The number of Internet of Things (IoT) connected devices is growing at a record pace. As recently as 2015, there were just 15.4 billion IoT devices – yet by 2025 this figure is expected to reach 75.4 billion.
Add to that more than three billion smartphone users around the world, and it's no surprise we hear so much about 'big data' – the volume, velocity and variety of data being generated is vast. The race is now on to store all this data and use it – data has become a commercial commodity.
The emergence of technology that enables insights to be gained from data sets has opened up a much wider range of applications to benefit not just business but also the population at large – think smart cities, for example.
At GeoSpock, we've taken this one step further by focusing on spatial big data – data with a geographical element – as we believe this gives the crucial ability to tie 'big data' back to real people and improve real lives.
One example of this is our work with Oxfordshire County Council, where the service optimisation opportunities buried within the data offered scope for reducing commuting time and expense for care workers and cutting patient waiting times, as well as reducing costs for the council.
With 243 care worker commuting journeys and 15,000 patient visits each year, the council wanted to discover whether its staff were working from the offices nearest their homes – and whether its offices were in the right place to serve the majority of patient referrals.
Our location visualisation and analysis revealed that more than a third of care workers were working out of the 'wrong' office – one that was not the nearest to their home. And there was scope for reorganising patient referrals to more closely align them with the council office locations.
The addition of a 'spatial' element adds an extra layer of context to all kinds of data. In the case of health data, for example, it can help track disease spread. When it comes to smart cities, it can enable the streamlining of public transport.
The possible use cases are as varied as the data. But although every bit of data has the potential to be of value, you need to be able to store and access it in an efficient way – otherwise it is worthless.