GIS as a complete SaaS with Cloud Computing and Artificial Intelligence
Working with GIS requires big data handling and regular software updates. SaaS- Software as a Service helps the user to work efficiently without investing most of their time in solving other issues.
GIS as a complete SaaS using Cloud computing and Artificial Intelligence
GIS is all about acquiring data, processing and making it available to the user. Spatial and non-spatial data analysis requires a robust platform. Since Data processing and storage is very time consuming and needs expertise, professional assistance is required while working with GIS. Handling Large volume of data, suitable software requirement and regular up-gradation of software involve significant planning.
To overcome this complex process, SaaS (Software as a Service) is a suitable solution. SaaS delivers centrally hosted software through internet. One could easily access the application in a web browser without actually downloading and configuring the software. It is sometimes referred to as “on-demand software”. It allows users to connect to and use cloud-based apps via internet. (For eg: the University of Southern California offers its students ‘ArcGIS Pro’ to conduct GIS exercises using common industry tools).
Seamless upgrades and deployment of new features help the user to keep the software up to date. Most of the time users don’t even notice that their software has been upgraded automatically to an advanced version. SaaS applications prevent the user from configuration inconsistencies as these are hosted in an optimal environment.
Google Earth and Bing Maps provide mapping tools but they couldn’t be used for large scale GIS. If GIS as a service succeeds, integration of GIS with many applications would be easy such as smart mapping, data collection, tracking and more.
A geospatial cloud, providing GIS as SaaS is able to give many analytic and visualisation capabilities and ready to use map or imagery layers. Integrated with Artificial Intelligence and machine learning, the GIS cloud could automate techniques like classification, change detection, clustering etc.
GIS as SaaS provides Cloud-based mapping tools, open data platforms, Artificial Intelligence integration, geospatial data editing and sharing and helps in handling big data.
At CTIA Wireless Conference, eSpatial, the Web GIS and geographic business intelligence company announced to provide the full function Web GIS as a SaaS. Now, eSpatial is offering SaaS web-based GIS software which could easily transform data into visual maps. Census data integration, geocoding, interoperability, spatial analysis, internet mapping, creating maps, colour coding, labelling are some of the features provided by eSpatial. Planning and routing for field sales, plotting pins on an interactive map, management of sales territories, radius maps, use of annotations are other features offered by eSpatial.
Like many other industries, here also Artificial Intelligence has a major role. Machine learning algorithms analyse the stored data and automate the processing.
Cloud computing and SaaS has made mapping fast, easy and powerful. Geospatial cloud supports mobile applications in offline mode also. Feeds from cameras, drones, and satellites could be stored for analytical purpose.
Cloud Service Models
SaaS, PaaS and IaaS, i.e. Software as a Service, Platform as a service and Infrastructure as a service respectively are the three models of cloud service.
SaaS utilizes the internet to deliver applications to users without downloading or installation. Google Apps, Dropbox and Concur are some examples of SaaS.
PaaS provides a framework for developers. It is built on virtualization technology. Eg: Windows Azure, Google App Engine.
IaaS gives infrastructure to organisations. In IaaS resources are available as a service. Eg: Microsoft Azure, AWS, Digital Ocean etc.
Geospatial cloud is already in use by millions of people. Many are using ArcGIS online. Esri cloud allows the user to create, share, edit maps. Cloud SaaS supports GIS as a service in combination with imagery, applications, and data as a service.
Companies like ESRI, Google Maps (Google), Bing Maps (Microsoft), Super Map, Zondy Crber, GeoStar, Hexagon Geospatial, CARTO and GIS Cloud are participating in GIS Cloud computing technology.
Continuous updates and open access helps the public to gather reliable information with the ability to integrate the latest databases. Various sectors could take advantage of GIS SaaS including geo-referenced weather services, traffic management, research, public safety and emergency, E-commerce and road infrastructure projects.