How has FortyGuard been doing since the last time you sat with ADSME Hub?
We’re doing very well. We’re scaling and growing the business into different markets. We recently joined global accelerator Techstars out of Miami to introduce our climate tech solutions to the US market, work with partners to help us enhance our models, and add more experience by training different applications. We’re focused on artificial intelligence (AI), machine learning, data processing techniques, and other things, always in a hyper vertical way. We’re building FortyEngine, our own AI model which correlates only to outdoor temperature data.
What is the purpose of this AI model?
Temperature can be personalised, so we’re trying to develop solutions and applications catering to different industries. We’re not just building FortyEngine for urban planners, real estate developers, government entities, and engineering consultants; we also want to personalise the experience for large enterprises in energy, insurance, banking, health, logistics, food and food security, tourism…
But more importantly, we want to incentivise existing applications. In the geospatial market, for example a property listings app, we can provide much more navigational tools around temperature-based routes, risk zone identification, etc.
Our vision is ambitious, but it has to be to match the need as temperatures increase.
Indeed, the need for FortyGuard’s solutions seems to be more evident every year. Does this translate into more awareness of your work?
Our solution is very novel, and a lot of education is still required. Many folks still think that we’re a weather company. We’re not. We measure temperature where people interact with it, from the ground up to a building rooftop.
In addition, heat is pretty intimidating. We know it’s hot outside, so we have more indoor activities, larger malls, cooling corridors… but no one is targeting the actual problem, although half of the solution is literally understanding what and where the problem is. If you don’t understand, deploying the right solution becomes more difficult.
So, we’re missionaries. To bring that understanding to decision-makers and to professionals in different sectors, we’re building not only a very technical tool but also a non-technical platform. In the US, for example, we’re going to create an urban heat index, mapping all cities across the country so that users and the media can better understand urban heat and its consequences.
What are the ways in which a cooling technology like yours can help make a city smarter today?
The sustainability and human aspect of smart cities is very important, part of the fabric of anything that you do within the city. And cities, by default, tend to heat up. The urban heat island effect occurs as we have more concrete, more asphalt, more buildings, more human industrial activities, and so on.
As we transition to smarter cities, it’s important to consider solutions like FortyGuard because temperature impacts people’s health, comfort, activities, spending, and all the other things people do around the city. In fact, introducing cooling solutions like ours before those cities are built would be a lot more efficient and cost-effective.
[However], the climate tech space is relatively new, and the startups in that space really need a lot of funding and projects to prove the viability of their solutions. Because impact doesn’t usually come with financial returns, you need to measure that impact by improvement in other aspects – environment, governance, social, etc. There’s a reason why we’re part of Ma’an, the Abu Dhabi social authority; they want to see that technology reflected in the social well-being of the citizens of Abu Dhabi.
Have you been working on this type of project in the UAE in particular?
Everyone in the UAE wants to cool down the UAE – we know that it’s hot. And, in the UAE, almost 60% of our energy goes into cooling buildings. We have been working with a partner who’s building a smart city platform, to enhance their decision-making process, access to information, and models, particularly for energy consumption. Our technology correlates that cooling demand with outdoor temperatures, using predictive models, design, and other activities to optimise [utilisation] and make it more efficient.
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