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Monitor the spread of COVID-19 with Artificial Intelligence in Geospatial Domain

In as of late's global, we are moving in opposition to automation of the applications for societal benefits. In this context, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques are providing an additional edge to the process of automatization and type building. Artificial intelligence (AI) refers to the simulation of human intelligence in machines which might be programmed to assume like people and mimic their movements.

Geospatial Technology is an rising field of analysis that incorporates Geographic Information System (GIS), Remote Sensing (RS) and Global Positioning System (GPS). It allows us to procure data that is referenced to the earth and use it for analysis, modelling, simulations and visualization. It can give quick, simple and financial answers in almost each and every field of lifestyles including health, training, agriculture, ingesting water, sanitation, sensible town planning and crisis management. The geospatial technology when coupled with the complicated AI algorithms can enormously reinforce the processing of giant spatial data and can also produce correct predictions.

There are numerous applications of AI and ML within the geospatial area including Disease outburst identity, Urban and Rural Planning, Illegal Construction or Encroachment Detection, Crop Mapping and Yield Prediction, Business, Tourism, Disaster Management and lots of more.

A short lived description of one of the most essential applications is summarised underneath:

Disease Outburst Identification

The satellite photographs in conjunction with the AI-enabled machine can be used to map and observe the unfold of several illnesses akin to malaria, dengue and so forth. The recent danger because of novel COVID-19 disease can be mapped geographically and observe the unfold of the same the usage of the spatial data. These digital maps can be used by the Govt. government for effective planning at the native level in opposition to combating the unfold of the disease in different spaces.

Urban and Rural Planning

Geospatial technology plays a very important position in sensible town planning and rural building. The current land and water assets within the towns and villages will also be mapped the usage of the high-resolution satellite photographs and techniques for his or her utilisation in more than a few applications will also be recognized. Also, geotagging of the very important infrastructures akin to schools/faculties, clinical centres/dispensaries, overhead tanks, ration distribution centres, landfill websites and so forth. will also be performed to identify the distance spaces for any region in GIS.

Illegal Construction

Land is a pricey commodity, and its encroachment for more than a few uses is a significant issue in lots of the towns in India. In the present state of affairs, the identity of the encroached spaces is an overly challenging and time-consuming activity. Towards that, automated extraction of constructions from high-resolution satellite photographs can give as one of the most answers for locating the encroached spaces. The geo-visualization device and AI-based DSS will also be evolved to permit the Govt. government to briefly act upon in case of any unlawful development of their land spaces.

Disaster Management

Geospatial technology is effectively being utilised for mapping and prediction of the different herbal disasters including floods, droughts, landslides, forest fires and so forth. Usually, mapping and prediction of such disasters involve the analysis of the satellite datasets received at other dates (temporal dataset).

In collaboration with AICTE and different global organizations, Bennett University has arrange the largest Artificial Intelligence (AI) Skilling Platform in India known as

The Computer Science Engineering (CSE) Department of the Bennett University is leading the initiative by analysing the satellite photographs of various spatial and spectral resolution the usage of AI techniques for extracting the different landcover features akin to roads, agricultural fields, water bodies, settlements and so forth. The students also are running in opposition to growing a framework for extracting building footprints from excessive spatial resolution photographs the usage of deep learning architectures to take on with the issue of unlawful development in Government lands, techniques for tracking the expansion of the vegetation and predicting the crop yield and mapping of forest fires in accordance with satellite observations.

This article is written by Dr Kuldeep, Assistant Professor, School of Engineering & Applied Sciences, Bennett University.

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