FALL APP TECHNOLOGY
ARTIFICIAL INTELLIGENCE & CAREGIVING WEBINAR
Within the past several years, artificial intelligence (AI) based consumer products and services have been launched to make life easier and to increase productivity. Examples include the Amazon Echo’s natural language understanding, Google’s email spam filters, Uber’s fare calculations, IBM’s Watson X-ray interpretation, and UPS’s traffic avoidance routing system.
To help caregiver-based organizations understand artificial intelligence and where it can be applied to enable smarter and more efficient processes, Mom's Safety Net provides a 30 minute seminar, at no cost, upon request. For further information, please contact: info@momssafetynet.com
To help caregiver-based organizations understand artificial intelligence and where it can be applied to enable smarter and more efficient processes, Mom's Safety Net provides a 30 minute seminar, at no cost, upon request. For further information, please contact: info@momssafetynet.com
ARTIFICIAL INTELLIGENCE
AI is based on deep learning. Data, for example, of seniors walking and falling is passed through a web of math, inspired by how brain cells work, known as artificial neural networks. As it processes training data, connections between network parts are adjusted, building an ability to interpret future data. When the solutions are implemented, they adapt to new conditions .
Deep learning creates generalizations on the data automatically during the training process and learns the frontiers between decision boundaries - even if there are 100's of variables involved in the input data set! During decision making the prediction algorithm uses the info and can interpolate new situations without being explicitly taught every possibility. This differs from rule-based solutions where one needs to clearly provide exact values or a range of values for decision criteria - aka domain expert knowledge. if 100 scenarios were possible and then there are be 100 rules. With more scenarios, more rules are made. There comes a point, when nobody can measure how well the rules work or how many new rules and exceptions there are. For real-time events, the systems are like dinosaurs. False positives and negatives increase and. caregivers no longer respond to alerts.
Deep learning creates generalizations on the data automatically during the training process and learns the frontiers between decision boundaries - even if there are 100's of variables involved in the input data set! During decision making the prediction algorithm uses the info and can interpolate new situations without being explicitly taught every possibility. This differs from rule-based solutions where one needs to clearly provide exact values or a range of values for decision criteria - aka domain expert knowledge. if 100 scenarios were possible and then there are be 100 rules. With more scenarios, more rules are made. There comes a point, when nobody can measure how well the rules work or how many new rules and exceptions there are. For real-time events, the systems are like dinosaurs. False positives and negatives increase and. caregivers no longer respond to alerts.
WHY AI IS WINNING
Very simply - accuracy, convenience. Deep learning systems learn - just like a human. Their accuracy continually improves. AI also removes the manual task of classifying and tweaking rules each time there's an environmental change.. Fixing rules manually over time becomes harder - like adding to a house of cards. Deep learning systems are easy to set-up; There is no requirement, within the camera’s field of view, to mask out areas or designate areas of interest for monitoring or be concerned a pet will trigger an alarm.
