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Artificial intelligence in GIS: what you should know about AI integration in GIS?

In the past decade, GIS has been increasingly leveraging artificial intelligence, offering a powerful combination for ensuring accurate location intelligence. Read on to learn about the exciting and evolving field of artificial intelligence in GIS.

In the modern world, artificial intelligence is gaining tremendous momentum due to its potential to provide precise and valuable insights to businesses and individuals. As a result, several tech giants are investing heavily in research and development in this field and expanding the applications of artificial intelligence to various domains such as finance, healthcare, manufacturing, and many more. When applied in GIS, artificial intelligence can transform GIS technology by improving the efficiency and accuracy of spatial data capture and analysis.

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, bringing high stress on the need for accuracy at all stages of data processing. This is where artificial intelligence can help. Artificial intelligence technology mimics the human brain and comes with self-learning capabilities due to which it becomes possible to process large sets of data and find patterns that humans might miss. As a result, artificial intelligence is capable of ensuring high levels of accuracy while capturing, storing, and analyzing location data. It can also greatly improve efficiency by decreasing the time needed to collect, analyze, and create maps.

Further, artificial intelligence can improve the selection of spatial patterns and also assess the predictive capability of spatial modeling techniques. This makes the application of artificial intelligence highly useful in the field of landscape ecology where determining the pattern of the landscape is important for classification.

The transportation industry is another domain where GIS can integrate artificial intelligence. The advanced AI capabilities can help road network professionals quickly process emergency situations such as accidents or bad weather and re-route in the best possible way.

Another useful scenario of artificial intelligence is in the field of geomarketing. GIS combined 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, there are several hurdles in the way of integrating the two, which need to be addressed.

GIS requires complex infrastructure and storage resources and for artificial intelligence and GIS integration to function efficiently, there is a need for a huge investment which could be a challenge, particularly for smaller companies. Apart from this, since GIS requires a huge volume of diverse data, the integration process also poses data structure challenges. Hence, for a successful AI and GIS integration, a support system with reliable data sources is crucial.

Another challenge in the way of AI and GIS integration is the lack of skilled professionals. For efficient handling of GIS and AI systems, we need professionals who have a comprehensive knowledge of machine learning and data science, which in many situations is hard to find. Nevertheless, as more professionals are entering the domain and proving their expertise, we can expect this issue to be resolved soon.

The way forward

Artificial intelligence can combine with GIS and help organizations make quick and informed decisions. The two technologies are remarkably interrelated and could increasingly work together in various domains like asset tracking and management, fleet localization, and location intelligence. Eventually, the integration of artificial intelligence in GIS is set to transform the GIS landscape and tremendously improve the potential of GIS.

At SBL, our multi-disciplinary team of GIS professionals can work to integrate advanced technologies into your location intelligence requirements for precise spatial data. Contact us today, to know more.

Frequently asked questions

1. How artificial intelligence is used in GIS?

Artificial intelligence is an accurate tool for optimal problem-solving and intelligent decision-making. In the domain of GIS, we can apply artificial intelligence in various scenarios such as prediction, classification, and segmentation.

 2. What is artificial intelligence used for?

With artificial intelligence implementation, machines could perform tasks in a way similar to human beings and further learn from experience. The advanced capabilities of artificial intelligence technology allow businesses to
leverage neural networks and perform data analysis with high accuracy. As a result, artificial intelligence finds application in a wide range of domains including healthcare, transportation, manufacturing, and many more.

3. What is machine learning in GIS?

Machine learning incorporates data-driven algorithms to automate the clustering, prediction, and classification of data. It can support accurate spatial pattern detection and plays a crucial role in spatial problem-solving.

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