AI/ML & their Impact on Geospatial Technology Space
In a recent conversation with Charulatha (Correspon- dent, Silicondindia), Saurabh shared his insights on the current geospatial technology scenario in India and various other aspects surrounding it. Below are a few key extracts from the exclusive interview
Share your thoughts on the integration of AI and ML technologies in the geospatial space in recent times
AI and ML are increasingly becoming vital components of geospatial technologies in recent times and are considered to be the most powerful tools in the space of geospatial analysis. Traditionally, geospatial analysis was a very time-consuming process, most of which had to be done manually. Although we were able to gather the necessary results, it would not service the time sensitive nature of the task as efficiently as it is being done today using AI/ML. Today, AI/ML algorithms can sift through huge amounts of remote sensing data that is collected through images from various satellites, analyze that data and complete the tasks that earlier took days in just a few hours. Some of the other key use cases of AI/ML technologies in the geospatial area are identifying land use, predicting the spread of wild fire, analyzing the cause of natural disasters and many others. This has resulted in a significant cut-down in durations for taking crucial decision during the time of crisis.
AI/ML algorithms can sift through huge amounts of remote sensing data that is collected through images from various satellites, analyze that data and complete the tasks that earlier took days in just a few hours
How is the implementation of augmented reality in geospatial technology impacting urban planning and environmental management?
The biggest advantage of augmented reality technology is the diverse variety of visualization options that it offers. As a result, the number of use cases for augmented reality (AR) in geospatial technology has increased drastically in recent times. Additionally, we are also seeing an increased usage of the combination of AR geospatial technologies in a variety of mobile video games lately; Pokemon Go being the most well-known example. While AR acts as an enabler for visualization, geospatial technologies enable real time synchronization of the physical location into the location within the game. AR and geospatial technology have now enabled creating a real life 3D replica of an entire city, which will have a huge number of applications in terms of urban planning and infrastructure development projects. Also, AR coupled with geospatial technology and real time data has the capability to overlay real time environmental data, making it easier to take critical decisions pertaining to air/water quality and other environment related issues.
Throw some light on how geospatial data be used in public health, such as disease tracking and healthcare resource allocation?
The recent covid pandemic is the best example in this regard, wherein via geospatial tech- nology, the government was able to monitor the disease among general public, track its spreading pattern and accordingly take preventive measure in order to contain further spreading of the disease to other areas. By combining predictive analysis with geospatial data, we can also easily locate individuals who are at very risk of being exposed to the disease based on their travel data. This was the baseline of disease tracking and management across the world during the covid pandemic. Another very important use case of geospatial data is in allocating healthcare services such as ventilators, ICU beds and others to general public.
"AR and geospatial technology have now enabled creating a real life 3D replica of an entire city, which will have a huge number of applications in terms of urban planning and infrastructure development projects"
How do you expect the geospatial technology landscape to evolve in the coming years?
Geospatial technology will have a very transformative impact on almost all industries in the days to come. As the AI/ML algorithms grow and become more advances, they will no doubt bring-in more automated and sophisticated geospatial analysis use cases. Also, real time analysis will gain widespread prominence, and technologies like IoT will streamline the entire data collection and automation process. Lastly, geospatial technology will continue enhancing the effectiveness of various use cases in the defense sector – be it in terms of missile targeting systems, navigational systems and many others.