GIS has been using artificial intelligence for some time now. However, obstacles still exist in the integration of artificial intelligence with GIS . Read on to learn about the exciting and evolving field of geospatial artificial intelligence.
Artificial intelligence (AI) is all the rage these days, with the several big names in the industry investing heavily in research and development in the field. At its core, AI is the idea of a machine completing tasks in a way that mimics how humans would complete them. When applied to GIS artificial intelligence uses several techniques such as machine learning, statistical analysis, natural language processing, and spatial analysis to make GIS more intelligent and more adaptive.
This article discusses the benefits of incorporating artificial intelligence in GIS and the obstacles that still exist in the integration of artificial intelligence with GIS.
Role of artificial intelligence in GIS
The convergence of AI and GIs has been increasing over the past decade. GIS being a mapping technique requires precision and this is possible only through using accurate data. That’s where artificial intelligence can help. AI is a type of technology that mimics the human brain and offers self-learning capabilities. This allows AI to process large sets of data and find patterns that humans might miss and thereby ensure high levels of accuracy. It also greatly improves efficiency by decreasing the time needed to collect, analyze, and create maps.
Artificial intelligence can improve the selection in spatial patterns and also assess the predictive capability of spatial modelling techniques. This makes it highly useful in the field of landscape ecology where determining the pattern of landscape is important for classification.
The transportation industry also benefits tremendously through the integration of artificial intelligence techniques and GIS. It can help the road network professionals process emergency situations like accidents or bad weather and re-route in the best possible way.
Another useful scenario is in the field of geo marketing. GIS with AI allows the decision makers to re-route the delivery trucks in case of accidents or other emergencies. It helps to manage the supply chain efficiency and minimize the delivery time. Geospatial artificial intelligence also finds application in the health sector by allowing authorities to analyze the population demographics and limit the spread of diseases.
Challenges in integrating AI and GIS
The scope of converging AI and GIS is impressive. However, we have been facing several challenges in integrating the two technologies.
GIS requires complex infrastructure and storage resources. For AI and GIS to function correctly huge investment is required and this acts as a hindrance to small companies. Apart from this, the integration also has to overcome data structure challenges since GIS requires a huge volume of diverse data. We need to support the system with reliable data sources for a smooth operation.
Lack of skilled professionals is another challenge that needs to be addressed. Apart from good industry experience, people handling the GIS and AI system need to have comprehensive knowledge in machine-learning and data science. Nevertheless, as more professionals enter the domain, we can expect this issue to be resolved soon.
Artificial intelligence can combine with GIS and help organizations make quick and informed decisions. The two technologies are remarkably interrelated and will increasingly work together in various domains like asset tracking and management, fleet localization, and location intelligence. Eventually, this is set to change the GIS landscape and improve the potential of GIS.