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☁️ Cutting Carbon in Buildings

My Climate Journey

Photo by Mykyta Martynenko / Unsplash

Table of Contents

Host: Jason Jacobs
Guest: Lee Hoffman | Co-Founder & COO | Heat Watch
Category: ☁️ Carbon Reduction

Podcast’s Essential Bites:

[4:04] “Heat Watch is […] a software and hardware platform for buildings that helps run buildings and building systems better. So the platform really consists of a computer and wireless network and sensors that go into a building. And then we use that data to control the building systems more efficiently, better for tenants, better for owners, to cut carbon output.”

[6:51] “Last year in the average building we controlled heat, we were able to reduce the energy usage by 21%, while making tenants more comfortable. So the end result is property owners and co-ops and condos can basically save 21% on their heating costs, which could be $50,000-100,000 a year in certain buildings. And they'll pay a small fraction of that to us to do it. So it's an incredible investment. And the ROI is usually less than a year. So one of the best investments you can make in real estate. But at the same time, it actually makes the people in the building more comfortable and as a byproduct you are cutting carbon output by 20 plus percent. […] The average building will take about 8 to 10 cars worth of carbon output off the road, simply by controlling pieces of the building slightly better. We started in heat, now we're doing it with water, we're going to be rolling out cooling. There are a whole series of applications, almost every aspect of buildings are not being run efficiently today. And what Heat Watch does is it uses technology to run buildings better.”

[8:09] “Everybody likes to talk about electric cars. And I'm a huge advocate of electric cars, […] but when you look at the carbon output threshold from different industries, almost 30% […] of all of the carbon output in this country is coming from buildings. So literally, just by running buildings more efficiently and better, you can have a gigantic impact on carbon output, and you can fundamentally change cities. And I think that's really kind of one of the things we've clued into simply by operating buildings better, we can make cities substantially more affordable, cleaner and more sustainable. So it's kind of a win for everybody all at once.”

[12:09] “There are probably a handful of key systems that are using a ton of energy. Heating, especially in cold areas is a gigantic one. […] A big building could be spending a half a million or a million dollars a year on heating gas, or heating oil. Cooling can be a gigantic one, particularly in office settings. […] The one that we're really bullish about particularly is water. It's one that's been overlooked for a long time. But just to put this in scope, like a [single] running toilet in New York City can cost […] thousands of dollars […] a year. And there's a tremendous amount of energy that goes into cleaning that water and particularly in areas where you have droughts […]. It's not even just a financial issue. It's an environmental issue. […] And then the last is obviously electric that goes to […] common systems like elevators, fans, pumps.

[14:20] “Most buildings have no sensors. […] There's nothing in the building to tell the system what the temperature is. So most buildings run on what's called an outdoor reset, which is literally a hard coded table […]. And that's how almost every building in the country for heating still runs except for the Heat Watch buildings. So there isn't a standard here. In fact, we wanted to use off the shelf sensors and things we didn't want to build hardware in the beginning, it just didn't work. None of the sensors out there were easy to install and lasted 10 years on a single battery charge, which meant when you're in thousands of buildings, you're replacing batteries and every apartment, it just wasn't tenable. So we had to develop our own custom wireless network that could go through 4-6 floors without a repeater, could be installed in minutes, [and] lasted 10 years. And that allows us to then instead of saying, run the heating system randomly for some number of minutes, we can precisely predict using machine learning what the temperature indoor should be, and literally minute by minute change the ideal setpoint based on our machine learning models, and precisely keeping the building at a temperature that's going to be the most comfortable for tenants, but also minimize fuel usage.”

Rating: ⚡⚡⚡⚡

🎙️ Full Episode: Apple | Spotify (Original Title: "Startup Series: Heat Watch")
🕰️ 43 min | 🗓️ 09/16/2021
✅ Time saved: 41 min

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