Connections: Bringing Our Knowledge of Machine Learning to the Real World

Machine learning affects many of our machine systems, but as we think of real world issues that machines with learning can solve, sometimes we skip over the usefulness of machine learning in the health care of the elderly. This is a huge area of technological importance as we have large surges in our elderly populace. Assisted living technologies are becoming more and more vital as our population skews older but our elderly still look to live independently.

A paper on ‘Abmient-Assisted Living’ tools offers an idea of how systems could be used to help the elderly live independently. This paper offers three specific tools used to assist independent elderly living: smart homes, wearable sensors, and assisting robots. These are all technologies that depend heavily upon machine learning.

Smart homes already possible today can create a living space for the elderly that can monitor their overall health with many different sensors. These various sensors allow a machine learning system to decide if the elderly person is getting sick or needs medical attention.

Wearable sensors are also considerably advanced and can give many vital signals to determine the overall health of an elderly person living on their own. These sensors are often more specified and don’t have all the data that a smart home would take, but they should take different specific data that the home can’t keep, such as movement, location, and constant updates of body functions such as blood pressure, or glucose levels. These can also alert if an elderly person needs to see a doctor or monitor if they are in an abnormal state.

Assisting robotics gives can make the elderly even more independent by doing many of the things that elderly care nurses currently do, such as helping with self-maintenance activities, fetching things, and helping with other daily living tasks. These personal helper robots can allow the elderly to feel more independent because they are not dependent on another human being.

As these functions are all currently possible, it is exciting to see what will happen in ten years. Extrapolating from these current possibilities is uncertain, but I am confident that in 2026 machine learning will allow for a great increase in elderly autonomy. It would be reasonable to say that machine learning will allow for these five things in ten years: automatically scheduling appointments when needed, automatically calling the correct emergency response in case of an emergency, robot assistant help to replacing in home nurses, prescribing diet or health actions to improve overall health, and giving reminders and aid for the elderly to participate in social and personal activities and hobbies.

These machine learning abilities will give the elderly an unprecedented amount of independence. This will remove a dependence on others to give reminders and physical help. Even the most handicapped can be given a chance to participate fully in the world around them because they will have both monitors to check their health and physical assistance to allow them to physically interact with their community.

The amazing strides machine learning has taken in today’s world means a great deal for ten years from now.