Our Own Devices with Nandagopal Rajan
How is AI making buildings greener?
In this episode of The Indian Express tech podcast – Our Own Devices, host Nandagopal Rajan, COO, The Indian Express Online is joined by Sivakumar Selva Ganapathy, Vice President of OpenBlue India Software Engineering & APAC at Johnson Controls. We are living in the age of artificial intelligence, and we cannot even imagine the ways in which it can be put to use. AI can help make our buildings sustainable and green. With the correct amount of data, buildings can be made sustainable at their very foundation and this is exactly what Sivakumar talks about. To understand the need for sustainable architecture and how it is being worked upon, tune into today's episode of Our Own Devices with Nandagopal Rajan.
00:00 Introduction
0:44 How AI helps in creating sustainable buildings
2:31 Enabling Sustainability at the foundation
5:10 How data specific to India helps in buildings sustainable buildings
9:19 Regular optimization
13:14 Command control hub in buildings
16:30 An awareness and knowledge gap
Edited and mixed by Suresh Pawar
- Duration:
- 22m
- Broadcast on:
- 01 Jul 2024
- Audio Format:
- mp3
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Call clickgranger.com or just stop by. Granger for the ones who get it done. Hello and welcome to another episode of our own devices. This time, we are going to talk about something again quite interesting because it is again something I didn't know about, that AI can help in how you make sustainable buildings. And to talk about that, we have with us Mr. Shivokumar Selva-Gadabati, who is the Vice President of Open Blue India Software Engineering and APAC at Johnson Controls. So, Mr. Shivokumar, welcome to the show. Good evening, Nanda Gopal. It's great to have you here. Thanks for the opportunity. So, see, the concept of sustainable buildings, green buildings have been there for a few years now. And I remember maybe in almost a decade back when the concept started sort of coming in, there are many ways to do it. There is a rating, but at a broad level, how is AI helping you? Yeah, definitely. So, if you really look at across the globe, roughly about 40 percent of the greenhouse gas emissions are from the buildings. So, that's one trend we are seeing. The second thing what's happening is, all of the companies, countries and regions, now they are committing for sustainability goals. Some take 2030, some take 20, 70, so on and so forth. And particularly in the context of India, we do have Sydney mandated BRSR reporting. And all these are enabled by data. So, that's where artificial intelligence comes in. And the way we have to look at is, how do we make the buildings not only operationally efficient, but also intelligent enough? Because we are talking about Gen-Yers and Gen-Zers coming into the building as occupants and their expectations are completely different. So, in addition to making operational efficient, how do we really make sure the indoor air quality is better, the space or optimized? And also looking at how do we really optimize our energy build? And at the same time, make the buildings much more greener. So, that's where the delta driven artificial intelligence and machine learning comes into the future. And at Johnson Controls, we focus on commercial building solutions and sustainability in the way we work across our businesses and functions. We help enable our customer and client and at the end of the day, save our planet. And all these are enabled by data driven decision making and also infusing AI and machine learning. And most recently, also generative AI in some of the use cases where a customer wanted to solve a problem. So, if I understand this correctly, a lot of these sustainability initiatives in the real estate space earlier used to happen at a retrofit level, right? You have a very good building that you think about what all can you add that makes the building greener more sustainable. But now, and is it right to say with AI also in the picture, you have the ability of thinking something from the ground up literally, which is sustainable at every level from the construction to maybe how or where the building is placed in the plot of land. Like, there are many angles to it, right? Yeah, absolutely. All right. And also, the way we look at this in two parts. One, the brownfield buildings where retrofit is a very big opportunity. We sensorize it, we put some collection data to edge devices or building articulation systems and then pass it on to cloud and then use the data to do some prognastics and then really predict before and even to have which is happening, right? So, that's one use case. The second thing is, now, if you really look at the India landscape particularly, the number of green buildings which are greener by design is 5%. There is a lot of trust and encouragement from the government of India to really encourage sustainable green buildings through lead and edge kind of certifications. And it is only going to grow. Yes, you're right, from a greenfield buildings, we can really look at the 3D approach. You design for sustainability and you enable sustainability through the second day, which is digitalization through industrial IoT and edge and analytics, AML or whatnot, and then finally seamlessly deploy at the end customer site. And that building could be any type of building. It could be commercial-related building, it could be now with the increased focus of data centers in India. It could be data center type of building or airports or retail malls or university campuses or even large government buildings. And even hospitality sectors, hotels and hospitals. So, across these type of buildings, we enable to deploy our equipments and our sensors and gateways to really look at how we enable sustainability. One is the brownfield, as you said, there's a huge retrofit opportunity. And that second one is greenfield buildings where white design and nowadays, you know, I mean, any company operating their board shall constitute a board member representing ESG. And most of the large conglomerates have chief sustainability officers. So, some of the customers which we interact with and some of our forums we represent in, so there is an increased attention and focus on sustainability by design rather than an afterthought. So, there's the first element of the 3D that you mentioned. In that, for instance, does AI help you? Like, you know, there is no, you mentioned about the data available, right? But you also have data available for the location, for instance, you know, it tells you about everything from rainfall to sunlight available and all of that. So, earlier, for instance, a lot of the concepts, I remember, you know, it was sort of imported from, you know, an Australia or wherever the concept had gained ground before us. And maybe all of that doesn't work in the Indian context, right? So, but here you have the ability to sort of fine-tune it exactly to the data available for that specific place. Is that right? Yes. Yeah. So, let's take a building, right, an operating experience of a building. So, what we focus is how do we make the occupant of a building more comfortable, more safer and more secure, right? Once an occupant enters the building, the clear consumption of energy is through the HVAC equipment, which is at the basement of the building, etc. Right? Now, the first use case, what we're really trying to drive is how do we predict the energy performance so that at a large company level, when you have a fleet of buildings, let's say a big commercial real estate owner, so can really link it to their KPIs, right? It could be, hey, this would be my energy utility index. These are my ESG codes. So, that is where based upon the data, the past pattern and also the environmental factors to weather data and the benchmarked, pure building data, we can really predict what the energy performance is. So, that at the operational level, the technician level, they can take actions based upon the insights because AI is only as good as once it is acted upon. Yes, delivering insights is one part of it, but you close to loop to command and control by taking action on it. At the same time, when you roll up to the boardroom at a CXO level, what we are enabling through AI is a single pane of glass. So, then across the portfolio, it's dissipated within the country or even across the geography, how we enable the analytics part of it, to really look at where my problems are, in one area, hey, my HVAC could be a problem, and we all know these are capital intensive assets, where we infuse AI and MLAs, really looking at vibration analysis. For example, if you take our huge yacht chiller or any branded chiller, right? So, these are capital intensive assets. So, can we collect, centralize it? Can we collect the data and deploy machine learning models to predict that this could fail, at least a couple of weeks ago, so that that could be a huge cost saving for a COO or a general manager of the operations perspective. That could be a huge cost saving, which is the bottom line perspective. Now, let's come inside the building. Now, you have gentsias coming in, different person has coming into the building. Now, using AI techniques, we can really deploy and design our spaces accordingly, so that based upon the need of the occupant, we can give recommendations saying that, hey, if you are in a collaborative environment, you can take the meeting spot on, or if you want to really ideate with India's startup ecosystem and a lot of innovation happening, more open spaces are required, right? So, through data-driven approach, we can suggest and recommend what type of activities need, what type of buildings inside the system. So, that's on the a couple of use cases which we can think of. Now, I would also look at during COVID and post-COVID scenario. Indo-react quality has becoming more and more important, and as a community within India, as citizens of India, we are more concerned about how do we keep ourselves a more hygienic environment. So, that is where we deploy Indo-react quality sensors, collect the data, and then mash it up with other data like energy and lighting, etc. And then provide optimal performance by keeping the occupant healthier. At the same time, you optimize your energy bills. All these are driven by data and definitely using AI and ML algorithms. So, of course, there is a predictive angle, but there's also an angle where based on actual data, you get the insight to keep on continuously optimizing, right? Within inside a building, for instance, when do you switch on the AC, which doors open, which doors don't? Why do you have the lighting natural, or why do you have artificial lighting coming in? So, how effective is that part of this? Yeah. So, what's happening is, as you rightly said, we do have with a large number of years of domain expertise, we do have FTD, fault detection and diagnostic algorithms. So, what we do is, when we collect the data, we also look at the quality of the data coming from all these sensors, and also we look at the equipment performance as well. So, that is where we are looking at, how can we really look at these equipments, the health of the equipments, and really tying out with prescriptive methods? Let's say one is the predictive and primitive part of it, but there will always be certain areas where certain events occur. So, at that point in then, using AI and ML, how do we retrieve the right kind of knowledge articles quickly and remotely, right? So, imagine we are looking at a space where we are in the internet world and internet of things world. It's not economical and logistical possible to deploy a technician to any of the buildings across the world. So, that's why we have removed diagnostics monitoring solution, and also looking at command and control. So, we are only looking at the smartness of the building right now. As we speak, as the buildings you are, we are looking at autonomous buildings, and that autonomous team comes in to some of the augmentations, where we look at, hey, can we create an AI agent which can really autonomously look at some of the space requirement, some of the energy requirements, and also the way you build your building information model using a twin, how do we segment the lighting? Let's say in a hybrid work model, one set of space we not have a lighting at all. So, how can we make it more autonomous so that it is self-sustaining? So, that is where some of the digitalization aspect, AI, ML aspects comes in, and then we are in a unity and diversity kind of a country, and taking globally, we have technicians speaking multiple languages. So, that's where generative AI comes in, where we provide conversational inputs to the technicians, remotely avoiding the travel costs, etc. And at the same time, the software aspect, many of the people, how do we motivate these technicians from a monotonous task of, hey, acknowledging an alarm and taking action on it? They also get motivated by using these digital technologies to say, hey, this is the type of the chiller, and this is the issue, how do I solve it quickly? So, through those conversational aspects, we've retrieved the right kind of knowledge articles, which is predominantly manual, etc., and then suggest them, how do we really fix the problem? So, this way, we shrink the cycle time, where the end customers, the maintenance technicians, and the operators are happy, and at the same time, we are reducing the cost, which gives a bottom line advantage. But imagine the scenario of a hotel, you also look at new revenue stream. So, there are no studies we have done recently, and also, there are a couple of external reports where they suggest the citizens, the travelers, are willing to pay a premium. Maybe a 5%, 10% extra, tools, and eco-friendly, greener buildings or greener states. So, there, we can help the hotels to generate additional revenue streams, really looking at, hey, if this is the kind of room temperature, this is the quality indoor air quality we're talking about, we not only provide the visibility, but we also provide command and control and kind of self-service kind of offerings as well. Now, if you are working, let's say, on a big hotel or a hospital complex, how does it work to you? So, a building like this, or a factory like this, actually needs a command and control hub, right? So, is that within the building, or is it managed like centrally by you people? How does it work? And the other aspect is that, no, I remember the conversations a few years back, because no company in a way had an end-to-end solution, right? You needed to have some things coming from somebody else, and there were some standardization issues, because your hub doesn't, maybe, it can't talk to the other IoT devices, because it's based on some other standard. So, are we in a situation now where a company like yours can go in and give an end-to-end solution? Absolutely. Very good question and neither of the hour to save our planet. So, at Johnson Controls, as mentioned earlier, sustainability is our key team. So, we do have a sustainability infrastructure team, where first they go, take any type of building, first do an audit, they assess where they are, and then they compare it with our own benchmarks, with a huge amount of fleet of building data we have, and then say, hey, what are all the areas of focus, depending upon your KPS? First, number one, how do you make your buildings healthier? Number two, it could be, how do you optimize your energy cost? Number three, how do we really make sure it is sustaining, right? Sustainable report, but it has to be continuous and sustainable product. Now, once we assess this, that's where our open blue platform comes in, our data and analytics platform, which is blue represents our legacy brand, Johnson Controls Blue, and the open is where open to the open ecosystem. It is brand agnostic, it is protocol agnostic. We have the ability to interface or connect in a secure way through APIs to not only ingest the data and collect the data, but also push the data out. So, a couple of examples, particularly in Asia, back in Singapore, one of the large customers, we are able to, because some of the large customers, they already have a command control center, let's say a knock or a sock. From a single pair of glass, we provide the energy efficiency and equipment efficiency data as one of their pain. So, we provide that data to them. So, that's one model we are looking at. The second thing is, we also have our own open blue platform has command and control capabilities, whereby, depending upon what we are operating, either it could be an equipment or it could be space performance or it could be net zero buildings and net zero advisor or sustainable manager, we not only recommend, but we also have control, which interacts with our own metastas kind of a building automation systems or any other brand building automation system and closest to loop. So, that is the key differentiation, what we need to look at when we are talking about connected building to smart building to autonomous building. Connected buildings are good, but smart buildings are even better so that you can have the command and control functionality. And when we move as the industry move towards autonomous, we will be able to ensure that with a still human in the loop, how do we minimize and make it more autonomous, more data driven. So, before we wind up, one last thing I want to ask you is that, so even a situation where every company has to designate somebody as a sustainability officer, everybody has a ESG goal, but even then, is there still awareness deficit in the market that people still don't know that this, some of these things are very easily doable, especially if you are setting up a new greenfield building, right? And certainly, we really don't need to be in a situation where we still have buildings without even one element of smartness to it. So, is there a gap in the market still? And how do you think this gap can be solved? Yeah. So, first, let me take the Indian context. Yes, you are absolutely right. There is a gap between what commitment as a country we have signed up for, I mean, 27 year, 26 year work more. But if we need to get there, we need to start looking at the grassroots level. So, yes, number one, there is a awareness or a knowledge gap whereby industry, the government and the academia shall come together, catch them young early from a school and college days, and then early in the life cycle, so create those awareness. That's number one. And number two, also like what currently the government is doing, really looking at, for example, from a technology perspective, there is an India AI mission. They have signed up, they have committed roughly about 10,000 floors of Indian rupees over the next five years. Not only AI from India, but AI for India, which is going to have a societal impact. One such a streams could be, how do we mark carve out some amount of investment towards the greener, sustainable planet, and a greener building, which is sustainable so that it helps India as a country to meet those goals. That's the second piece of it. One is the awareness, the second one is real kind of support, and third one is on an ongoing basis, how do we ensure this is not just a, oh, milestone achieved, I'm done, right? It's there has to be an ongoing governance model. That is where we have regulatory authorities through the boards, the constituent of the board with ESD representatives and sustainability officers. There has to be a consortium, and there are forms like CIIs and ISHWAIs and through NASCOM from a technology perspective. We do collaborate and ensure how do we do this on a sustainable basis, sustainability on a sustainable basis, so that we as a country, we adopt. But when you look at the global context, I think the awareness and the adoption, the North America and EU, they're slightly ahead of us, and the commitments are also bit aggressive, and the technology deployments are faster. But my only hope is India being the AI capital of the globe, I think we should take the whole position too, and with the kind of richness in data centers, both cloud service providers and small and medium search centers coming in, and the kind of talent we get from the universities and schools in terms of AI, and not only that, also coming out with sustainability and greener academia courses, I think we are shaped up well to really take the whole position and lead our country forward. On this positive note, Mr. Ashir Kumar, thanks for being on the show. It's very insightful to dig in something I'm sure a lot of our listeners were not aware of, and we'll apply their mind when they are looking at setting up something new. That's right. Thank you, Nana Gopal. Nice to be with you. So you are listening to our own devices. We'll be back again next week with another guest, and a lot more insight. You were listening to our own devices with Nand Gopal Rajan by the Indian Express. This week's episode was edited and mixed by Suresh Pawar and produced by Meen Harakananda. If you like the show, then do share it on your social media handles, and do not forget to tag us. We go by Express Audio. You can find us on X and Instagram, and if you have any feedback, do write to us at podcasts@inexpress.com. That's podcast with an S, and do not forget to tune in next Monday at 4 p.m. for another episode of our own devices. How to Have Fun, Anytime, Anywhere, Step 1. Go to Chumbacassino.com. Chumbacassino.com. Got it. Step 2. Collect your welcome bonus. Come to papa welcome bonus. Step 3. Play hundreds of casino-style games for free. That's a lot of games, all for free. Step 4. Unleash your excitement. Chumbacassino has been delivering thrills for over a decade, so claim your free welcome bonus now, and live the Chumbalife. Visit chumbacassino.com. If you're a facilities manager at a warehouse, and your HVAC system goes down, it can turn up the heat. Literally. 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