The power of goldeni is in the data-driven analytics that turns the collected in-home and local area data into actionable insights. These insights enable property services teams to better manage and maintain the properties, therefore delivering healthy homes for tenants and environmentally friendly properties for landlords.
goldeni does this with Microsoft’s Power BI, which is the engine behind our unique front-end dashboard. Power BI enables data visualisation along with ESRI ArcGIS geospatial mapping of properties and graphically display the insights that are built out of the machine learning algorithms and models.
The entire goldeni ‘stack’ consists of The Things Industry (TTI), Microsoft Azure, data warehouse, and tools such as Power BI for visuals, python and R Notebooks for ML model, advanced analytics and visualisation. These facilitate our market-leading data analytics and machine learning models and artificial intelligence (AI) development.
Using Azure Functions and Service Bus, goldeni automatically notifies property services teams of any alerts (non-emergency) that could be happening at a specific property.
For example, data from sensors measuring external and internal air quality, temperature, humidity, and energy consumption is transformed, mapped and fed in through goldeni’s unique machine learning algorithms and models to convert the data into actionable insights. These actionable insights inform property services teams as well as landlords and tenants of the state of their property. Insights into the internal air quality, potential build up of mould or for leak detection. Insights along with clear actions and recommendations empower the property services teams to undertake maintenance to reduce the adverse impact on tenant health and wellbeing.
Layering data is also important – we are looking at how seasons, external conditions, external air quality and location affect the homes; how they operate, the energy efficiency, and the internal air quality. Does the external environment negatively impact the internal environment and the living conditions for residents, and by how much? How does seasonal weather and building fabric affect a tenant’s energy bill? There are many aspects to consider, and we ensure data and insights from one set of sensors is layered with data from others to provide a complete picture of how the property is performing.
Our vision is to have several unique machine learning models to support every client’s needs and ensure seamless interoperability of many IoT sensors, gateways and cloud platforms. We will continue to build our Digital Twin technology as we connect different silos of data from properties, tenants, environmental and geographical conditions.
goldeni’s ambition is to upscale customised sensor deployment across multiple boroughs and regions. To better support tenants across the UK and through dashboards and apps, we can help to influence the tenant to change how they operate and interact with their homes to reduce environmental impact and also reduce their energy bills.
For more information on how goldeni can help you, please get in touch with the team by email: firstname.lastname@example.org or call us on +44 20 3318 722