Spatio-temporal modelling

Often models used by organisations do not explain the underlying data well enough to make suitable decisions for specific points-events in time or space. Many problematic issues with geo-spatial data arise at early processing and data management stages when different sources of information with varying geographies, coordinate systems or time frequencies are merged and collated for further analysis. The complexity of workflows and multivariate, dynamic nature of data make it very difficult for many organisations to select and implement appropriate modelling and machine learning methods for predictive analytics purposes. This is even more challenging when such approaches are applied to any form of Big Data (e.g. large, fast, complex, unstructured, noisy or irregular) or where distributed computing is necessary.

 

Novel data mining approaches for spatio-temporal data

Our areas of expertise include large scale geo-spatial, temporal (time-series) and spatio-temporal analysis. We use cutting-edge geospatial science and data mining techniques as well as novel ways of dynamic, user-reactive and 3D geo-spatial visualisations typically used by gaming and film-making industries. Combining advanced machine learning methods with high-dimensional visualisations is suitable for representing and modelling complex, large datasets with geographical, spatial and/or time-series referencing. In specific cases and depending on project requirements, we use artificial intelligence approaches (e.g. CNNs or RNNs) to train sophisticated models for predictions of particular events, behaviours and patterns in (near) real-time and selected geographic areas of interest.

Spatio-temporal modelling

 

Applications of geo-spatial, temporal and spatio-temporal modelling

Geo-spatial and temporal applications

A large diversity of potential data that can be represented using geo-spatial information, mapping or longitudinal and temporal frequencies, make it applicable to almost unlimited business cases or research questions. From smart sensors, social networks, web analytics and typical finance forecasting to longitudinal election, epidemiological, public health and socio-demographic studies, the range of possible applications is limitless. As Mind Project has traditionally been involved with clients from banking, finance, health and public/local governance industries, we strongly encourage organisations coming from these sectors to contact us to discuss your specific projects, however we are also open to other clients interested in our bespoke geo-spatial and spatio-temporal modelling solutions.

 

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