Morgan Sindall Launches Innovative Machine Learning Software Platform
Morgan Sindall Launches Innovative Machine Learning Software Platform

Construction and regeneration group Morgan Sindall Group plc will launch this week an innovative technology platform which uses machine learning software to provide social housing landlords and tenants with real-time, actionable insights to help them ensure their properties are healthy, legally compliant and more energy-efficient.

Using discreet interconnected sensors positioned throughout a home, the platform collects data on the internal environmental conditions in a property, including temperature, air pressure, light levels, humidity and carbon dioxide. goldeni also monitors heating systems, detects for water leaks and monitors electricity and gas consumption.

The goldeni platform has been developed by data scientists working for Morgan Sindall Property Services, the property maintenance division of the Morgan Sindall Group. Morgan Sindall Property Services currently looks after 200,000 homes on behalf of social landlords across the UK.

“Morgan Sindall is committed to developing and implementing innovations for our customers. The launch of goldeni, our first technological innovation for the sector, represents an important milestone not just for Morgan Sindall but also for Social Housing as a whole. By giving clues to potential issues within homes even before they occur, it can help those living in social housing have healthier, safer, more energy efficient homes, as well as saving Social Housing providers costs,” said John Morgan, Chief Executive of the Morgan Sindall Group.

“While we’re initially focusing on social housing, its ability to provide an instant overview of a building’s health in real time means that goldeni would just be as useful for commercial and private residential property owners as well, and that’s something we’ll be looking to roll out in the future.”

Morgan Sindall Property Services is the first property maintenance provider to develop an inhouse platform that can consolidate and interpret information from a number of commercially available ‘Internet of Things’ sensors in real-time. It 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 requiring additional insulation.

According to Inside Housing, in 2019 / 20 Housing Associations in England spent a combined £5.51bn 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 £550m per year. This figure is likely to be even higher for providers who also follow goldeni’s recommendations about how to make properties more energy efficient.

The platform also has a crucial role to play in the path to net zero. goldeni provides 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.

The sensors are sensitively designed and easy to install, and the platform can be accessed from any device. What’s more, landlords and tenants immediately benefit after installation, as the machine learning software platform makes preventative recommendations and identifies potential issues from day one.

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BDC 317 : Jun 2024