Three Questions For… Jack Dangermond, Founder & President of Esri
By Esri
Dangermond shares five ways that location intelligence are benefitting smart cities.
1: What trends are you seeing in your area of work, and why does it matter to governments?
There are five big trends in how forward-thinking smart cities are applying location intelligence to decision-making.
i. Data from IOT
First, the data from IoT networks gives governments the ability to understand the behavior of people as well as the condition of the environments they live in, providing deeper insight into what is going on in communities and where. Cities can use sensors to mine data in everything from infrastructure to vehicles, and enable deeply informed decision-making.
ii. Real-time insights
Second, real-time GIS has quickly taken hold in a wide range of enterprise systems, brought on by the rise of sensors, nimble drone platforms, and ubiquitous handheld devices. Location intelligence is so much more effective if you can see what is happening everywhere the instant it is occurring. For instance, if a city’s utility departments can identify where power outages are happening the instant they do, they can be more responsive.
iii. 3D maps
Third, 3D capabilities are increasingly allowing city planners and developers to see how future structures will work in the physical world. In cities especially, the vertical space is all-too-often underrepresented on conventional maps. Today, 3D maps can show us how the world really is, as well as proposing and forecasting what will be—almost like a “digital twin”. As an example, builders and planners can use this tool to visualise the floors of a proposed high-rise in 3D, and how they each need to be zoned differently for residential, retail, or commercial applications.
iv. Artificial intelligence
Fourth, Artificial Intelligence is a crucial tool in a smart city’s digital transformation, helping governments to understand behavior and act accordingly. Geospatial analysts work in concert with AI to automate information processing and expand their understanding. In the case of New York City’s Legionnaires’ Disease outbreak in the summer of 2015, AI helped humans make location-based predictions of where the bacteria were likely spreading from.
v. Shared content for collaboration
And finally, large organisations have begun to adopt distributed GIS. Interactions in distributed GIS revolve around shared items - web maps, web scenes, layers, and apps, to name a few. Shared content becomes discoverable for each participant in the collaboration, and workers from local to a worldwide scale can gain unprecedented access to data and applications from anywhere, and on any device.
2: What is one key challenge that your organisation is facing, and how are you helping to overcome it?
One key challenge our organisation and others are facing is developing a trained workforce. As in the past, we desperately need to add more modern web GIS practitioners, spatial data scientists, app programmers, and software engineers for all of us to collectively achieve our shared geospatial vision.
3: What are you most inspired by right now, and why?
The most inspiring thing that we have seen over the past few years is governments using location intelligence to engage their communities in building smarter cities. They are achieving this through data-driven grass-roots solutions and apps.
Population increases, climate change, income inequality, housing shortages - governments are now using solutions like ArcGIS Hub to communicate key challenges to citizens. Hubs bring together a city’s data, visualisation, analytics, and collaboration technology, and support data-driven work on policy initiatives and the measurement and prediction of outcomes.
Citizens can join Hubs in their communities and contribute data, provide feedback, attend events, follow initiatives they care about, and create and share analyses. It places GIS tools and practices into the hands of the people who are directly affected by these global and local issues.
It’s inspiring to see location intelligence used in this way, because it is a clear example of GIS technology being used to make the world a better place from the bottom-up.