{"id":100485,"date":"2021-10-18T11:06:29","date_gmt":"2021-10-18T10:06:29","guid":{"rendered":"https:\/\/www.pbctoday.co.uk\/news\/?p=100485"},"modified":"2022-07-01T15:56:25","modified_gmt":"2022-07-01T14:56:25","slug":"machine-learning-social-housing","status":"publish","type":"post","link":"https:\/\/www.pbctoday.co.uk\/news\/digital-construction-news\/construction-technology-news\/machine-learning-social-housing\/100485\/","title":{"rendered":"Morgan Sindall launches machine learning platform for social housing"},"content":{"rendered":"

Morgan Sindall<\/a> is set to launch a new machine learning software platform to provide social housing landlords and tenants with real-time, actionable insights<\/h2>\n

The machine learning<\/a> platform will provide the social housing sector with insights to help them ensure their properties are healthy, legally compliant and more energy-efficient.<\/p>\n

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.<\/p>\n

goldeni also monitors heating systems, detects for water leaks and monitors electricity and gas consumption.<\/p>\n

The goldeni platform has been developed by data scientists working for Morgan Sindall Property Services<\/a>.<\/p>\n

Morgan Sindall Property Services currently looks after 200,000 homes on behalf of social landlords across the UK.<\/p>\n

Morgan Sindall Property Services is the first property maintenance provider to develop an inhouse machine learning platform that can consolidate and interpret information from a number of commercially available \u2018Internet of Things<\/a>\u2019 sensors in real-time.<\/p>\n

It provides social housing landlords and tenants with clear, practical recommendations.<\/p>\n

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 \u00a3550m per year. This figure is likely to be even higher for providers who also follow goldeni\u2019s recommendations about how to make properties more energy efficient.<\/p>\n

The machine learning platform 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.<\/p>\n

\"machine<\/p>\n

\u2018Healthier, safer, more energy efficient homes\u2019<\/h3>\n

John Morgan, chief executive of the Morgan Sindall Group, said: \u201cMorgan Sindall is committed to developing and implementing innovations for our customers.<\/p>\n

\u201cThe 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.<\/p>\n

\u201cBy 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<\/a> costs.<\/p>\n

\u201cWhile we\u2019re initially focusing on social housing, its ability to provide an instant overview of a building\u2019s health in real time means that goldeni would just be as useful for commercial and private residential property owners as well, and that\u2019s something we\u2019ll be looking to roll out in the future.\u201d<\/p>\n

Phil Copperwheat, information systems director of Morgan Sindall Property Services, commented: \u201cThis is an important moment for Morgan Sindall, as it\u2019s the first time we\u2019ve launched a bespoke, comprehensive software platform, developed entirely in-house.<\/p>\n

\u201cBy using machine learning, we\u2019ve ensured the platform constantly updates and improves itself, so the more customers use goldeni the more useful and insightful it will be.<\/p>\n

\u201cWe\u2019ve worked hard to make the interface as simple and intuitive as possible, so that customers can start to benefit from it straight away.\u201d<\/p>\n

The sensors are easy to install and the platform can be accessed from any device.<\/p>\n

\n<\/div>","protected":false},"excerpt":{"rendered":"

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