GeoAI — A Blend of Geospatial Technology and Artificial Intelligence

Original article can be found here (source): Artificial Intelligence on Medium

GeoAI — A Blend of Geospatial Technology and Artificial Intelligence

Artificial Intelligence (AI) is today a buzzword that is staging the future of innovative transformations in the field of technology. AI is in a way a deciding factor of how the industry will be driven in the recent and distant future. AI is utilized in various sectors through data classifications, intelligent algorithms and smart predictive analysis. One such blend of AI is encountered with geospatial technology as it merges with the solution-based approach and sharp analysis of artificial intelligence, becoming Geospatial AI or Geo AI.

Geo AI is also understood as a form of machine learning based on geographic data. Let us know more about how it works and the challenges it faces in today’s world. We have also thrown light on its role in various sectors.

How Geo AI works?

The best example of Geo AI in our daily life is its use in simple mobile applications. Have you ever noticed how you get the real-time feedback about almost anything and everything around you, such as traffic congestion, the peak hours, places and more? It all happened with AI and geospatial technology, that is, through Geo AI. The data is sorted, analyzed and used for accuracy and precision as there are hundreds and thousands of individuals contributing to the database.

Through proper analysis of the data, Geo AI helps us receive more accurate results, such as, the area in of high traffic congestion, the shortest route to our destination during peak hours and rerouting of the vehicle flow.

What are the challenges when using AI in GIS?

Despite all the successful efforts, there are a few challenges geospatial experts encounter while using AI in GIS. The first of the few obstacles on the path of implementing Geo AI is the varying temporal resolution. For example, predicting and modelling chronic disease patterns having long latency periods is not carried out successfully. In cases like this, various factors come to play, such as long development periods, environmental factors and several physical factors that suggest about the existing datasets not being enough diverse or go back in time to allow easy execution of the forecasts.

The second on the list of challenges is that maximum of the image data remains biased towards the Western states with people speaking English, restricting Artificial Intelligence to some countries because not enough learning datasets are available.

Other focusing areas by geospatial experts include improving the low resolution imagery to boost knowledge awareness for particular areas or historical data purposes. The use of CNNs (Convolutional Neural Networks) is extended to the low resolution satellite imagery and it shows to enhance feature identification as low resolution data improves with a basic input in various spectral bands. This way the limitations of earlier satellite system can be addressed, such as the previous Landsat systems, to be improved and utilized for long-term land use change in a better way.

How Geo AI is used in business development?

When it is about understanding the relationship between technological innovation and business development, there are two different thought process existing out there. There is a group that believes in the fact that technological progress is the key to take a business forward. And on the other end is another group with the belief that business investments are the reason for technological advancements like contemporary Geo AI. To say the truth, it lied somewhere in between these two schools of thought.

To understand it better, we should consider it as a circle, a never-ending one as cutting-edge technology and evolving business sectors are correlated in most ways. Consider a business financing the R&D on a particular field and giving way to new business opportunities.

Geospatial AI in the field of business represents the world of geospatial analysis in different sectors of business, both private and public by using artificial intelligence. Ideally, there are three massive trends bringing out the advent of Geo AI — a huge amount of geospatial data from more brief remote sensing and satellites, the exponential rise of computational power and the innovations like machine learning.

Be it in the field of education, collection of geospatial data or transportation, Geo AI plays an important role in business development.

How Geo AI contributes to health and healthcare industry?

The blend of AI and geospatial technology/GIS is what leads to Geo AI. Geospatial artificial intelligence or Geo AI opens gates of massive opportunities and applications in the sector of health and healthcare, as the location plays a crucial role in both individual and population health. There are various fields in the domain of public health, smart healthy cities and regions, Internet of Things (IoT), precision medicine and more that are getting the benefit from GeoAI. Some of these sectors include epidemiology, environmental health, epigenetics, genetics, infectious diseases, social and behavioral sciences and more.

Geo-tagging of big data collated from leading sources such as satellite imagery, social media streams, IoT sensors in smart cities and personal sensing can be reasonably combined with GeoAI to get answers to the issues in the crucial research on health in a much more comprehensive way.

With GeoAI, we can capture and model our environment, connecting the places where we work, live, travel or spend most of our time to social, environmental and other kinds of location-based exposures to understand their possible roles to influence our health. They can potentially predict disease occurrence, generate new kinds of hypotheses, help plan and track the deployment of health promotion, disease control and prevention programs, etc. in smart healthy cities. Geo AI is not limited to population-level tracking, but there are further chances of integration of GeoAI and location-specific information intelligence into the areas of precision medicine through customized mHealth interventions for individual patients.

To Conclude

Geospatial Artificial Intelligence of GeoAI came to the surface when two different technological innovations, geospatial technology and artificial intelligence combined together for human welfare. Today, GeoAI is used in various fields such as business, health & healthcare and more fields to make life easier for individuals and it is only going to get stronger in the future.