Morgan Sindall Launches Machine Learning Software for Maintenance Insights

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• Morgan Sindall Launches Machine Learning Software for Maintenance Insights

20 October 2021

Morgan Sindall Property Services is to use a machine learning platform to provide social housing landlords and tenants with real-time insights to help them ensure their properties are healthy, legally compliant and more energy efficient.

Sensors positioned throughout a home collect data on internal environmental conditions in a property, including temperature, air pressure, light levels, humidity, and carbon dioxide.

It also monitors heating systems, detects water leaks, and monitors electricity and gas consumption.

Using goldeni’s IoT enabled solutions, Morgan Sindall Property Services is the first property maintenance provider to develop an in-house platform that can consolidate and interpret information from a number of commercially available IoT sensors in real-time.

According to Inside Housing, in 2019 / 20 Housing Associations in England spent a combined £5.51 billion on repairs and maintenance, with many Housing Associations experiencing double-digit increases in their repair and maintenance costs year-on-year.

By helping landlords and tenants identify potential maintenance issues before they occur and remediate leaks before they escalate, it is estimated goldeni could help social housing landlords save over £550 million per year.

Practical Recommendations for Landlords

The system provides social housing landlords and tenants with clear, practical recommendations. For example, goldeni monitors ventilation and will recommend opening more windows to ensure homes are less susceptible to mould, can identify water leaks in real-time, and spots when a boiler needs to be serviced so that preventative action can be taken before a problem escalates.

By tracking which homes are using central heating too often or too little, goldeni can also help users identify properties that are in fuel poverty or require additional insulation.

The platform can also provide practical recommendations in real-time for how to make properties more energy efficient, from using heating more effectively throughout the day, to suggestions on the best time to run energy-hungry appliances or improve insulation.

Phil Copperwheat, Information Systems Director of Morgan Sindall Property Services said: “This is an important moment for Morgan Sindall, as it’s the first time we’ve launched a bespoke, comprehensive software platform, developed entirely in-house. By using machine learning, we’ve ensured the platform constantly updates and improves itself, so the more customers use goldeni the more useful and insightful it will be. We’ve worked hard to make the interface as simple and intuitive as possible, so that customers can start to benefit from it straight away.”

Alan Hayward, Managing Director of Morgan Sindall Property Services, said: “For Morgan Sindall Property Services our focus is ensuring our data insight and innovations provide positive outcomes for customers and communities, improving their living environment and quality of life. goldeni will allow us to take a more proactive and preventative approach to reducing repair demand by flagging potential issues in real-time and helping us spot potential indicators of vulnerability such as fuel poverty.”

Picture: an aerial photograph of some houses 

Article written by Ella Tansley | Published 20 October 2021

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