This review presents the new opportunity for research and developer teams working on LBS-enabled solutions and Internet of Things infrastructure. Geo2Tag is the world’s most popular open source LBS platform1. Recently the IEEE IoT technical team listed Geo2Tag as a platform for making IoT solutions in city tagging scenarios2.
The Geo2Tag platform enables simultaneous work on multiple different services and seamless creation of new services without server reloads. The platform provides a sophisticated spatiotemporal API for the services, which allows geo-fencing with altitude support, date/time filtering (including support of BC dates), data aggregation and visualization, and so on. At the same time service creation on Geo2Tag is an easy and cozy process, and developers have access to the large library of templates and functions implementing typical functionality. This, plus the use of an open source license, makes Geo2Tag the most cost-efficient and technically best available backend for commercial and non-commercial geo-apps.
Geo2Tag supports Platform as a Service Architecture (PaaS). It uses virtualization instruments such as Vagrant and Docker that enable easy integration with a majority of cloud services. The main services provided by the platform are:
- Storage, processing and visualization of spatiotemporal data.
- Simultaneous work on several location-based services inside one instance of the platform.
- Fast content-building startup by importing and pre-processing data from the open databases.
The Geo2Tag data model is as follows. Point is an atomic element of spatiotemporal data. Channel is formed as a set of points. The service is a set of channels. The user is an application or human actor that performs interaction with the platform.
The external interface for LBS developers is provided by REST requests over HTTP. API provides control over spatiotemporal data, geo-fencing functional and administrative actions for a service and the whole platform instance. The spatiotemporal data filtration has several criteria: date and altitude intervals, spatial region, and allowed channel set. All criteria can be applied independently. All REST requests for geo-data support the GeoJSON standard. API authorization is implemented by the use of the OAuth2 protocol. Geo2Tag provides an API for high performance geo-data visualization and has a special web-service for displaying results of REST queries on a custom map based on a leaflet.js library with changeable map provider. With this solution geo-data elements (points) can be grouped into clusters, which makes data on the map easy to navigate and decreases the volume of used RAM.
Geo2Tag provides an open API for developing third-party plugins. A plug-in is an isolated extension for a platform REST API, which can perform background computations on services data and can be turned on and off without server restart. The plug-in system also contains common interfaces for developing open data plug-ins. These extensions allow the importing and processing of external open access web datasets.
Geo2Tag is used as a platform for various apps and use cases3. As an example, the Open Karelia museum system (www. openkarelia.org) networks a number of museums in Russian and Finnish and provides a common set of e-Tourism services. Other examples of Geo2Tag based services are: nearest doctor search, tracing public transport, car fleet services, and personal tracker.
Future development of Geo2Tag is focused on improving the usability of the REST API, getting more LBS developers on board. We continuously work to further improve mobile power consumption and performance and increase usability. More content is made available to developers via the API and plug-ins. We welcome you to start using Geo2Tag by visiting www.geo2tag.com, or contacting us via email (Mark.Zaslavskiy@fruct.org, Kirill.Krinkin@ fruct.org, Sergey.Balandin@fruct.org).
1MetricsKey rating http://metricskey.com/open/open-source-location-basedservices/ + is the 2nd in Google for “LBS platform” (after TomTom)
2The reference is at the bottom of the first page in PDF http://iot.ieee.org/ iot-scenarios.html?prp=6.
3E. Balandina, S. Balandin, Y. Koucheryavy, and D. Mouromtsev, “IoT Use Cases in Healthcare and Tourism,” Proc. 17th IEEE Conf. Business Informatics (CBI 2015), Lisbon, Portugal, July 13–16, 2015. pp. 37–44.