True North Podcast: Smart Tech, AI, and Machine Learning for Organizational Wellbeing and Efficiency
In this interview (23:50), Chris provides insights from his extensive experience as a Business Development Leader in technical innovation. Working across industries that include Government, Healthcare, Financial, and Pharmaceutical, Chris’s specialty is in using technology to solve problems for Ithena’s clients in the private and public sectors.
Following an in-depth analysis, Chris works with his engineering team to bring modernizing solutions to clients that yield improved performance, increased productivity, and significantly lower operational costs.
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I'm delighted to talk with you today about the work that you do because this is really the intersection of addressing industry quandaries as they relate to the workplace and working conditions, helping people be the most productive that they can so that the organization can do the important work that it does. I know that digital transformation is a key part of that – could you unpack that a little bit for us?
Sure, absolutely Beth. Yeah, and thank you for having me on this podcast. I’m delighted to be here. So basically, at Ithena, we're connecting systems together that are usually isolated. So we literally integrate them to basically share information or even collect information. So some of the examples of this might be, think of a manufacturing company that might have four different production systems within their factory.
Well, we would connect all of those systems for the benefit, of sort of knowledge, on how each manufacturing system is performing or conducting themselves. And what that does is it yields a whole bunch of knowledge on or awareness on logjams, on ways to be more efficient, and basically supply a better performance and at a smaller cost altogether. So whether it's to systems or devices, we do the same thing with a lot of different devices – we’ll connect a streetlight together with having to be on one system, basically for control, so you can dim lights and therefore have the efficiency savings of you know, limiting the electricity use a certain municipality or town or things of that nature.
And we do this all with controls that are basically centralized on a dashboard. So it allows the person running the application to have visibility of all these different systems that used to be isolated in one connected form, and seeing their efficiency or maybe the lack of efficiencies that would, therefore, call for something for that person running the systems to change. So hopefully that gives you sort of a baseline of what digital transformation is and what it does.
It's an excellent big picture, Chris. And I think it really helps us understand what it is and how it connects with the kinds of work that people do in a range of environments. Could you speak to some of the big trends that you're seeing that are driving smart grid and smart technologies today, as I understand they’re called?
Sure, absolutely. I'd say the biggest trend is really trying to conserve energy, energy usage amongst, you know, companies, entities, or even government sectors as well, too. So take here in the Boston area where we're talking to different organizations on their energy output. And when we do an analysis, what we find out, as I said previously about digital transformation, we're finding out that they too have all these isolated mechanisms of using meters, if you will, which will basically take in the numbers of what they're using for electricity, as an example.
So we have to deploy things like sensor technology. Like we're doing this right now with one of the train systems and we will basically measure one train system versus another using sensor technology, collecting the information on elements beyond just their energy use but also maybe the age of the train itself, the weather that given day. They do know the number of passengers that are on these trains. So, we will apply that data to basically collect all this information, if you will, and be able to make more informed decisions on why one particular train system is consuming and utilizing more energy, more electricity than another. But all this is sort of pooled into the same sort of template, if you will, the same sort of manner that I mentioned with digital transformation, it comes to a dashboard and in a very simple way gives reporting on that usage of energy, if you will, by one particular training system versus another.
Wow. So it really gives the organization a full range of information that they can use to make better decisions in support of efficiency.
Exactly, I mean, it literally will send out once it collects all that data and can use other forms of technologies, which we'll get to a little bit later, like artificial intelligence or machine learning. It can set up alerts, Beth, that where it will alert you saying, hey, you're trolley number A seems not to be functioning at a norm. And you can look into that and maybe see that there was something mechanically wrong with Trolley A, or maybe it's something to do with the route to where Trolley A actually drives itself when it's bringing passengers throughout the city.
So all those different forms of information are firstly gathered. And then secondly deployed using artificial intelligence and machine learning for better knowledge, but better recommendations and remedies to improve energy use.
Beautiful. So thinking about some of the questions that organizations are starting to think about as it relates to the health of their employees Chris, I'm curious about the intersection of some of these schools with that wellness focus, helping organizations ensure that their people are healthy and able to effectively do the work that they do. What are you seeing in terms of tools in this part of the field?
That's actually a great question. So right now the biggest fear is, how do we get back to some, some sort of sense of normalcy of working and going back to the office?
I think everyone's afraid of that, and they're not knowing what to do. So Ithena has actually created a new product called ISafe. And it's basically it's still using sensor technology in several areas, but we're essentially replacing sensor technology with thermal scanning software or thermal imaging, which is basically without really interfering with an employee or student, it can take their body temperature, and use that data in the same formation, as I spoke of earlier with the example of the trains and electricity, if you will. So it's basically called Track and Tracing.
And for employees, we can intersect, you know, talking again about digital transformation and bringing systems together, we can intersect our ISafe COVID-19 detection software that is capturing body temperature. And we can connect that to an HR system. And basically keep a record for tracking and tracing.
Because the first thing you want to do is if you find somebody that might have a fever and therefore might be at risk for COVID is to give that person care and this will allow him to see dashboard manners in reporting manner within the HR system is sort of behind the scenes, our ISafe application would provide that capability and allow an HR director or whoever it may be to track and trace on those who look to be at risk of having COVID-19. And again, it allows an organization that might have 10,000 employees, how would they do with the numbers for the course of a week, in the course of a month, and where are the at-risk locations as well.
Through sensor technology, we can earmark moisture, you know, humidity areas that usually are factors that are usually conducive, with a likely scenario of spreading COVID-19. The cafeteria would be an obvious example of shooting too close together or something. So those are some of the things right now. We're wanting to help with COVID-19. But we're also excited that our capability, it's sort of like opportunity meeting, preparedness, our capability allows for us to sort of go to market with this application and help large businesses, schools or even manufacturers who want to see when they have so many people coming into their buildings.
What a great resource for organizations that are really trying to get a handle on how do they help people be able to get back together and do it in a safe way that supports everyone in the organization.
Exactly. Yeah. In addition to that, we do use, like we layer it, Beth, with self-reporting. Because self-reporting is a lot of things. It really helps give a profile for the healthcare service workers.
You can sort of share that information with them but at the same time, it will help an employee not feel the level of anxiety that one might feel if they were earmarked to have a potential body temperature, you know, of 99 or 100, or something like that.
This whole self-reporting part is a way to communicate through a cell phone with those who are in place or sort of speak, those go into work, and having this risk detection take place day in and day out. And we see that as being something that's very helpful with collecting data on what people are given. Because again, that's really what we're all about is collecting data, using AI, artificial intelligence, using machine learning to make that data more useful, but at the same time, it's a nice interaction between the employee and the employer in regards to the whole COVID-19 risk.
So essentially, I'd be able to look on my phone at a trail of information that shows me over the last week or two what my temperature was and really get a sense of my level of individual health. Is that right, Chris?
Absolutely. In fact, you know, in a company, it's easier, we could literally collect their phone numbers of their cell phones, and if they can walk into the front entrance, and through the thermal scanning cameras, were said to have a fever of 100. We could literally connect with them immediately through their cell phone and say, Look, can you please come down to a particular office that's caring for patients that might be at risk for COVID-19. But that's the sort of communication that initiates the process but continues it in sort of a self-reporting way.
They may want to know what to do next, which this whole chatbot application is geared and set up to answer in that regard.
So it's really a good way to actually make the employee feel as if somebody is watching over for them, or watching over them and that there's a whole regimen to this. That first things first, let's make sure you're, you're healthy don't have COVID-19. But if you do, there's a process we're going to have to follow in this whole application is chatbot application covers that, where you still might that might need to have any quantity because the risk is just too substantial to ignore it if that makes any sense.
Totally. Wow. It sounds like the work that Ithena does really presents a suite of tools that can help an organization, not only in this current environment that we're all amidst, Chris, but a range of other ways. Can you give a few other highlights for some of those tools that helps the organization be more effective and efficient?
Sure, absolutely. I think, again, it comes back to our ability to collect data, which is essentially what the sensor technology is doing. You know, take a smart streetlight as an example. We have a device that we can put on every street light that essentially connects it to one platform, which would be that dashboard, you know, facet I mentioned earlier. Now, what does it do? Well, it collects data of all different types. It collects data of how many cars that go down that street, how many pedestrians walk down that street, even Co2 levels, and things like that. You can have a camera on it. To watch out for crime, you can set it up so that it's a certain noise level takes place. It's probably a car accident or maybe the gun shooting or something like that which can immediately alarm or alert the police department to take the oldest to this. So there's all different things we can do. But what it really is doing, Beth, is collecting data. So why is that important? Well, with the data, you can use artificial intelligence, which is essentially software that makes decisions for you. And I'll speak to that in a second.
The other technology that it uses is machine learning, and that is the more data that states when we assume learning an application or software, the more it learns, no differently than how you text on your cell phone. So if you use a particular name that you know. On my phone, I used to deal with as an investor a company called Primus. It’s spelled P-R-I-M-U-S. Where at first you know, when I would text that I would never get it right. Especially if I use voice recognition on my cell phone, it would never come up correctly. But over time from correcting it so much, it captures that information and eventually acclimates itself to when I'm saying Primus or when I'm trying to spell it. And that's really like a form, a simple form of machine learning. So, you know, back to the streetlight, right?
We're collecting all this data of when how many cars goes down or travels down a particular street, how many pedestrians and we've got, you can use informed decisions where artificial intelligence will say, you know what, after one 1 am in the morning, literally, practically no one in the course of a month walks down the street. So let's turn the lights off. And that can be an enormous savings for a city or municipality.
With that kind of true, they call it big data, big data at can that justifies these decisions and, you know, technology allows you to that you can set things up with a radar you know, with the sensor technology would kick the light on if someone were walking down the street at one in the morning or driving by as well, too. But that's sort of an informed decision that managers or directors would make knowing the knowledge, the knowledge that comes very neatly to them about the pedestrians, or the cars that have traveled down that street, let's say after midnight, for 90 days, and when they look at that data, they can, therefore, make adjustments on energy usage, in this case, electricity and have significant savings on the whole net net.
Wonderful, wow. And that's, that's impressive. When we think about the big goals that organizations have, having these datasets can be so valuable, right? What are some of the general categories that you hear organizations are trying to use that data to support? We’ve spoken about one, energy efficiency. What are some others that you hear organizations really trying to fill the gap so they can reach for that big goal?
Right, right. I think it depends on who you're speaking to, if they say municipality or government of some kind. They're also looking for things like smart parking, with some sensor technologies, smart utility meters, which the sensor technology and in the same connotation as we just had, it's collecting data. Whereas then measure data of one meter, let's say it's one electricity meter versus another, and send out an alert if the numbers are not in accordance to how they had been for, let's say, 20 previous months, you know, so the spikes really high or it's very low, that could be a meter that's broken.
Or there could be something in that electricity unit that's off-kilter, that's not correct.
Governments are really looking at this, are knowledgeable about this now -- they want to know, I want to be told when I'm at risk for something bad to happen. The same thing could happen with water levels, you know, with a water meter of some kind. And today with sensor technology and digital transformation, you're able to sort of bring together devices, and platforms and applications to provide this sort of information. You know, in similar fashion with manufacturers, they're looking at things like asset tracking, they want to know the location, the lifespan, so to of speak, of a product from the second that comes off of the assembly line, which when it’s being utilized by the end-user by the customer, right?
And those efficiencies or lack of efficiencies are revealed through using sensor technology and tagging it. It's called asset tracking. You're basically watching it or knowing where it is at times, but you also collect data on its lifespan, on its roadmap. And you can make decisions in a similar fashion, as they say on so-called efficiencies or remedies or seeing where there's areas of concern.
Wow, to have access to all this data, Chris, is super exciting. I mean, you've talked about the financial benefits organizations, the resource stewardship, you’ve spoken about how we touched on safety, and then lifecycle, making sure that when something needs to repair, that you plan for that and you're anticipating that that need is coming. So there's so many benefits to the work that you do and the resources that you provide the organization. Chris, can you tell me a little bit about the dashboard that you help people build to be able to keep track of all of these many data points?
Yeah, sure. That's a great question because say you're doing something for a city, they may have, they may have literally 100 applications that are doing different things. But if you just want to see in the dashboard, how your streetlights are functioning, you can literally just click on the dashboard where it says smart streetlights.
And it would give you a grid of the city and basically earmark the efficiencies of each set of lights. Because you know, the traffic lights are not coordinated necessarily throughout the whole city. And you know, this whole use of technology and this whole thought process that you and I've been discussing that has that same premise where you can literally take the technology usage, its use case, apply to traffic lights as an example. And rather than having a whole bunch of isolated decision making on green lights and how long the green light is, or yellow lights, red lights, you can coordinate an effort based on information that you know, on volumes, volumes of pedestrians, volumes of cars at what particular times.
So collecting all that is really useful information and it can help you know, improve the whole traffic flow of the city, but more importantly, it can be a quick decision or a quick monitoring scenario for that manager on the dashboard, just going to that section. And then he seemed to jump over to the smart streetlights with the same information made available. Utility meters, same information available, you know, smart parking, you could literally see what spaces are open, based on the sensor technology you use that earmarks what spaces are open or not.
And this could go on and on and then you could do the same thing with buildings, with heating systems and C systems, electricity units or grids within a large building that might be owned by a city. So there's so many things that can be set up in a dashboard. That sort of the demand that these managers have given to our industry, our marketing, they're like, Look, we want one thing that we can jump around to get information immediately so we know we're on top of it, and nothing is slipping by.
Wow, very exciting stuff to be on the leading edge of all of these technologies, Chris. Thank you so much for telling us about it and helping us kind of look under the hood, and see how it all works and how it can apply to our organizations. So Chris, if people wanted to reach out to you, what's the best way for them to contact you?
Oh, sure. Yeah, this has been my pleasure, Beth. Thank you for having me on your podcast. It's been fun talking about what we do at Ithena so the best way to contact me would be through email or phone. My phone number is 508-596-8873. And I welcome a call at any point. Or if it's better to email me my email is ChrisB@ithena.ai.
Ai stands for artificial intelligence, we use that as opposed to dot com. So it’s ChrisB@ithena.ai. And I'd be happy to answer any questions that they may have on any of the topics that we discussed during the podcast.
Thank you so much, Chris! Very much appreciate it.
My pleasure. Thank you, Beth.