Artificial Intelligence (AI)has become a word that symbolizes the next stage of innovative technological transformations and how to direct the future industry. Artificial intelligence has been influential in many sectors with intelligent algorithms, data classification and intelligent predictive analysis.
The term that combines the delicate direction of GIS with artificial intelligence methods, effective analysis, and solution-based approach to artificial intelligence Spatial Artificial Intelligence (Geospatial AI) .
Spatial Artificial Intelligence can also be called a form of learning a new machine based on a geographical component.
How does it work?
With the help of simple smartphone applications, people can give real-time feedback about the conditions in their surroundings, such as traffic jams, peak hours, user experiences, ratings (low, medium, or dense). The data is then blended, sorted, analyzed, and on this count, accuracy and precision are increased due to the large number of users contributing to the database.
This approach to using location information will not only be interpreted as missing information, but it will also help more efficient solutions for specific geographical regions. For example, you can estimate which route in the city will encounter the most bottlenecks, or the way in which the vehicle traffic load must be distributed, or the traffic flow redirection.
Various applications of Spatial Artificial Intelligence
As an example, traffic congestion is a problem we encounter almost every day from our homes to workplaces and back to home. However, Spatial Artificial Intelligence (Geo.AI) applications are found in a variety of sectors, including location and GIS users. Journey sharing companies, logistics, agriculture, measurement and infrastructure are some of the outstanding examples.
uber, lyft etc. travel sharing companies can use feedback from customers, the intensity of the car, and whether they are eligible for customer acquisition.
In the logistics and supply chain, Spatial Artificial Intelligence, you can get more accurate location information that will make product delivery easier and save you time.
Today, there are systems based on the deep learning principle, which are cloud based, project based, each having a large amount of data storage and all working to solve the same problem. However, it is true that the use of deep learning at the level of automation up to several years past is not appropriate due to constraints on cost implementation or restrictions on the application of technology.
Likewise, Spatial Artificial Intelligence capabilities will be developed to serve multiple purposes as it has a location component in artificial intelligence applications in accordance with the objectives of the industry.
Business in general Spatial Artificial Intelligenceplanning, resource planning and decision making will significantly improve, anticipate the increase in demand and supply, identify high and low margin expectations, increase supply chain efficiency and optimize service delivery in various sectors.
Spatial Artificial Intelligencewherever the positioning information of the specification is analyzed; our business will continue to come out more often with the features of facilitating our business and our ability to decide our place!
Aditya Chaturvedi-https: //www.geospatialworld.net/