Smart Emergency Alert and Monitoring System
Link to presentation file (https://docs.google.com/presentation/d/1NitohiGjYeXeJdz5qjj-PC42TEjij9u2CllShMYydcg/edit#slide=id.p)
Link to github (https://github.com/archang/SEAMS)
SEAMS is a machine-learning driven wearable application for primarily senior citizens who live alone. It runs on Intel Edison with Sparkfun Muscle Sensors, accelerometers, and other sensors with the aim of alerting senior citizens' remote family and other loved ones as soon as an accident is recorded on the wearable.
Currently, SEAMS has support for accidents of the following kind:
identifying when a person falls/trips undergoes a tonic clonic seizure (total body seizure) epilepsy.
More and more senior citizens are moving into homes alone, with the proportion of senior citizens doing in a certain age cohort increasing with age. There are currently many proposed ways to increase the safety of senior citizens living alone, including having a family member or loved one checking in periodically, improving general health and awareness, and safe-proofing the home.
Nonetheless, these solutions do not take into account the worry that constantly burdens these seniors' loved ones. Senior citizens have a right to choose to live independently if they so desire; simultaneously, their loved ones have a right to keep non-invasive tabs on their well-being.
We are working hard to ensure that SEAMS will cater to this necessary need, while also taking ordinarily auxillary matters, such as comfort and style, into serious consideration.
Intel Edison Sparknotes 9DOF module Sparknotes Muscle Sensor v3 Parse back-end Docker container scikit-learn (logistic regression)
Contributors (github handles)
@archang, @naokiyokoyama, @jennycheung1217, @vkaran101