
- Discussed about our solutions for each area:
- Design of the device:
- Pin to your belt or body to fix the location of the device, which keeps the fall detection data consistent
- Fall detection:
- Listed types of normal activities (ordinary behavior) for fall and non-fall categories (unusual fall) for testing
- ML algorithm selection design decision
- Mobile App:
- Decided to change from iOS to Android application
- Design of the device:
- Picked up core hardware, determined approximate specs for the remainder
- We have a new team member (Jacob) joined our team. He will help work on the machine learning portion of the fall detection system.
Nick’s Status Update for 02/15/2020
Accomplishments this week:
- New plan for mobile application from iOS app to Android app since some of us have Windows laptops, which prevents us download Xcode (development tool for iOS app)
- Setup a new initial environment for the Android application
Progress for schedule:
- On schedule
Deliverables I hope to accomplish next week:
- Finish setting up a new environment for the application
- Start adding features for sending a message to the first responders
Introduction and Project Summary
For many elderly people, walking safely is especially important for the elders because fall-related injuries are common and can lead to severe health problems. However, there are concerns that they may be left alone in a dangerous situation or get lost without any assistance near them. To resolve such problems, we came up with a smart attachable device connected with a mobile application that detects a fall and sends alerts to the first responders. The main feature of our smart cane is sending an alert to the user’s first responders when there is an unusual fall detection on the device.