Author: Jiyun Lee (Page 1 of 2)

Yesterday, I had lunch with a friend and had an opportunity to share our summer experiences. The typical response I get when I say I am working on “Internet of Things” and “Smart Homes” is “That is so cool! I would never be able to do CS.”

This friend, keen on knowing more details, asked what exactly a Smart Home is. With vague details, I mentioned that it is a house that can learn behaviors of people and automate certain repeated patterns and can communicate with people living in it.

She raised a question, “So would it turn lights off automatically after averaging out the time I go to bed?” I acknowledged that is one possibility. Then, she quickly asked, “What if one day I go to bed at a different time?”

Yes. This is the nature of humans. More prone to pick out faults then appreciating what works. Even if a smart home correctly learns patterns and does things 99% correctly, people will take it for granted. However, they will pick up on 1% that didn’t meet their expectations.

Machine learning is in a sense an “averaging” process. An “average” is bound to have standard deviation, or margin of error. Will people be generous to accept these margins of error?

Let’s say a student’s bed time is on average, 1:16AM. One day he decides to go to bed at 1:15AM. Will he be patient enough to wait for 60 seconds until lights turn off automatically? And he almost always has coffee right after he takes a shower in the morning, so the smart home brews coffee while he is taking a shower after detecting motion and water usage in the bathroom. What if he decides not to drink coffee that day because he has a stomachache? Will he turn a blind eye to the coffee that was automatically brewed, or complain about wasted coffee beans and electricity?

Recalling the papers on Nest thermostat, people were more unhappy about Nest picking up on exceptional cases rather than it learning the completely wrong patterns. If Nest works as it should, people will gradually forget about the need to control temperature manually, forget that Nest is doing all the work for them, and then get mad when Nest does one thing wrong.

So maybe we don’t want automation. No one’s life follows a fixed schedule to the second 24/7, so there will be that 1% that makes people unhappy.  Maybe all we want is just a house that listens to what we want — as opposed to making decisions on its own —  and obediently follows directions.

Although being tracked doesn’t feel comfortable, today is one of those days where I wish I lived in a smart home that tracked my patterns. Currently my roommate and I are living in a big house with 6 rooms (4 of which are empty) and together in a month apparently used 800 kWh of electricity and had to pay $160 together. Given that we did not use our air-conditioner, we were very surprised. Since we could hear the air-conditioner running almost all day long from the other side of the house (our 6 rooms are one half of the house), we were wondering if their air-conditioner was connected to ours. We are looking into whether that is true or not. In the mean time, I thought I would do a little research on how much electricity home appliances use to get a sense of what the most likely culprits that drained energy would be.

Below are what I found online as average usage of kWh in households per year:

• Circulating fan =  4 kwh
• Coffee Maker= 9 kwh
• Frying Pan= 8 kwh
• Microwave Oven= 16 kwh
• Self-Clean Oven= 61kwh
• Toaster= 3 kwh
• Blender= less than 1 kwh
• Refrigerator 14-17 cu. ft.= 170 kwh
• Washing Machine= 9 kwh
• Dryer= 75 kwh
• Lighting 4-5 Room= 50 kwh
• Outdoors, 1 Spotlight, All Night= 45 kwh
• Vacuum Cleaner= 4 kwh
• Hair Dryer= 2 kwh

Now I generally get a sense that ovens, fridges, and dryers use a lot of energy. With power meters available, smart homes would be able to tell me where most of my energy use is coming from. It would be even better if it analyzed my living pattern and told me when I use most electricity.

This is exactly what Kamin Whitehouse envisioned — that smart homes would be beneficial for the environment — and I can do nothing but agree. Right now, my roommate and I know that we used a lot of electricity(although we are both usually out working), but we have no idea what to do in order to fix it.

My roommate installed a home security system called Canary. Once you install an app on your phone, your phone serves as a presence sensor and knows whether you are home or not. It time stamps when you entered and left the house.

When both my roommate and I are not in the house, the device is in “Armed Mode” which allows us to make a siren alarm go off. When one of us is home, it is in “Disarmed Mode.”

It is currently sitting on a table in front of the front door, and I can watch a live feed from my phone. It uses a HD camera for vision and sound. Whenever motion is detected, it records 10 minutes or so of footage(both image and sound) which can be accessed from timeline of my phone. Yes, it is creepy.

Canary device also senses temperature, humidity, and air quality.

My phone is busily buzzing today because I am getting notifications from SmartThings door sensor whenever lab room door is opened and closed, and also from Canary whenever motion is detected in the house.

I find it interesting how there is a huge market for all the camera systems for safe home. About a week ago when I was in Boston, there were so many posters of Nest’s camera in subway stations. What is it that drives people to buy cameras to watch their homes, which is the most intimate and private place of all places? Is privacy an inevitable price you have to pay for security?

Any how, I am being tracked everywhere, from lab room with two Kinects and multisensors along with door sensor, and Canary at home.