The Intersection of AI & IoT for a Healthier Smart Home

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There are countless connected home products available, but are they actually "smart"?

Sean Lorenz, CEO & Founder of Senter, believes mainstream consumer adoption of connected home products will only happen when we begin aggregating data from different manufacturers, then apply deep learning and artificial intelligence to turn that data into something useful. Following his role as Director of IoT Market Strategy for Xively by LogMeIn and co-founder of TechStars robotics startup Neurala, in 2015 Sean founded Senter, where they are creating an IoT cognitive assistant for longer and healthier aging.

At the RE•WORK Connected Home Summit in Boston, Sean will discuss what protocol, aggregation, time series-based predictive analytics, and user experience changes are necessary to make smart home features like “monitor my health” or “lower my energy bill” a reality. I caught up with Sean ahead of the summit next month to hear more.

Tell us about Senter and why you founded the company.
Senter is a smart health hub for helping aging people live longer, healthier, safer lives at home. We aggregate data from lots of smart home, wearable, and connected health products then use neuroscience-based algorithms to learn how elderly people live and move in their daily lives. I originally started Senter because both of my children were born extremely premature (16 weeks and 11 weeks early, respectively). My daughter went from being hooked up to machines for 135 days to having zero insight into how she was breathing or handling her gastro tube feedings. We were in and out of hospitals due to this lack of insight. The same scenario applies globally to our rapidly aging population. Senter's goal is to make advanced technology fade into the background while making us more aware of our health states at the same time.

What are the main challenges of creating the fully smart home currently?
The biggest challenge at this point is getting access to reliable data. Understandably, each "smart" home product wants to be the central user experience, so navigating strategic data partnerships across different product manufacturers in the home can be difficult. If done thoughtfully, however, sharing data can be beneficial to all parties involved.

How can we successfully integrate machine learning and AI into the home?
AI is at the core of what Senter does. We act as an intelligence layer across data streaming in from motion, humidity, location, accelerometer, blood pressure, among other sensors. Machine learning and AI has focused primarily on natural language and image processing for the past several decades, and this makes sense given that web and smartphone applications have been the primary sources of data input/output. This is changing quickly now that time series-based smart home sensor data is becoming the largest source of data needing analysis. The next frontier in AI will be discovering better insights across IoT data streams.

What advancements excite you most in this field?
Part of my PhD research involved looking at a part of the brain known as the posterior parietal cortex. This area is known for integrating data across sensory and motor areas in order to make higher-level associations. I see the smart home in a similar way. There are a number of sensing and actuating devices in a home that need to be aggregated and made sense of in order to learn better decision making options. So, I believe the most exciting smart home advancements will come from the field of sensor fusion intelligence.

What areas of the home will be impacted the most by AI & IoT?
I am obviously biased, but I believe home health will be impacted most by the intersection of AI & IoT. Better value-based care requires us looking outside the hospital and primary care walls for understanding our activity, sleeping, feeding, and cognitive habits. It is the intersection and sense-making of data coming from smart home, wearable and health devices that will keep us living longer, healthier lives.

Sean Lorenz will be speaking at the RE•WORK Connected Home Summit in Boston, taking place alongside the Deep Learning Summit, on 12-13 May 2016. Other speakers include Blade Kotelly, VP of Design at Jibo; David Isbitski, Chief Evangelist of Alexa and Echo and Amazon; Rahul Bhattacharyya, Research Scientist at MIT; and Andreas Gal, Founder & CEO of Silk Labs. 

Until Friday 15 April you can get 25% off all tickets the Connected Home Summit using the discount code IOTDAY16. Tickets are limited, to register please visit the event website here.

Big Data Connected Home Machine Learning Deep Learning Algorithms Deep Learning Home Automation AI Healthcare MedTech Connected Home Summit


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