IoT and Data Analytics Post
How Data Analytics can use the Internet Of Things in Healthcare Post
The “Internet of Things” or IoT is a buzzword being used frequently today but not everyone understands what it means to how it’s being used. Wikipedia basically says that it’s a collection of hardware, software or sensors connected to a network. I prefer a different explanation: The Internet of Things is the process of giving objects that, until recently, never had internet access, nor sensors that we could directly access the internet. I prefer to say a “process” since the IoT isn’t a finished object. Companies are creating new items and sensors that can give real-time access to decision making data and some of those products are just now reaching widespread adoption.
One such example of those new products is an Electronic bacteria sensor created by Purdue University1. and the Philips E-Alert2 which helps hospitals keep track of malfunctioning equipment. Fortunately, the remote patients monitoring use of the IoT is taking off faster, with several companies3 offering the ability to track patient health outside of the hospital or doctor’s office.The “Internet of Things” or IoT is a buzzword being used frequently today but not everyone understands what it means to how it’s being used. Wikipedia basically says that it’s a collection of hardware, software or sensors connected to a network. I prefer a different explanation: The Internet of Things is the process of giving objects that, until recently, never had internet access, nor sensors that we could directly access the internet. I prefer to say a “process” since the IoT isn’t a finished object. Companies are creating new items and sensors that can give real-time access to decision making data and some of those products are just now reaching widespread adoption.
This growth of accessible health data is very pertinent to my current data analytics class. Currently, the class is learning about k-means clustering, and decision trees, which can both place a role in helping healthcare professionals proved better care for patients. K-means cluster could help build types of patient profiles to give patients more customized treatment and reduce the length of hospital stays. Decision trees with this knowledge could assist physicians in diagnosis, by giving statistical probabilities of an illness given habits, or determine what services are most used by patients. Examples Biotronik3is already using this technology in their home monitoring tools to reduce the number of doctors visits a patient needs, and Nihon Koden’s4 Aware system can prioritize health alarms based on the type of patient.
Sources:
- https://www.sciencedaily.com/releases/2016/06/160614100347.htm
- http://www.businessinsider.com/how-hospitals-are-using-iot-2016-10
3 & 4. https://mhealthintelligence.com/news/top-10-remote-patient-monitoring-solutions-for-hospitals