Private, personal, elder care and assistance Improving elder wellness at home using artificial intelligence to sense, respond, inform, understand, plan, predict, and act.

Our Story

Age-At-Home provides personal, local, artificial intelligence to assist and interact with both the elderly and their community of family, friends, and care-givers.

Utilizing open-source software from Home Assistant and the LINUX Foundation's Open Horizon, the system provides distributed and decentralized edge AI to sense and respond to end-user activities and interactions.

While many approaches to assisting the elderly require devices to be worn or smartphone apps and sending data to the Cloud, Age-At-Home is a pervasive, but not invasive, aggregation of your Internet-of-Things (IOT) and "smart" devices and their capabilities. Analyzing data, producing information, and sensing and responding in the home; disclosing only your selected information to friends, family, or care-takers.

Our objective is to improve the lives of people, starting with the elderly, by sensing and responding in the home and leveraging communities of shared interest to improve AI's ability to understand, learn, plan, and interact.

How does it work?

Age-At-Home interfaces with Internet-of-Things (IoT) devices, including cameras, microphones, speakers and utilizes artificial intelligence to:

• processs sensor data into information (e.g. person detected kitchen)
• calculate information statistics for normal to help determine abnormal conditions
• interact for reminders, notifications, with rule-based automations
• collect feedback enabling automated learning and improved predictions

Activities of Daily Living (ADL)

The portfolio of AI's detect the presence of people -- and animals, vehicles, faces, posture -- and analyze that data to produce actionable information relevant for the key performance indicators: Mobility Cooking Sleeping Bathing Dressing Toileting

Proactive engagements via voice

Reminders for activities, e.g. eating, bathing, ... Question & Answer to request confirmation or selection of option Learning from new examples based on feedback

Our Principles

We believe AI accuracy depends on data intimacy; and intimacy requires privacy. We aspire to effect ethical AI with beneficial outcomes. We make to help people live more satisfying and fulfilling lives.

References

• Understanding AI
• Building a Better 'bot
• Cognitive IoT and Eldercare at O'Reilly AI Conference in New York, NY USA
• AgeAtHome - Deep Learning at the Edge at nVidia GPU Technology Conference in San Jose, CA USA (YouTube)
• IBM Outthink Aging
• IBM and Avamere to Bring Cognitive Eldercare Research to Senior Living and Skilled Nursing Facilities
• IBM and Italian Healthcare Provider Sole Cooperativa to Study How Internet of Things Can Improve Senior Housing Facilities
• IBM Human Centric Solutions Center is making a difference for Italian seniors aging at home in Bolzano

Video

Analysis

Entity detection information across time and location; for example analysis of person detected in the kitchen:

Entities detected in the kitchen, including heatmap, cloud, and relationships

Open Source

Motion Ã👁 - Platform for capture and analysis of IoT sensor data (aka situational awareness)
Home Assistant - home automation software enabling access to 1,000+ IoT devices from many vendors, including those from Apple and Amazon
Open Horizon - LINUX Foundation project for distribution and management of AI services

Prototypes

If you've read all the way to here and you still want more information, you can find me at the following places; or click on the little blue circle in the lower right of your web browser to talk to me directly: LinkedIn GitHub Twitter