PROPTECH-X ‘Proptech & Property News’: Climate & Energy Proptech PropEco partners with Stafford Railway Building Society | IBM Advances Geospatial AI to Address Climate Challenges

Andrew Stanton’s daily PROPTECH-X ‘Proptech & Property News’ in association with Estate Agent Networking and News Now.

Stafford Railway Building Society partners with climate and energy Proptech PropEco

UK-based lender The Stafford Railway Building Society (SRBS) has partnered with leading climate-tech company PropEco, enhancing its ability to assess energy performance and anticipate the potential impacts of climate change across its mortgage portfolio.

Through the partnership, PropEco will provide a range of data-driven tools and services that help SRBS assess and manage current and future climate risks. The two organisations will also work together to explore opportunities to support members of SRBS, providing insights in areas such as energy efficiency and climate resilience.

Chris Hardman, Co-founder and CEO of PropEco, said: ‘We are delighted to be working with SRBS, which has consistently demonstrated that it is both forward-thinking and fully engaged when it comes to modelling and developing its understanding of the impacts of climate change. We look forward to working with the team to identify further opportunities and deliver additional value for its Members.’

Chris Reid, Finance Director at SRBS, said: ‘Over the past six months we have been working closely with PropEco to support our aim for a more comprehensive set of climate and energy performance data across a broad range of metrics. This is an area which will continue to evolve and we very pleased to be working with PropEco, in particular the flexibility, responsiveness and data coverage that PropEco offers really sets its solution apart.

‘We look forward to building a successful partnership over the coming years.’ For more information on the partnership, or to find out more about the products and services that PropEco provides.’

For those unfamiliar with the brand, PropEco provides a data-driven platform that helps organisations and their customers assess and improve the energy efficiency, climate resilience and liveability of residential properties. The platform integrates hundreds of sources of enhanced data, advanced analytics, proprietary models and cutting-edge technologies to power multiple products and services including portfolio assessment tools, an interactive dashboard for property professionals, property reports and an API.

The platform helps organisations streamline their reporting, gain new insights, decarbonise & de-risk their residential property exposure, enhance customer engagement and generate new business. For more information go to www.propeco.io, connect on LinkedIn or at info@propeco.io.

Stafford Railway Building Society is an independent mutual building society founded in 1877 to provide and support its members to save and own their own homes. Over 140 years later they are staying true to their word by offering straightforward, good value savings and mortgage products backed by a plain-speaking, friendly service, to help our members reach their savings and home ownership goals. Mutuality is at the heart of their business and it continues to be here for the service of their members and not shareholders.

Stafford Railway Building Society is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority. Find out more at www.srbs.co.uk.




IBM Advances Geospatial AI to Address Climate Challenges

PRESS RELEASE LONDON, UK.IBM (NYSE: IBM) today announced new efforts that apply its geospatial AI technologies, including IBM’s geospatial foundation model developed in collaboration with NASA, to climate efforts including climate resiliency in the United Kingdom (UK); analysis of urban heat islands in the United Arab Emirates (UAE); and reforestation across Kenya. 

IBM continues to advance its AI model strategy in part through the creation, training, fine-tuning and open-sourcing of foundation models – models that can be used for different tasks and apply information from one situation to another – designed for domains beyond natural language, including geospatial applications.  

These models, which are trained on geospatial information such as satellite images, present a unique opportunity to address climate change because unlike traditional AI models tailored for specialised tasks, geospatial foundation models – encompassing satellite and weather data – create knowledge representations from petabytes and exabytes of climate-relevant data that can facilitate accelerated and streamlined discovery of environmental insights and solutions.

“Climate change is a real and pressing issue that we must find new ways to address as quickly and efficiently as possible, including through today’s most advanced AI technologies,” said Alessandro Curioni, IBM Fellow and Vice President, Accelerated Discovery at IBM.

“AI foundation models utilising geospatial data can be a game-changer because they allow us to better understand, prepare and address the many climate-related events effecting the health of our planet in a manner and speed never before seen.”

Elevating climate resiliency across the United Kingdom

IBM and STFC Hartree Centre, through the Hartree National Centre for Digital Innovation, are advancing a new area of research with Dark Matter Labs and Lucidminds, as part of their TreesAI project. The research project will apply IBM geospatial AI technologies to their Green Urban Scenarios (GUS) model to map urban locations where trees can be planted to help alleviate the risk of surface water flooding. The effort will eventually inform an end-to-end digital planning platform for urban planners, project developers and green urban investors across the UK.

Kate Royse, Director at STFC’s Hartree Centre, said: “There has never been a more important time to prepare for the challenges posed by climate change, both from an industrial and societal perspective.”

Djeevan Schiferli, Climate Intelligence Business Strategist, Royal HaskoningDHV said: “Operational and strategic planners in every company require a clear understanding of how weather and climate-related incidents affect their business operations. By harnessing AI and geospatial data, we will super charge our climate risk assessments on a global scale.”

Chloe Treger, TreesAI UK Lead, said: “Over 300,000 properties are at risk of surface-water flooding. Without action, this figure is set to almost double by 2055 due to climate change and urbanisation.”

Analysing urban heat islands in the UAE By the end of this century, many cities will likely experience disruptive and excessive heat waves if GHG emissions continue at high levels. To develop sustainable and equitable plans to keep cities habitable, the rising heat levels must be accurately mapped and addressed.

IBM and the Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) are pioneering an attempt to apply foundation models to the mapping of urban heat islands – areas with significantly higher temperatures compared to surrounding locations. To date, the model has informed efforts that have succeeded in a reduction of heat island effects in the region by more than 3oC (5.4 F)[1]. Going forward, the model is expected to continue to provide unique insights that inform the development of urban design strategies designed to help reduce urban heat stress in changing climates.

Professor Tim Baldwin, MBZUAI Acting Provost, said: “Our collaboration with IBM marks a groundbreaking effort to utilise foundational AI models in analysing and identifying solutions to urban heat islands for Abu Dhabi and parts of the UAE, a region which is particularly affected by climate change. This research underscores the vital role of AI in tackling global issues, emphasising the urgency of continued exploration and innovation.”

Advancing reforestation and water sustainability in Kenya In December 2022, President of Kenya H.E. D.R William Ruto unveiled the National Tree Growing and Restoration Campaign designed to plant 15 billion trees across Kenya by 2032, including in areas of critically affected water towers – forested landscapes that retain water and source many rivers throughout Kenya. While water towers account for about three quarters of the nation’s water resources, deforestation is contributing to increasing water scarcity in these regions.

IBM and the Kenyan government’s office of the Special Envoy for Climate Change Ali Mohamed have signed a Memorandum of Understanding (MoU) to support the National Tree Growing and Restoration Campaign through a new “adopt-a-water-tower” initiative.

The President’s Spokesperson, Mr. Hussein Mohamed, MBS, said: “We recognise that technology plays a pivotal role in unlocking our full potential, optimising resource utilisation, and seizing opportunities. It serves as a means to ensure that we harness our resources most effectively to drive our grassroots-driven economic transformation agenda.”

Extending NASA collaboration to apply generative AI to weather Beyond their initial commitment to build and deploy a geospatial foundation model, IBM and NASA have also announced work on a new, separate AI foundation model for weather and climate. By applying AI technology from IBM, the model aims to improve the accuracy, speed and affordability of weather forecasting and other climate applica


Andrew Stanton’s PROPTECH-X ‘Proptech & Property News’ in association with Estate Agent Networking & News Now publications. #proptech #property #realestate #digitaltransformation #startups

Andrew Stanton is the founder and CEO of Proptech-PR, a consultancy for Founders of Proptechs looking to grow and exit, using his influence from decades of industry experience. Separately he is a consultant to some of the biggest names in global real estate, advising on sales and acquisitions, market positioning, and operations. He is also the founder and editor of Proptech-X Proptech & Property News, where his insights, connections and detailed analysis and commentary on proptech and real estate are second to none.

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