By Benjamin Harris — Predictive analytics driven by smart sensors and the intelligent capture of lifestyle data, can greatly improve the quality of care for this population. Learning more about even simple patterns that emerge over the daily life of an elderly patient can lead to greater insights from everything from routine health concerns to predicting when a life threatening event is imminent.

“We can predict health from data from different sources,” said Kuldip Pabla, senior vice president of engineering for Raleigh, North Carolina-based K4Connect, a developer of smart tech tools for senior living spaces.

Pabla describes capturing data from three areas: smart home, smart wellness and smart community. If all of the lights are off and no motion sensors are activated in a senior’s house during a time they historically have been active, a predictive system might guess the resident has fallen or gotten hurt.

Read more from K4Connect Senior Vice President of Engineering, Kuldip Pabla, on Healthcare IT News!