HERE have introduced the new Reality Lens, allowing quick mapping to create spatial databases, measure areas of interest and model in 3D your future planned assets. This can also be valuable for the consumer and the automotive industry, due to being able to input various information in the map as seen on the picture above. Moreover, it can help identify assets within 2cm point accuracy, making any model very accurate.
For the automotive industry, this technology is vital for smart cars to be able to take full advantage of the best possible navigation. This technology in return, creates a positive customer experience and contributes to the local economy, through allowing consumers to identify points of interest in the area and even possibly use the car navigation system as a device to advertise places to visit. I could see the usefulness of this technology to be able to identify the customer ratings of a restaurant instantaneously through e-glasses through the help of open data sources.
A major theme from the conference was the way that GIS technology is moving towards the 'sharing capability', hearing it from Esri UK's Managing Director Stuart Bonthrone. Seeing the depth of the applications that HERE are creating, with one of the company focuses being on assessment and insurance, the information gathered from Reality Lens can help businesses with their real estate valuation, property tax assessment and flood insurance estimation. But to not forget the usefulness of Reality Lens in areas such as engineering and planning, public safety, being able to capture data in the morning and be able to work on it by the afternoon.
My personal favourite from the presentation by HERE on 3D Capturing was the availability to collect and analyse advertising board placement and using the line of sight information to not only best position advertising boards, but know the locations to charge a premium for. Keep an eye on 3D modelling next time you encounter a problem and possibly think about how this technology could help you collect data and then analyse it. Happy learning!